50+ Kubernetes Jobs in India

Job Title : Software Development Engineer II (SDE 2) – Java or Golang (Backend)

Experience : 3+ Years

Location : Bengaluru

Working Days : 5 Days WFO

Notice Period : Immediate to 15 Days

Interview Process : 3 Client Rounds

Job Overview :

We are looking for an SDE 2 – Backend with strong hands-on experience in Java / Spring Boot or Golang to design, develop, and maintain scalable, high-performance backend applications. Candidates with experience in caching services will be highly preferred.

Mandatory Skills :

Java, Spring Boot, Golang, Gin, gRPC, REST APIs, Microservices, MySQL / PostgreSQL / Oracle, System Design, Caching, Data Structures & Algorithms, Git, CI/CD, Docker, Kubernetes, AWS / GCP.

Key Responsibilities :

• Design, develop, test, and deploy scalable backend applications and APIs.
• Develop microservices using Java / Spring Boot or Golang.
• For Golang roles, experience with Gin and gRPC is preferred.
• Work with MySQL, PostgreSQL, Oracle, or similar databases.
• Design and optimize caching solutions for application performance.
• Participate in system design and architecture discussions.
• Conduct code reviews and write unit/integration tests.
• Troubleshoot bugs and performance issues.
• Collaborate with Product, QA, and other engineering teams.
• Contribute to CI/CD, cloud, and DevOps practices.

Requirements :

• 3 to 5 years of backend development experience.
• Strong proficiency in Java / Spring / Spring Boot or Golang.
• Good understanding of REST APIs, Microservices, DSA, and System Design.
• Experience with relational databases.
• Strong debugging and problem-solving skills.
• Exposure to AWS/GCP, Docker, Kubernetes, Git, and CI/CD.
• Java candidates with end-to-end application design experience are preferred.
• Exposure to AI/ML tools or Low-Code/No-Code frameworks is a plus.

Interview Process :

Round 1 – LeetCode / Coding Round

• Data Structures & Algorithms
• Problem-solving and coding proficiency

Round 2 – System Design

• System architecture
• Scalability and performance
• API and database design
• Caching and distributed systems

Round 3 – Hiring Manager Round

• Technical depth
• Project and ownership experience
• Problem-solving approach
• Communication and collaboration
• Role and culture fit

Job Title : MLOps Engineer

Mode: Hybrid

Experience : 4 to 7 Years

Location : Hyderabad (Priority)/Bengaluru locations only

Notice Period : Immediate Joiner

Job Summary:

We are looking for a skilled and proactive ML Engineer with strong expertise in Python, Databricks, and Machine Learning model development. The ideal candidate should be proficient in building scalable data pipelines and deploying ML models, with a working knowledge of MLOps principles and tooling. This role offers an opportunity to work on impactful AI/ML initiatives in a collaborative environment.

Key Responsibilities:

• Develop and maintain machine learning pipelines for training, testing, and deploying models

• Design and implement infrastructure for managing and monitoring machine learning models

• Work with data scientists to build scalable, efficient, and automated model training and testing processes

• Collaborate with software engineers to integrate machine learning models into production systems

• Automate and optimize the deployment and scaling of machine learning models in a distributed computing environment

• Monitor and troubleshoot machine learning systems and infrastructure to ensure high availability and performance

• Develop and maintain documentation and best practices for MLOps processes and procedures.

Experience:

Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field

• 3+ years of experience in MLOps or related field, including building and deploying machine learning models at scale

•Proficiency in programming languages such as Python, Java, and C++

•Experience with machine learning frameworks such as TensorFlow, PyTorch, and Keras

• Experience with containerization technologies such as Docker and Kubernetes

• Strong understanding of DevOps principles and practices

• Experience with cloud computing platforms such as AWS, Azure, or Google Cloud

DevOps Engineer – 3+ Years

About the Role:

We are looking for a DevOps Engineer with 3+ years of hands-on experience to build and manage CI/CD pipelines, cloud infrastructure, containerized deployments, and production monitoring.

You will work closely with Architects, Developers, QA, and Integration teams to deliver secure, scalable, and production-ready applications across AWS and Microsoft Azure environments.

What You’ll Do

• Design, implement, and maintain CI/CD pipelines using GitHub Actions, Azure DevOps, Jenkins, or similar tools.
• Deploy, manage, and monitor applications on AWS and/or Microsoft Azure.
• Build and manage containerized applications using Docker.
• Provision and manage cloud infrastructure using Terraform / Infrastructure as Code (IaC).
• Configure IAM, Key Vault/Secrets Manager, networking, SSL, and secure deployment processes.
• Implement monitoring, logging, alerting, backup, and disaster recovery solutions.
• Troubleshoot build, deployment, and production issues in collaboration with development teams.
• Maintain deployment documentation, runbooks, and operational procedures.

What We’re Looking For

• 3+ years of experience in DevOps, Cloud, or Infrastructure Engineering.
• Strong understanding of DevOps principles and CI/CD practices.
• Hands-on experience with AWS and/or Azure.
• Experience with GitHub Actions, Azure DevOps, Jenkins, or similar CI/CD tools.
• Strong Linux administration skills.
• Hands-on experience with Docker and container lifecycle management.
• Working knowledge of Terraform or other IaC tools.
• Good understanding of DNS, SSL, Load Balancers, Firewalls, and Virtual Networks.
• Basic operational knowledge of PostgreSQL/MySQL.
• Strong troubleshooting and production support skills.
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Cloud Technologies:

AWS: EC2, IAM, S3, VPC, RDS, CloudWatch, ECR

Azure: App Services, Container Apps, Key Vault, Azure Monitor, Application Insights, Azure Container Registry

Good to Have

• Kubernetes (AKS/EKS) or Azure Container Apps.
• Prometheus, Grafana, ELK, CloudWatch, or Azure Monitor.
• GitHub Enterprise, Branch Protection, and CI/CD quality gates.
• Security tools such as CodeQL, Dependabot, Trivy, or SonarQube.
• Shell, Bash, PowerShell, or Python scripting.
• Microsoft Entra ID (Azure AD), OAuth, or SSO.
• Exposure to enterprise integrations such as Oracle, Kafka, REST APIs, or OIC.

What We Value

• Strong ownership and problem-solving mindset.
• Good communication and documentation skills.
• Ability to collaborate effectively in Agile teams.
• Passion for automation, security, and continuous improvement.

Senior DevOps Engineer

AWS Infrastructure, Kubernetes & Production Operations

📍 Mumbai (On-site) | Full-time | 5-8 years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

We are hiring a Senior DevOps Engineer for a dedicated client engagement building an AI platform that turns a written prompt into a working, deployed web application.

The platform runs entirely on our own Kubernetes on AWS in Mumbai: multiple clusters, self-hosted Kafka, PostgreSQL, Redis and a complete observability stack, with untrusted AI-generated code executing inside isolated sandboxes.

This role owns that infrastructure end to end.

The mandatory requirement is hands-on production ownership of self-managed Kubernetes and self-hosted stateful services.

This is not a managed-services role: almost nothing here is a click in a console, and there is no platform team above you to escalate to.

You will pair daily with the Tech Architect who owns the architecture, and you own its execution, which covers clusters, networking, pipelines, observability, isolation, and the monthly cloud bill as a number you can explain line by line.

The role carries a deliberate path into LLM infrastructure over the first year, and we are saying so up front because we want someone who wants that direction.

A typical week includes rehearsing a cluster upgrade in a lower environment, tracing an unexplained cost line to its source, tuning autoscaling so non-production shuts down cleanly overnight, and hardening the boundary that keeps AI-generated code away from everything else.

Responsibilities:

Kubernetes Platform Ownership

Own multiple EKS clusters separated by trust boundary, covering platform services, messaging, sandboxed build environments, and hosting for customers' published applications.

Node pools, taints and tolerations, resource requests versus limits, pod disruption budgets, and the scheduling decisions that determine whether a cluster is efficient or merely large.

Plan and execute version upgrades without customer-visible downtime.

Infrastructure as Code

Everything in Terraform, with no console changes that are not in code.

Build reusable cluster modules rather than copies.

Keep state and reality in sync, and treat drift as a defect.

CI/CD and Release Engineering

Own the GitHub Actions pipelines and self-hosted runners: OIDC-based AWS authentication with no stored credentials, image builds, and rollouts across development, QA and UAT.

Move manifest templating from scripted substitution to Kustomize or Helm.

Make a rollback as routine as a deploy.

Network Architecture and Workload Isolation

VPC and subnet design, ingress through load balancers and service mesh, and eBPF-based network policy.

The platform runs code we did not write, so the isolation boundary is a primary deliverable: default-deny egress, kernel-level sandboxing for untrusted workloads, no platform credentials inside tenant pods, and one project per pod with nothing shared between customers.

Observability

Operate a self-hosted stack of Prometheus, Grafana, Loki, Tempo, OpenTelemetry and Alertmanager.

Build alerts engineers trust rather than mute.

Know what belongs in a metric, a log and a trace, and keep metric cardinality under control as tenant count grows.

Autoscaling and Capacity

Node autoscaling with Karpenter, and workload autoscaling on the signal that actually matters, which is queue depth or a schedule rather than CPU wherever CPU misleads.

Implement scale-to-zero across non-production and warm-pool patterns where cold starts are unacceptable.

Size capacity from measurement, not assumption.

Cost Operations

Own the cloud bill as an engineering artifact.

Attribute spend per cluster and per environment, right-size against real utilisation, apply Spot where interruption is safe and never where it is not, and investigate any line you cannot explain.

Instance family selection is a cost decision: match the family to the resource that binds first.

Self-Hosted Stateful Services

Operate Kafka, PostgreSQL and Redis in-cluster, covering persistence, replication, failover, upgrades, and backups you have actually restored from.

Rehearse the restore and record how long it took.

Security Posture

IAM and workload identity, migration away from static credentials, secret management, web application firewall rules, and closing the gaps you find.

Credential rotation and least privilege are ongoing work, not a one-time project.

AI Infrastructure (Growth Path)

Within the first year, take on the infrastructure serving AI workloads: multi-provider LLM gateway and routing, token and cost attribution, rate-limit-aware capacity planning, LLM tracing with Langfuse, vector databases such as pgvector and Qdrant, and self-hosted embedding models including GPU nodes on Kubernetes.

This is inference operations, not model training.

AI-Assisted Engineering Discipline

Use Claude, Cursor, and similar tools day to day for infrastructure code, scripts, and pipelines.

Set the team standard for safe use, review, and validation of AI-generated infrastructure before it ships.

Requirements:

Hands-on Production Ownership of Self-Managed Kubernetes (Mandatory)

Must have personally operated a production Kubernetes estate with operational responsibility including oncall, incident response, and upgrade ownership.

You understand why a cluster ends up over-provisioned and how to fix it.

Managed-platform-only experience, or Kubernetes limited to deploying into a cluster someone else runs, does not qualify.

5+ Years of Overall Engineering Experience

With at least 3 years in DevOps, SRE, or platform engineering.

This is not an ML science role.

A strong infrastructure background with genuine appetite for AI infrastructure is exactly the profile we want.

Proven Ability to Learn an Unfamiliar Technology to Production Depth

We are hiring for trajectory as much as for current tooling, so this carries real weight.

Be ready to walk us through something you picked up from scratch and then owned in production: what you got wrong in the first attempt, how you found out, and what you would do differently.

A candidate with a shorter tool list and a strong record of learning will be preferred over a longer list learned only at the surface.

Self-Hosted Stateful Services in Production

One or more of Kafka, PostgreSQL, Redis, or Elasticsearch operated by you, not by a managed service.

Backups, restores, failover, and version upgrades.

This matters more than any other line here, because almost everything we run, we run ourselves.

Infrastructure as Code Depth

Terraform in anger, including modules, state management, and recovering from drift.

Docker and image optimisation.

AWS at Depth

EKS, EC2, VPC, IAM, S3, RDS or Aurora, and load balancing.

You can read a bill and explain where the money went.

Networking Depth

VPC and subnet design, NAT and egress paths, load balancer behaviour, DNS, TLS, and Kubernetes networking.

Able to reason about address exhaustion and routing limits before they are hit rather than after.

Observability Depth

Production experience with Prometheus, Grafana, and a log or trace backend.

Comfortable instrumenting with OpenTelemetry.

Able to define alerts that are actionable and to resist the cardinality that makes a metrics system collapse.

CI/CD and Deployment Automation

Strong with GitHub Actions or GitLab CI, including self-hosted runners and short-lived cloud credentials.

Experience making deploys and rollbacks safe and routine.

Cost Management for Cloud Infrastructure

Demonstrated ownership of a cloud bill: right-sizing, reserved capacity or savings plans, Spot strategy, and tracing an anomaly to its cause.

Reliability Engineering

Comfortable defining SLOs and being accountable for them.

Experience with graceful shutdown, connection draining, disruption budgets, and long-lived connections such as WebSockets that autoscaling can otherwise sever.

Nice to Have:

• arm64 and Graviton estates
• eBPF networking with Cilium
• container runtime isolation such as gVisor, Kata, or Firecracker
• Kafka operations including partition and consumer-group management
• service mesh with Istio
• GPU workloads on Kubernetes
• hands-on familiarity with LLM observability tooling such as Langfuse or LangSmith
• India data-protection and residency requirements under the DPDP Act
• AWS certifications

We are seeking Senior Backend Engineers who can hack around multiple technologies and build highly scalable, low-latency, distributed systems with RESTful services. You will be responsible for developing new software products (internal) and solving complex technical challenges for scale-ups and enterprise companies. You should excel in working with large-scale applications and frameworks and have outstanding communication and leadership skills.

You’ll be responsible for—

• Writing clean, high-quality, high-performance, and maintainable code.
• Solving complex technical problems.
• Performing an objective analysis of the problem statement and coming up with an unbiased technical solution before writing a single line of code.
• Coordinating cross-functionally to ensure the project meets business objectives and compliance standards.
• Participating in and driving code reviews.
• Building robust, secure, and scalable microservices.
• Implementing RESTful services with a metric-driven API Gateway.
• Ensuring sub-second server response and will be responsible for implementing relational, document, key, object, or graph data stores, index stores and messaging stores as needed.
• Tracking defects and work with business owners and users to triage bugs and manage backlog
• Taking ownership to run and maintain Cloud infrastructure.
• Evaluating relevant technologies, influencing and driving architecture and design discussions.
• Architecting & designing the platform.
• Mentoring junior engineers helping them grow, performing code reviews, system monitoring & delegation.
• Writing documentation & create engineering processes.
• Working as an individual contributor.
• Helping drive KPIs with Product.
• Taking ownership of backend systems.
• Helping with unit tests & QA process.
• Scaling the engineering team.
• System scaling to hundreds of millions of users.
• Working with product managers and designs.

Requirements

What you need—

• Overall 5-8 years of experience in software development with a strong base in Golang/Java/Python and a degree in Computer Science(optional).
• Experience with Go, K8, Docker, AWS, and CI/CD.
• Experience with micro web frameworks – like Springboot, Gin/Mux.
• Experience in working with microservice architectures, Transactional systems, and Distributed environments.
• Exposure to building RESTful APIs with monitoring, fault tolerance, and metrics (with something like Hystrix).
• Experience with MySQL, and NoSQL (Cassandra, Redis, DynamoDB).
• Experience in server-side services using ElasticSearch and ESB - Camel, ActiveMQ.
• DevOps experience.
• Experience with AWS stack.
• Excellent attention to detail.
• Outstanding written and verbal communication skills.
• To be a self-starter who can work well with minimal to no guidance in a fluid environment.
• To be excited by challenges surrounding the development of highly scalable & distributed systems.
• To be agile and able to adapt quickly to changing requirements scope and priorities.
• To be experienced in working on massively large-scale data systems in production environments.
• To have led or mentored an engineering team before(optional).
• To have contributed to open-source projects.
• To have a strong drive & desire for continued growth.
• Proficiency in English.
• Experience with Web3(optional).

Benefits

What you get—

• Best-in-class salary: We hire strong talent and compensate accordingly.
• Meet and learn from designers, engineers, product leaders, and AI practitioners.
• Continuous learning: Work with a world-class team and stay close to the latest in AI, engineering, and product development.
• High-impact work: Build AI-first systems and products used at scale by global clients.

About the Programme

Developing an enterprise AI platform focused on financial compliance and intelligence.

Role Overview

We are looking for a Backend Engineer to own the integration layer of the platform. You will build the APIs and services that connect AI outputs back into operational workflows, integrate with government portals and external data sources, and ensure that the system interacts reliably with RIL’s existing infrastructure. This role requires equal measures of technical rigour and pragmatism to deliver reliably within a fast-moving build timeline.

Key Responsibilities

Integration Mapping & Design

•       Work with the Solutions Architect to map every integration touchpoint — ERP workflow interfaces, government portals, supplier portals, and banking feeds.

•       Understand the latency requirements for each integration and design accordingly — real-time endpoints and batch integrations have fundamentally different design constraints.

•       Design robust fallback mechanisms for every integration — if the AI model is unavailable or low-confidence, the system must degrade gracefully without blocking operational workflows.

Real-Time API Development

•       Design and implement the API layer that connects the AI inference layer to operational systems — clean contracts, versioned endpoints, and clear error responses.

•       Ensure all real-time integrations are built with resilience patterns — circuit breakers, retry logic, timeouts, and graceful degradation under load.

Government Portal & External Integrations

•       Build integrations with government portal APIs for inward supply data, vendor return filing status, and notice data where available via official channels.

•       Build the integration with the customs data portal

•       Manage the specific constraints of government API ecosystems — rate limits, authentication flows, schema changes, and reliability issues that differ significantly from commercial APIs.

Monitoring & Production Stability

•       Build API monitoring and alerting covering latency, error rates, and upstream availability so integration failures are caught before they affect the compliance team.

•       Work with the MLOps Engineer to ensure model inference endpoints are stable and performant enough for the real-time integration to depend on.

•       Maintain clear API documentation so the Full Stack Engineer and other squad members can consume integrations without dependency.

Required Qualifications

Education

•       B.E. / B.Tech / M.Tech in Computer Science, Information Technology, or a related field.

Experience

•       5+ years of backend engineering experience with a focus on API design and enterprise system integration.

•       Proven experience building and maintaining production-grade integrations with complex or legacy enterprise systems.

•       Experience with real-time, latency-sensitive API development in an operational context.

Technical Skills

•       Languages: Python (primary); working knowledge of at least one of Java, Go, or Node.js.

•       API Design: REST API design principles, versioning, authentication (OAuth 2.0, API keys, mTLS), and contract-first development.

•       Resilience Patterns: Circuit breakers, retry logic, rate limiting, bulkheads, and graceful degradation.

•       ERP Integration: Experience integrating with SAP or equivalent large ERP systems — BAPIs, RFC calls, or event-driven extraction patterns strongly preferred.

•       Async & Messaging: Kafka, RabbitMQ, or equivalent for event-driven integration patterns.

•       Containerisation: Docker and Kubernetes for deploying and managing API services.

•       Observability: API monitoring, distributed tracing (Jaeger, Zipkin, or equivalent), and structured logging.

Preferred Qualifications

•       Prior experience with government API ecosystems — GSTN, ICEGATE, or similar; understanding of their specific constraints and reliability characteristics.

•       Experience building integrations that serve ML model inference endpoints in a production setting.

•       Familiarity with SAP integration patterns — SAP BTP, OData services, or SAP API Hub.

•       Prior work in fintech, compliance, legal technology, or similarly regulated environments.

•       Experience with API gateway tooling — Kong, AWS API Gateway, or equivalent.

About the Programme

Developing an enterprise AI platform focused on financial compliance and intelligence

Role Overview

We are looking for a Full Stack Engineer to own both the application layer and the user-facing interfaces of the platform. You will build the backend services that power core workflows — case management, exception handling, and feedback loops — as well as the interfaces through which the compliance and assurance teams interact with the system. You are comfortable owning both layers and moving fluidly between them.

Key Responsibilities

Application Backend

•  Design and build the core application services powering the platform — exception case management, workflow state tracking, audit logging, and user action recording.

•  Build the feedback mechanism that captures validator decisions and overrides and routes them back to the AI layer for model improvement

•  Own the data models for all application-layer entities — exception cases, workflow states, user actions, and decision history.

•  Build and maintain the API endpoints consumed by the frontend, with clear contracts, versioning, and error handling.

•  Implement role-based access control across the application — different user types within the compliance and assurance teams require different levels of access and visibility.

•  Build notification and alerting services — surfacing deadline-sensitive items and pending exceptions to the right users at the right time.

•  Ensure all application services maintain a complete audit trail, given the compliance context in which the platform operates.

Frontend & User Interfaces

•  Build the workflow interfaces used by the compliance and assurance teams — exception queues, validation screens, dashboards, and status views.

•  Surface AI outputs — confidence scores, historical context, and recommendations — in a way that is clear and actionable for non-technical users.

• Conduct working sessions with the compliance team to validate usability and incorporate feedback before deployment.

•  Maintain a consistent, functional UI across all modules of the platform.

Quality & Production Readiness

•  Write unit and integration tests for both frontend and backend components.

•  Ensure the application layer is production-ready — monitored, observable, and stable under expected load.

Required Qualifications

Education

•  B.E. / B.Tech / M.Tech in Computer Science, Information Technology, or a related field.

Experience

•   4+ years of full stack engineering experience with ownership of both frontend and backend layers in production.

• Experience building internal enterprise workflow tools or operational dashboards.

• Comfortable being the sole owner of the full stack without dedicated frontend or backend partners.

Technical Skills

•  Frontend: React or Vue.js;

•  Backend: Python or Node.js for API and service development.

•  Databases: PostgreSQL or equivalent relational database; basic familiarity with NoSQL.

•  API Design: RESTful API design and consumption; experience working against well-defined API contracts.

•  Testing: Unit and integration testing frameworks for both frontend and backend.

•  Containerisation: Docker; basic Kubernetes familiarity.

•   Version Control: Git-based workflows, code review practices.

Preferred Qualifications

•  Experience building applications that consume or display ML or AI model outputs.

•  Prior work on compliance, operations, or workflow management tools in an enterprise environment.

•  Familiarity with data visualisation libraries for building dashboards and exception reports.

•  Exposure to accessibility and usability best practices for internal tooling.

Location - Bangalore

We are looking for a Staff Full stack Engineer with strong frontend expertise to help shape, scale, and continuously evolve our platform. In this role, you will take ownership of application architecture across the stack, drive frontend excellence, and influence engineering standards across multiple teams and products.

What You’ll Do -

• Define and evolve application architecture across frontend and backend systems, ensuring scalability, performance, and maintainability.

• Design and build modern, data-rich web applications to visualize and interact with complex industrial data.

• Take end-to-end ownership of critical features across the stack from discovery to release and observability.

• Drive frontend architecture, component design, performance optimization, and technical quality across teams.

• Contribute to backend services, APIs, and data integration layers where needed.

• Establish and promote best practices in design systems, code quality, testing, and CI/CD.

• Partner with Product, Design, Backend, and Platform teams to align on architecture and delivery.

• Mentor engineers and guide teams in adopting scalable patterns and modern engineering practices.

What You’ll Bring (Must-Have) -

• 10+ years of experience in software development with strong expertise in TypeScript and JavaScript.

• Deep hands-on expertise with a modern frontend framework (Angular preferred).

• Proven experience defining and scaling frontend architecture for complex, enterprise-grade applications.

• Strong experience with Node.js and backend service development (APIs, microservices).

• Solid understanding of API design, frontend-backend integration, and state management.

• Strong experience in Object-Oriented Design, system design, and service-oriented architecture.

• Hands-on experience with testing frameworks, observability, and CI/CD practices.

• Demonstrated ability to influence technical direction and drive engineering standards across teams.

Nice to Have -

• Experience with MEAN stack (Node.js, Express, MongoDB, Angular).

• Experience with microservices, event-driven architecture, or distributed systems.

• Experience with design systems, accessibility, and frontend performance optimization.

• Experience with 3D visualization libraries (e.g., WebGL, Three.js, Babylon.js).

• Experience with Docker, Kubernetes, and cloud platforms (Azure/AWS).

• Experience architecting or developing mobile applications (e.g., Flutter or similar frameworks).

• Exposure to data platforms, analytics systems, or GenAI/LLM-based applications.

Company Overview:

Euphoric Thought Technologies is a technology-driven firm focused on building scalable software solutions and high-performance digital infrastructure. Operating at the intersection of cloud engineering and enterprise software, the company empowers businesses to streamline their operations through robust, automated, and secure platforms. With a culture rooted in technical excellence and collaborative problem-solving, Euphoric Thought Technologies supports a diverse range of clients in optimizing their digital footprint and accelerating their time-to-market.

Role Overview:

As a Senior DevOps Engineer, you will serve as a cornerstone of our engineering team in Bangalore, taking ownership of the end-to-end reliability and scalability of our cloud environments. You will work closely with software developers, product managers, and security teams to bridge the gap between code development and production deployment. Your daily efforts will directly influence the stability of our platforms, ensuring that our infrastructure is not only resilient but also highly automated to support rapid business growth and seamless user experiences.

Key Responsibilities:

- Architect and maintain highly available CI/CD pipelines to accelerate software delivery cycles and ensure consistent deployment quality across environments.

- Manage and scale containerized applications using Kubernetes and Docker to optimize resource utilization and application performance.

- Implement Infrastructure as Code (IaC) using Terraform to ensure environment consistency and enable rapid provisioning of cloud resources.

- Automate routine operational tasks and configuration management using Ansible and Python scripts to reduce manual overhead and human error.

- Monitor cloud infrastructure health and security posture within AWS to proactively identify and resolve bottlenecks or vulnerabilities.

- Collaborate with cross-functional teams to define and implement best practices for cloud-native development, ensuring high standards of security and operational excellence.

Required Skillset:

- Demonstrated expertise in managing large-scale cloud computing environments on AWS, with a deep understanding of cloud architecture and cost-optimization strategies.

- Proven ability to design and maintain complex CI/CD workflows using Jenkins, ensuring seamless integration and delivery for high-traffic applications.

- Strong proficiency in scripting and automation using Python, with a focus on building reusable tools that enhance team productivity.

- Exceptional problem-solving skills and the ability to troubleshoot complex production issues in a high-pressure, fast-paced environment.

- Strong interpersonal skills with the ability to communicate technical concepts clearly to both engineering and non-technical stakeholders.

- Ability to work effectively in a hybrid work environment, demonstrating self-discipline and a proactive approach to team collaboration.

- A minimum of 7 - 8 years of professional experience in DevOps and infrastructure engineering roles.

Key Responsibilities  

• Design, build, and optimize scalable data pipelines for AI/ML applications.
• Develop, train, evaluate, and deploy Machine Learning and Deep Learning models.
• Build production-ready LLM applications using Retrieval-Augmented Generation (RAG), prompt engineering, and vector databases.
• Fine-tune open-source and foundation models using domain-specific datasets.
• Develop and maintain end-to-end MLOps pipelines for model deployment, monitoring, and lifecycle management.
• Perform data preprocessing, feature engineering, exploratory data analysis (EDA), and model evaluation.
• Develop APIs and AI services for production deployment.
• Collaborate with cross-functional teams to deliver scalable AI-driven solutions.
• Monitor model performance, troubleshoot production issues, and maintain technical documentation.

Required Skills  

Mandatory  

• 1–3 years of experience in Data Science, Data Engineering, or AI/ML development.
• Strong programming skills in Python and SQL.
• Hands-on experience with Machine Learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Experience building LLM-powered applications using RAG, Prompt Engineering, and Embeddings.
• Hands-on experience with LangChain, LlamaIndex, CrewAI, or n8n for LLM orchestration and AI workflow automation.
• Experience in LLM fine-tuning and working with Hugging Face models.
• Knowledge of MLOps concepts including model deployment, monitoring, versioning, and CI/CD.
• Experience with Git, REST APIs, Linux environments, and data processing libraries.

Preferred  

• Experience with vector databases such as Pinecone, Chroma, Milvus, or Weaviate.
• Familiarity with Docker, Kubernetes, and MLflow.
• Exposure to Apache Spark or Airflow for data engineering workflows.
• Experience with cloud platforms (AWS, Azure, or GCP).

Primary Technology Stack  

• Languages & Data Processing: Python, SQL, Pandas, NumPy, Apache Spark
• AI & Machine Learning: PyTorch, TensorFlow, Scikit-learn
• Application Frameworks: LangChain, LlamaIndex, CrewAI, n8n
• Core Methodologies: Retrieval-Augmented Generation (RAG), Model Fine-Tuning, Prompt Engineering, Embeddings
• Models & Infrastructure: OpenAI APIs, Hugging Face Ecosystem, Embedding Models
• Vector Databases: Pinecone, Chroma, Milvus, Weaviate
• Databases: PostgreSQL, MongoDB
• MLOps & DevOps: Docker, Kubernetes, MLflow, CI/CD, Git
• Cloud Platforms: AWS, Azure, GCP

Experience: 1–3 Years

Domain: Data Science | Data Engineering | Machine Learning | Generative AI | MLOps

OpenShift Cloud Platform (OCP)

Location: Hyderabad

Exp: 8+ years

Budget- 25 LPA

Work Timings: 2 shifts (Morning shift & Afternoon Shift)

Primary Skills: OpenShift GKE/AKS, Kubernetes, GitOps

Secondary/Desired Skills (preferred): RHCE/EX280/CKA certification

About the Role

We are looking for a hands-on Principal Engineer who owns enterprise integration architecture from end to end — from the first whiteboard sketch through production delivery and ongoing governance. This is not a management role, and it is not a specialist role. We are not looking for an Angular architect, a Java architect with cloud exposure. We need a true Full Stack Integration Architect who has designed, built, and governed how large-scale enterprise systems connect, communicate, and operate reliably at scale.

You will be expected to go deep on integration design, backend engineering, data architecture, cloud infrastructure, and front-end development — and to defend every decision under rigorous technical scrutiny. If your experience is anchored in one layer or one language, this is not the right opportunity.

What You Will Own

• End-to-end integration architecture across cloud platforms (AWS, Azure, GCP), on-premises systems, and third-party services — designed, delivered, and governed by you
• Definition and enforcement of integration patterns across the enterprise: API-first, microservices, event-driven, and real-time and batch processing
• Seamless data flow, application interoperability, and fault tolerance across mission-critical platforms
• Quality and testing strategy across integrated solutions — automation frameworks, release readiness, validation, and quality governance
• Full-stack engineering across all layers: front-end, backend services, data, and cloud infrastructure
• GenAI and LLM integration into production-grade digital platforms
• Technical mentorship across engineering levels and cross-team architectural influence
• Clear communication of complex architectural decisions to both engineering teams and business stakeholders

What You Must Have

• 15+ years of hands-on software engineering experience with a strong track record in enterprise-scale distributed systems
• Proven end-to-end integration architecture experience — you have designed, governed, and delivered enterprise integrations across complex, heterogeneous environments; not just implemented someone else's design
• Genuine full-stack depth across all layers:
• Front-end: Angular, TypeScript
• Backend: Java, Python, Go, or Node.js — at least one deeply, others functionally
• Data: SQL, NoSQL, caching (Redis), event streaming platforms
• Strong database knowledge in both theory and practice — relational, NoSQL, distributed data, and streaming
• Cloud-native hands-on experience across at least one of AWS, Azure, or GCP — Kubernetes, Docker, and Infrastructure as Code (Terraform) are expected
• CI/CD pipeline experience tied to enterprise release cycles and quality governance
• The ability to clearly articulate the technical design, tradeoffs, and problem-solving approach behind your own recent work — this will be probed in depth during interviews

Integration & API Technologies

You should have hands-on experience across several of the following:

REST · GraphQL (Apollo Federation or similar) · gRPC · Kafka or equivalent event streaming · Microservices architecture · Event-driven architecture · B2B and internal system integrations · Real-time and batch integration patterns

What Will Strengthen Your Profile

• GCP-native database experience: BigQuery, Spanner, Bigtable
• Production-grade GenAI or LLM integration — not just prototypes or proof of concepts
• Experience with AI development tools: Cursor, GitHub Copilot, Vertex AI Studio, Claude Code
• Healthcare or regulated-industry platform experience
• MLOps or AI lifecycle management
• Identity, security, and privacy architecture at enterprise scale
• Observability tooling: Datadog, Prometheus, Grafana

Do Not Apply If

• You are primarily an Angular Architect, a Java architect, or strong in one layer only — this role demands genuine end-to-end depth across the full stack
• You cannot walk through the architecture, implementation decisions, and tradeoffs of your own recent projects with technical precision
• You have not designed or governed integrations at enterprise scale across distributed, heterogeneous systems
• Your backend, database, or integration experience is surface-level, theoretical, or limited to a single technology

Why This Role

This role carries real architectural authority at a large enterprise. You will set integration direction across business-critical platforms, influence engineering standards, and solve problems that matter at significant scale. The technical bar is deliberately high — because the impact is real.

We are looking for a AI System Engineer who is eager to build a career in AI systems, automation, backend workflows, cloud infrastructure, and intelligent product operations. Apply in https://gosuperedtech.com/career/ai-system-engineer

Core Responsibilities:

• Design & Development: Architect and implement scalable backend services and APIs using Python or Golang, ensuring high performance, resilience, and extensibility.
• System Ownership: Take end-to-end ownership of critical modules, from design and development to deployment and support.
• Technical Leadership: Conduct design and code reviews, enforce best practices, and mentor junior engineers to raise the team’s technical bar.
• Collaboration: Work closely with product managers, architects, and other engineers to translate business requirements into technical solutions.
• Performance & Reliability: Troubleshoot complex issues in production systems, identify root causes, and design sustainable long-term solutions.
• Innovation: Evaluate new technologies, contribute to proof-of-concepts, and recommend tools that can improve developer productivity.
• Process Improvement: Drive initiatives to improve coding standards, CI/CD pipelines, and automated testing practices.
• Knowledge Sharing: Document designs, create technical guides, and share insights with the broader engineering team.

Experience and Expertise:

• 4–7 years of backend development experience with Python or Golang.
• Strong expertise in designing, developing, and scaling microservices and distributed systems.
• Solid understanding of concurrency, multi-threading, and performance optimization.
• Proficiency with databases (SQL/NoSQL), caching systems (Redis, Memcached), and messaging systems (Kafka, RabbitMQ, etc.).
• Hands-on experience with Linux development, Docker, and Kubernetes.
• Familiarity with cloud platforms (AWS/GCP/Azure) and related services.
• Strong debugging, profiling, and optimization skills for production-grade systems.
• Experience with AI-powered development tools is a strong plus; familiarity with concepts like 'agentic coding' for workflow automation or 'context engineering' for leveraging LLMs in system design is highly desirable.

Skills:

• Strong problem-solving ability, with experience handling complex technical challenges.
• Ability to lead technical initiatives and mentor junior engineers.
• Excellent communication skills to collaborate with cross-functional teams and articulate trade-offs.
• Self-motivated, proactive, and able to operate independently while aligning with team goals.
• Passionate about engineering culture, quality, and developer productivity.

Core Responsibilities:

• Design, develop, and maintain backend services and APIs using Python or Golang.
• Write high-quality, testable, and maintainable code with a focus on performance and scalability.
• Implement automated tests and contribute to CI/CD pipelines.
• Collaborate with product, QA, and DevOps teams for end-to-end feature delivery.
• Troubleshoot production issues and provide timely resolutions.
• Participate in design and architecture discussions to improve system efficiency.
• Contribute to improving development processes, coding standards, and best practices.

Experience and Expertise:

• 2–4 years of experience in backend development with Python or Golang.
• Solid understanding of RESTful APIs, microservices, and distributed systems.
• Strong knowledge of data structures, algorithms, and OOPS principles.
• Hands-on experience with relational and/or NoSQL databases.
• Familiarity with Linux development, Docker, and basic cloud concepts (AWS/GCP/Azure).
• Proficiency with Git and version control workflows.
• Familiarity with AI-powered development tools or exposure to projects involving large language models (LLMs) is a plus.

Skills:

• Strong analytical and debugging skills with the ability to solve complex problems.
• Good communication and collaboration skills across teams.
• Ability to work independently with minimal supervision while being a strong team player.
• Growth mindset – eagerness to learn new technologies and improve continuously.

Core Responsibilities:

• Design, develop, and maintain backend services and APIs using Python or Golang.
• Write high-quality, testable, and maintainable code with a focus on performance and scalability.
• Implement automated tests and contribute to CI/CD pipelines.
• Collaborate with product, QA, and DevOps teams for end-to-end feature delivery.
• Troubleshoot production issues and provide timely resolutions.
• Participate in design and architecture discussions to improve system efficiency.
• Contribute to improving development processes, coding standards, and best practices.

Experience and Expertise:

• 1-2 years of experience in backend development with Python or Golang.
• Solid understanding of RESTful APIs, microservices, and distributed systems.
• Strong knowledge of data structures, algorithms, and OOPS principles.
• Hands-on experience with relational and/or NoSQL databases.
• Familiarity with Linux development, Docker, and basic cloud concepts (AWS/GCP/Azure).
• Proficiency with Git and version control workflows.
• Familiarity with AI-powered development tools or exposure to projects involving large language models (LLMs) is a plus.

Skills:

• Strong analytical and debugging skills with the ability to solve complex problems.
• Good communication and collaboration skills across teams.
• Ability to work independently with minimal supervision while being a strong team player.
• Growth mindset – eagerness to learn new technologies and improve continuously.

Company Description

The client is currently the industry's only Manufacturing Operating System, designed to deliver unparalleled automation, precision, and scalability to factories. By integrating advanced technologies, they empower manufacturers to optimize production processes and achieve greater control over operations. Their innovative solutions drive smarter, more efficient factories. Join us to contribute to the future of intelligent manufacturing.

Role Description

We are seeking a Kubernetes Engineer for a full-time, on-site role based in Hyderabad, IN. In this role, you will design, implement, and maintain Kubernetes-based infrastructure to support production systems. This is a hands-on platform engineering role for someone who has built and operated production-grade Kubernetes environments across cloud, on-prem, or hybrid infrastructure. You’ll own the platform foundation for secure, reliable, and governed AI workloads — with a focus on automation, reliability, security, developer enablement, and enterprise-scale operations.

What you’ll do

You will lead the design, deployment, and lifecycle management of highly available Kubernetes platforms across hybrid environments, ensuring resilience, scalability, and operational consistency.

You’ll establish secure multi-tenant platform standards, build GitOps-driven operations, define deployment and observability patterns, and embed security controls across identity, secrets, policy enforcement, and workload protection.

You’ll also work closely with application, security, infrastructure, and platform teams to standardize deployment patterns, improve reliability, and support adoption of the enterprise AI platform.

Key responsibilities

• Design, deploy, and operate highly available Kubernetes platforms across cloud and on-prem environments
• Build automated, GitOps-driven platform operations for provisioning, upgrades, patching, scaling, and decommissioning
• Establish secure multi-tenant standards for governance, workload isolation, and resource efficiency
• Define platform standards for deployment, observability, service operations, and production readiness
• Implement Kubernetes security controls including RBAC, network policies, secrets management, policy enforcement, and cluster hardening
• Troubleshoot complex issues across Linux, networking, storage, runtime, and Kubernetes layers
• Improve platform reliability, incident response, operational readiness, and service objectives
• Drive continuous improvement in automation, performance, and cost efficiency

Must-have experience

• Proven experience building and operating production Kubernetes platforms at scale
• Strong hands-on Kubernetes administration, operations, and lifecycle management experience
• Deep understanding of Linux, cluster networking, storage architecture, and infrastructure troubleshooting
• Experience with Terraform, Helm, and infrastructure automation in production environments
• Hands-on GitOps experience with Argo CD, Flux, or similar tools
• Strong Kubernetes security experience, including RBAC, network policies, secrets/key management, admission control, policy enforcement, and production hardening
• Experience with at least one major cloud platform, preferably AWS or Azure
• Experience with EKS, AKS, GKE, OpenShift, Rancher, or similar enterprise Kubernetes platforms
• Familiarity with service mesh, OpenTelemetry, observability frameworks, and container security tooling
• Experience supporting enterprise AI platforms or AI/ML infrastructure
• Certifications such as CKA, CKAD, or CKS are preferred

Initial focus

In the first phase, you’ll help establish the Kubernetes platform foundation across cloud and on-prem environments, implement baseline GitOps, security, access, and operational controls, and define the operating model required to scale governed enterprise AI workloads.

This is a high-impact role for someone who wants to build the platform layer behind enterprise AI adoption — not just maintain clusters.

Job Title : DevOps Engineer / Site Reliability Engineer (SRE)

Experience : 4+ Years

Location : Gurugram, Sector 48, Haryana (On-site)

Employment Type : Full-Time

Working Days : Monday to Saturday (1st & 3rd Saturday Off)

About the Role :

We are looking for a hands-on DevOps Engineer / Site Reliability Engineer (SRE) with strong experience in Linux, AWS, Kubernetes, Docker, CI/CD, Infrastructure as Code, and production application deployments.

The ideal candidate should have real-world production experience, excellent troubleshooting skills, and the ability to manage both infrastructure and application-level issues.

Mandatory Skills :

Linux, AWS, Docker, Kubernetes, Terraform, Ansible, Jenkins, GitHub Actions, GitLab CI/CD, CI/CD, Infrastructure as Code (IaC), Python, Bash, Git, Grafana, Prometheus, ELK, CloudWatch, New Relic, SRE (SLI/SLO/SLA), Networking (DNS, HTTP/HTTPS, TCP/IP, Load Balancer), Production Application Deployment & Troubleshooting

Key Responsibilities :

• Manage and maintain AWS cloud infrastructure.
• Build and optimize CI/CD pipelines using Jenkins, GitHub Actions, or GitLab CI.
• Deploy, monitor, and troubleshoot applications across production environments.
• Automate infrastructure using Terraform and Ansible.
• Manage Docker containers and Kubernetes clusters.
• Monitor systems using Grafana, Prometheus, ELK, CloudWatch, and New Relic.
• Perform Linux server administration and troubleshooting.
• Handle production incidents, Root Cause Analysis (RCA), and improve system reliability.
• Collaborate with development teams to support application releases and automation.

Required Qualifications :

• Bachelor's degree in Computer Science or related field.
• 4+ years of hands-on experience in DevOps / SRE.
• Strong Linux administration and production troubleshooting skills.
• Experience with AWS and modern DevOps toolchains.
• Hands-on experience with application deployment and production support.

What We're Looking For :

• Strong practical Linux and cloud knowledge.
• Real production experience with application deployments.
• Ability to troubleshoot both infrastructure and application issues.
• Experience handling live production incidents.
• Excellent communication and problem-solving skills.
• Candidates should be comfortable with scenario-based technical discussions and demonstrate genuine hands-on expertise.

Interview Process :

1. HR Screening
2. Technical Round
3. Client Technical Round
4. Final Discussion

Note : The interview will focus on practical hands-on experience in Linux, AWS, Kubernetes, Docker, CI/CD, Infrastructure as Code, application deployment, production troubleshooting, and real-world DevOps scenarios.

Job Title : Senior Software Development Engineer in Test (Sr. SDET)

Experience : 5 to 10 Years

Location : Bengaluru (5 Days Work From Office)

Working Days : Monday to Friday (5 Days a Week)

Notice Period : Immediate to 15 Days

Interview Process : 2 Technical Client Rounds

Role Overview :

We are looking for a Senior SDET with strong expertise in Backend/API Automation Testing for Microservices-based applications.

The ideal candidate should have experience building scalable automation frameworks, validating distributed systems, and integrating automation into CI/CD pipelines.

Mandatory Skills :

Java, Backend Automation Testing, API Automation, REST Assured, Microservices, TestNG, JUnit, Maven / Gradle, CI/CD, SQL, Kafka / RabbitMQ / SQS, Docker, Kubernetes, REST APIs, Distributed Systems, Grafana / Prometheus / Kibana / Splunk.

Preferred Skills :

AWS / GCP / Azure, MongoDB, Redis, Cassandra, WireMock, Pact, JMeter, Gatling, k6, Python, Shell Scripting.

Key Responsibilities :

• Design and maintain API/backend automation frameworks.
• Perform functional, integration, regression, and end-to-end testing.
• Automate testing for microservices and event-driven architectures.
• Integrate automation into CI/CD pipelines.
• Validate asynchronous workflows using messaging systems.
• Collaborate with Development and DevOps teams to ensure high-quality releases.
• Mentor QA engineers and improve automation best practices.

Required Skills & Qualifications :

• 5+ years of experience in Software Testing with a strong focus on Backend / API Automation.
• Hands-on experience testing Microservices-based applications.
• Strong expertise in REST API testing using REST Assured, HTTP Client, Postman, or similar tools.
• Excellent programming skills in Java with hands-on experience developing scalable automation frameworks.
• Strong experience with TestNG, JUnit, Maven/Gradle, and CI/CD integration.
• Hands-on experience validating asynchronous workflows using Kafka, RabbitMQ, AWS SQS, or similar messaging platforms.
• Strong knowledge of SQL and relational databases such as MySQL, PostgreSQL, or Oracle, including complex queries and joins.
• Experience working with Docker, Kubernetes, and containerized applications.
• Experience validating applications deployed in Ephemeral or dynamic test environments.
• Good understanding of distributed systems and backend application architecture.
• Experience with observability and monitoring tools such as Grafana, Prometheus, Kibana, or Splunk.
• Strong understanding of software design principles, automation architecture, and test automation design patterns.

Preferred Skills :

• Experience with NoSQL databases such as MongoDB, Redis, or Cassandra.
• Knowledge of contract testing, service virtualization, and mocking tools such as WireMock or Pact.
• Familiarity with cloud platforms including AWS, GCP, or Azure.
• Experience with performance and resilience testing tools such as JMeter, Gatling, or k6.
• Working knowledge of Python or Shell scripting.

At Quantiphi, you will be a key leader within our Platform Engineering team, responsible for defining and driving the architectural vision for cloud-based solutions. You will lead the design and implementation of robust pipeline infrastructure, orchestrating integration flows among upstream RPA processes, the AR tool backend, and downstream systems. You will work closely with stakeholders, cross-functional teams, and clients to ensure that solutions are scalable, secure, and aligned with business objectives.

Must have skills:

• Strong expertise in designing and architecting scalable, secure, and highly available AWS platforms using services such as API Gateway, Lambda, EC2, ECS/EKS, VPC, IAM, S3, CloudWatch, CloudTrail, ECR, SNS, SQS, EventBridge, Systems Manager (SSM), KMS, and Secrets Manager.
• Proven technical experience in designing and overseeing end-to-end platform integration architectures, orchestrating data and process flows between upstream systems, third-party applications (e.g., ERP systems such as BaaN, SAP, Oracle), internal services, and downstream consumer applications.
• Strong expertise in API architecture, including RESTful APIs, API Gateway, authentication/authorization (OAuth, JWT, API Keys), API lifecycle management, integration patterns, and secure third-party connectivity.
• Extensive experience designing AWS IAM security governance, including IAM Roles, Policies, Cross-Account Access, Permission Boundaries, Service Control Policies (SCPs), and enterprise identity and access management strategies.
• Strong experience designing AWS infrastructure using Infrastructure as Code (Terraform, AWS CloudFormation, or AWS CDK), with reusable platform modules, reference architectures, and standardized deployment frameworks.
• Expertise in designing and implementing enterprise CI/CD and DevSecOps pipelines using GitHub Actions, Jenkins, GitLab CI/CD, or AWS CodePipeline, integrating automated testing, security scanning, and deployment governance.
• Strong knowledge of enterprise networking, including VPC architecture, Transit Gateway, Direct Connect, VPN, Load Balancers, Route 53, DNS, PrivateLink, and hybrid connectivity.
• Experience implementing enterprise monitoring and observability using Amazon CloudWatch, CloudTrail, dashboards, centralized logging, and alerting frameworks to ensure platform reliability and operational excellence.
• Proficiency in automation using Python, Bash, PowerShell, and AWS SDK (Boto3) to streamline platform operations and deployments.
• Excellent technical solution design, stakeholder management, technical leadership, documentation, and mentoring skills, with the ability to drive architecture reviews and establish engineering best practices.

Good to have skills:

• Experience designing enterprise integration platforms using event-driven and microservices architectures.
• Knowledge of AWS Organizations, Control Tower, Landing Zone, governance frameworks, and FinOps best practices.
• Experience with container platforms such as Docker, Kubernetes, Amazon ECS/EKS, and service mesh technologies.
• Familiarity with enterprise observability platforms such as Grafana, Prometheus, Datadog, Splunk, or OpenSearch.
• Experience with enterprise messaging and integration technologies such as Kafka, Amazon MSK, MQ, or EventBridge.
• Knowledge of disaster recovery, business continuity, and high-availability architecture.
• AWS Certifications such as Solutions Architect – Professional, DevOps Engineer – Professional, Security Specialty, or Advanced Networking – Specialty.
• Experience working in Agile, DevOps, and Platform Engineering environments.

Greetings from NAM Info Pvt Ltd,

Job Title: GCP DevOps Engineer

Location: Bangalore

Experience: 6+ Years

Employment Type: Full Time with NAM Info Pvt Ltd (Payroll)

Job Description:

We are looking for a GCP DevOps Engineer with hands-on experience in Google Cloud Platform and DevOps tools. The ideal candidate should have experience in CI/CD, cloud infrastructure, automation, and container technologies.

Required Skills:

• Experience with Google Cloud Platform (GCP)
• Knowledge of CI/CD tools such as Jenkins or GitLab CI
• Experience with Docker and Kubernetes (GKE preferred)
• Infrastructure as Code using Terraform
• Good knowledge of Linux and Shell scripting
• Experience with Git version control
• Monitoring tools such as Prometheus or Grafana is a plus
• Good troubleshooting and communication skills

Job Title : Generalist Fullstack Engineer (Java / Node.js / React / AI-Driven Engineering)

Experience : 5 to 10 Years

Location : Bengaluru (Koramangala) – Hybrid (3 Days WFO)

Employment Model : C2H

Joining : Immediate to 20 Days Notice Only

Open Positions : 4

About the Role :

We are hiring a hands-on Generalist Fullstack Engineer for a high-impact engineering team. This is a 90% coding role focused on building scalable products across frontend, backend, cloud, and modern AI-enabled engineering practices.

Mandatory Skills :

Full Stack Development (Frontend + Backend), JavaScript / Java / Node.js / Python / Go, ReactJS or modern UI frameworks, Microservices, AWS, Docker, Kubernetes, SQL/NoSQL, CI/CD, Terraform (IaC), Automated Testing (TDD), AI-enabled software delivery, and strong hands-on coding experience.

Key Requirements :

• 5 to 10 years of software development experience.
• Strong expertise in JavaScript, Java, Node.js, Python, or Go.
• Hands-on experience with ReactJS / modern frontend frameworks.
• Strong backend depth with microservices & event-driven architecture.
• Experience with AWS, Docker, Kubernetes.
• Exposure to AI tools/frameworks in software delivery.
• Strong understanding of SQL/NoSQL databases & data modelling.
• Experience with CI/CD, automated testing, Terraform (IaC).
• Working knowledge of TDD, pair programming, continuous integration, security best practices.

Roles & Responsibilities :

• Develop and own production-grade full-stack applications.
• Build AI-first engineering workflows to improve delivery efficiency.
• Drive architecture decisions and engineering best practices.
• Deliver scalable cloud-native solutions.
• Collaborate across product, QA, design, and architecture teams.
• Improve system reliability through monitoring, automation, and testing.

Ideal Candidate :

✔ Strong end-to-end ownership (Frontend + Backend).

✔ Deep hands-on coding mindset (not people-management focused).

✔ Strong AWS + SQL exposure.

✔ Experience building and managing UI state and frontend components.

✔ Stable career progression (avoid frequent job changes).

Interview Process :

1. Technical Round – GT (Assemble)
2. Technical Round – Client
3. Technical Round – Client
4. HR Discussion & Offer

Great engineers aren’t built by watching.

They’re built by solving real problems.

At AbleCredit, interns don’t work on toy projects or isolated assignments. From your first few weeks, you’ll contribute to production systems used by enterprise customers, collaborate with experienced engineers, and learn what it takes to build reliable software at scale.

If you’re curious, enjoy building things, and want to accelerate your engineering career, we’d love to work with you.

What You’ll Build?

As an Engineering Intern, you’ll work alongside our engineering team to build and improve products used by real customers.

Depending on your interests and the team’s priorities, you’ll:

● Build backend services, APIs, and platform features.

● Develop user-facing features across our web applications.

● Work with databases, cloud services, and third-party integrations.

● Debug production issues and improve system reliability.

● Participate in code reviews and technical design discussions.

● Write clean, maintainable, and well-tested code.

● Learn how modern software is designed, built, deployed, and monitored.

Your work won’t be a demo project—it will ship to production.

What We’re Looking For?

We’re looking for people who enjoy solving problems more than collecting technologies on their résumé.

You’ll likely succeed if you:

● Are pursuing or have recently completed a Bachelor’s or Master’s degree in Computer Science or a related field.

● Have strong programming fundamentals and problem-solving skills.

● Understand data structures, algorithms, and object-oriented programming.

● Are comfortable with at least one programming language such as JavaScript, TypeScript, Python, Java, or Go.

● Understand the basics of databases, REST APIs, and Git.

● Learn quickly and enjoy exploring unfamiliar technologies.

● Communicate clearly and work well in a collaborative environment.

Bonus Points:

Experience with any of these is helpful but not required:

● Node.js, FastAPI, Spring Boot, or Django

● React and modern frontend development

● SQL and NoSQL databases

● AWS, GCP, or Azure

● Docker, Kubernetes, or CI/CD

● AI, LLMs, or workflow automation

Don’t worry if you haven’t worked with everything on this list. We care more about your ability to learn than your current toolkit.

What You’ll Learn?

During your internship, you’ll gain practical experience with:

● Building production software

● Backend engineering and API design

● Modern web application development

● Cloud infrastructure

● Distributed systems and asynchronous workflows

● Software testing and debugging

● Git-based development workflows

● Code reviews and engineering collaboration

You’ll also learn how engineering teams operate inside a fast-moving startup—from

turning ideas into products to shipping features used by customers.

Why Join AbleCredit?

You’ll join a small, high-ownership engineering team where your contributions matter from day one.

You’ll have the opportunity to:

● Build software used by real enterprise customers.

● Receive mentorship from experienced engineers.

● Learn modern engineering practices and tools.

● Work across the backend, frontend, and cloud stack.

● Take ownership of meaningful features instead of isolated tasks.

● Convert your internship into a full-time engineering role based on your

performance and available opportunities.

We Think You’ll Enjoy This Role If...

● You build side projects because you enjoy learning.

● You like understanding how systems work—not just using them.

● You’re excited to write code that reaches production.

● You ask questions, experiment, and learn quickly.

● You want an internship where you’ll build, not just observe.

About Blitzy

Blitzy is a Cambridge, MA based AI software development platform on a mission to revolutionize the software development life cycle by autonomously building custom software to unlock the next industrial revolution. We're transforming how enterprises build software, turning enterprise requirements into production-ready code with an agentic software development platform that can autonomously execute 80% of the quantum of software development work. We're backed by multiple tier 1 investors, and have proven success as founders of previous start-ups.

Location: Pune, India (In-Person) - Must be able to also support USA business hours

The Role

The role is to support our clients and ensure a stable environment across the full lifecycle: installation, ongoing upgrades, and day-to-day operation. The L2 Support Engineer works alongside L1 to triage and resolve issues, and escalates unresolved defects to engineering. It operates across Kubernetes, Docker, and the major cloud providers.

What Success Looks Like

• Customers' issues are resolved faster and escalated cleaner.
• Recurring problems turn into runbooks, dashboards, and alerts, not repeat tickets.
• Engineering trusts your escalations because they come with proof, not guesses.
• Customers trust your communication because it's clear, honest, and on time.

Areas of Ownership

• Deploy and install the platform into customer environments, and troubleshoot installation issues.
• Support ongoing upgrades and day-to-day operation, keeping customer environments stable.
• Work alongside L1 to triage and resolve customer-reported issues, driving them to resolution or escalation.
• Diagnose failures across the stack: compute, networking, storage, and the services running on it.
• Reproduce issues safely against live (often multi-tenant) environments using read-only diagnostics first.
• Build and maintain dashboards, monitors, and runbooks so recurring issues get faster to fix: or stop recurring.
• Write up clear, evidence-backed escalations and post-incident notes.
• Communicate status and resolution to customers clearly and on time.

Required Experience

• Distributed-systems debugging. Reason about a request crossing multiple services, queues, and network hops, and isolate which hop failed. You debug by forming a hypothesis and confirming it with evidence (logs, pod state, queue depth, DB rows), not by guessing.
• Kubernetes & Docker.
• Major cloud providers: GCP, AWS, and Azure. Hands-on with at least one deeply and able to work across the others: managed Kubernetes (GKE/AKS), cloud logging, IAM/auth basics, and cloud disk/storage behavior.
• Strong monitoring & observability practice. Fluent with an APM/observability stack (Datadog or equivalent): log queries, correlating across services by request/trace IDs, reading traces, and building dashboards and alerts. You reach for the data before theorizing.

Additional Skills & Experience

• Python and Redis literacy.
• Basic message queueing. Command transport runs over a message queue (Redis/rq). Comfort inspecting queue depth, backlogs, and stuck/failed jobs; concepts transfer from any broker.
• Networking & WebSockets. Many of our hardest issues are connection problems: WebSocket/Socket.IO drops, NAT/idle/LB timeouts, half-open sockets, DNS-vs-routing, TLS. Tell a transport fault from an application fault.
• SQL / PostgreSQL. Query operational tables to confirm what the system recorded.
• Source-control platforms. GitHub (incl. GitHub Enterprise Server), Azure DevOps, and/or GitLab, clone/push/pull, access tokens, app credentials, and their failure modes.
• CI/CD, Helm & deploy integrity. Many "sudden regressions" are a bad or partial deploy: check what version is actually running before chasing architecture theories. Helm and container deploy pipelines expected. ArgoCD is a plus.
• Secrets management. Comfort handling secrets, credentials, and certificates safely, ideally with Vault (strongly preferred).
• Linux and Windows. Workloads run on both; comfort triaging on each OS (process inspection, filesystem, basic networking).
• Methodical, evidence-first temperament. Hold several candidate causes at once, run the cheapest disconfirming check first, and never claim a root cause or fix you haven't proven.
• Multi-tenant safety mindset. Environments are shared and customer-owned: default to read-only diagnostics and understand blast radius before changing anything.
• Incident management & ticketing workflows: Jira or similar (a plus).
• Prior customer-facing support or SRE/on-call experience (a plus).

Hours & On-Call: please read

This is a customer support role, and the hours can be unconventional. Customers operate primarily in US time zones, so coverage is anchored to US business hours (roughly ET–PT). If you're based outside the US, expect your working day to shift accordingly.

Incidents don't keep office hours. Expect a rotating on-call schedule and occasional evening, early-morning, or weekend escalations outside a standard 9–5. We structure for it: rotations are shared fairly, on-call is compensated/time-off-in-lieu per policy, and we protect recovery time after heavy incidents.

If you're not comfortable with US-aligned hours and periodic off-hours on-call, this likely isn't the right role, and that's completely fine.

Our Culture

Who we are:

Led by two pioneering co-founders we are one of the fastest growing companies in the U.S., creating our own category of enterprise autonomous software development. We automate thousands of hours of software development for our customers, which includes strong representation within the Fortune 500.

How we work:

We move Blitzy Fast: Time is both our company's and our clients' most precious asset. We move quickly and decisively to innovate internally and deliver exceptional software externally.

Championship Mindset: We operate like a professional sports team. We win as a team by holding ourselves and each other to high standards, collaborating in-person, and remaining focused on the mission.

Passion for Invention: We're pushing the frontier of what's possible, requiring constant innovation and iteration.

We Work for the Customer: We focus on delivering outsized value to the customers we work with and expanding those relationships into deep, meaningful partnerships.

We believe in being 'everyday athletes'—taking care of ourselves so we can bring our best minds to work. We promote great sleep, movement, and restorative activities for optimal mental performance. It makes for a happier and more productive team.

Blitzy is an equal opportunity employer committed to building a diverse and inclusive team. We believe different perspectives make us stronger.

About LodgIQ

Headquartered in New York, LodgIQ delivers a revolutionary B2B SaaS platform to the travel industry. By leveraging machine learning and artificial intelligence, we enable precise forecasting and optimized pricing for hotel revenue management. Backed by Highgate Ventures and Trilantic Capital Partners, LodgIQ is a well-funded, high-growth startup with a global presence.

Role Summary:

We are seeking a Senior DevOps Engineer with 5+ years of strong hands-on experience in AWS, Kubernetes, CI/CD, infrastructure as code, and cloud-native technologies. This role involves designing and implementing scalable infrastructure, improving system reliability, and driving automation across our cloud ecosystem.

Key Responsibilities:

• Architect, implement, and manage scalable, secure, and resilient cloud

infrastructure on AWS

• Lead DevOps initiatives including CI/CD pipelines, infrastructure automation, and monitoring

• Deploy and manage Kubernetes clusters and containerized microservices

• Define and implement infrastructure as code using Terraform/CloudFormation

• Monitor production and staging environments using tools like CloudWatch, Prometheus, and Grafana

• Support MongoDB and MySQL database administration and optimization

• Ensure high availability, performance tuning, and cost optimization

• Guide and mentor junior engineers, and enforce DevOps best practices

• Drive system security, compliance, and audit readiness in cloud environments

• Collaborate with engineering, product, and QA teams to streamline release processes

Required Qualifications:

• 5+ years of DevOps/Infrastructure experience in production-grade environments

• Strong expertise in AWS services: EC2, EKS, IAM, S3, RDS, Lambda, VPC, etc.

• Proven experience with Kubernetes and Docker in production

• Proficient with Terraform, CloudFormation, or similar IaC tools

• Hands-on experience with CI/CD pipelines using Jenkins, GitHub Actions, or similar

• Advanced scripting in Python, Bash, or Go

• Solid understanding of networking, firewalls, DNS, and security protocols

• Exposure to monitoring and logging stacks (e.g., ELK, Prometheus, Grafana)

• Experience with MongoDB and MySQL in cloud environments

Preferred Qualifications:

• AWS Certified DevOps Engineer or Solutions Architect

• Experience with service mesh (Istio, Linkerd), Helm, or ArgoCD

• Familiarity with Zero Downtime Deployments, Canary Releases, and Blue/Green Deployments

• Background in high-availability systems and incident response

• Prior experience in a SaaS, ML, or hospitality-tech environment

Tools and Technologies You’ll Use:

• Cloud: AWS

• Containers: Docker, Kubernetes, Helm

• CI/CD: Jenkins, GitHub Actions

• IaC: Terraform, CloudFormation

• Monitoring: Prometheus, Grafana, CloudWatch

• Databases: MongoDB, MySQL

• Scripting: Bash, Python

• Collaboration: Git, Jira, Confluence, Slack

Why Join Us?

• Competitive salary and performance bonuses.

• Remote-friendly work culture.

• Opportunity to work on cutting-edge tech in AI and ML.

• Collaborative, high-growth startup environment.

• For more information, visit http://www.lodgiq.com

Roles & Responsibilities

• Lead AI Product Pods across Credit Risk, Fraud, and Collections functions.
• Build and deploy production-scale Machine Learning systems for lending lifecycle decisioning.
• Own complete ML lifecycle including feature engineering, model training, evaluation, deployment, monitoring, and continuous improvement.
• Design scalable distributed ML infrastructure, feature stores, model registries, and MLOps pipelines.
• Develop AI solutions for underwriting, portfolio risk monitoring, fraud detection, anomaly detection, and recovery optimization.
• Drive model governance, monitoring, explainability, and compliance within BFSI regulatory standards.
• Collaborate with Product, Risk, Engineering, Data, and Business teams to deliver AI-driven business outcomes.
• Define AI platform architecture, operational excellence, SLAs, and incident management practices.
• Build, mentor, and scale high-performing AI Engineering and Data Science teams.

Ideal Candidate

1.Strong Lead Data Science, / AI Engineer / Machine Learning Engineer profiles.

2.Mandatory (Experience 1) - Must have 10+ years of experience in Data Science, AI/ML or AI Engineering with hands-on experience building production-grade ML systems.

3.Mandatory (Experience 2) - Must have hands-on experience building AI/ML solutions for Credit Risk, Fraud Risk Management (FRM), Collections & Recovery, with proven delivery of business-impacting AI/ML solutions.

4.Mandatory (Experience 3) - Candidate's Current designation must be Lead or above.

5.Mandatory (Experience 4) - Must have strong experience designing and deploying large-scale distributed Machine Learning systems, including model training, fine-tuning, inference, scalable serving, and production deployment.

6.Mandatory (Experience 5) - Strong programming experience in Python, along with exposure to Spark, Kafka, Kubernetes, APIs/Microservices, CI/CD, Feature Store, Model Registry, and Distributed Computing

7.Mandatory (Experience 6) - Experience designing and deploying Credit Risk Models, Fraud Detection Models, Graph ML, Early Warning Systems, Portfolio Monitoring, Collections Optimization, Propensity Models, and Recovery Forecasting.

8.Mandatory (Experience 7) - Proven experience leading AI/ML teams, owning end-to-end delivery, mentoring engineers, driving cross-functional execution, and managing production AI platforms.

9.Mandatory (Experience 8) – Must have experience working under BFSI governance, including PII handling, auditability, model governance, compliance, secure-by-design architecture, approval workflows, and model risk management practices.

10.Mandatory ( Education ) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered

11.Mandatory (Age) - Candidate's Age should be below 37 years.

12.Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

13.Preferred (Experience 1) - Candidates currently working as Lead / Principal / Engineering Manager / Associate Director / Director in reputed Product, FinTech, Banking, NBFC, or Global Capability Centers will be preferred.

14.Preferred (Experience 2) - Indian professionals currently working overseas (NRI) who are planning to relocate and permanently settle in India are encouraged to apply.

15.Preferred (Experience 4) - Experience building enterprise AI platforms using Graph ML, Vector Databases, LLM-enabled decisioning, distributed training frameworks, and large-scale AI infrastructure.

Job description:

Position: Senior Infrastructure & Cloud Architect

Experience: 10+ Years

Location: Bangalore (Hybrid – 3 Days WFO)

Employment Type: Contract Workforce (CW)

Payroll: Haparz

Budget: Up to 30 LPA

Role Overview

We are looking for an experienced Senior Infrastructure & Cloud Architect to assess, modernize, and optimize enterprise infrastructure environments across hybrid cloud and on-premises platforms. The ideal candidate will have extensive expertise in AWS, enterprise infrastructure, cloud transformation, and infrastructure assessments while working closely with technical teams and business stakeholders to deliver scalable, resilient, and secure infrastructure solutions.

Key Responsibilities

• Assess enterprise infrastructure environments across on-premises and AWS cloud platforms.
• Evaluate current-state infrastructure and recommend modernization roadmaps.
• Review compute, virtualization, storage, backup, disaster recovery, monitoring, and operational infrastructure.
• Analyze AWS environments for scalability, security, performance, and operational excellence.
• Assess OpenShift, Kubernetes, Kafka, and Oracle platform architectures.
• Identify infrastructure risks, resiliency gaps, technology debt, and operational improvements.
• Review infrastructure security, governance, compliance, and disaster recovery strategies.
• Collaborate with architects, infrastructure teams, operations, security, and executive stakeholders.
• Conduct infrastructure maturity assessments, gap analysis, and cloud transformation recommendations.
• Review infrastructure automation practices using Terraform, Ansible, CloudFormation, Jenkins, GitHub Actions, or similar tools.
• Prepare architecture documentation, assessment reports, and executive presentations.

Required Skills & Experience

• 10+ years of enterprise infrastructure architecture or engineering experience.
• 5+ years of hands-on AWS infrastructure experience.
• Strong expertise in hybrid cloud and enterprise infrastructure environments.
• Experience with AWS services including EC2, Auto Scaling, IAM, EBS, EFS, S3, CloudWatch, CloudTrail, Systems Manager, and AWS Backup.
• Strong understanding of VMware, Linux, Windows Server, storage, backup, and disaster recovery.
• Experience evaluating OpenShift and Kubernetes infrastructure.
• Experience assessing Kafka platform architecture and operational management.
• Knowledge of Oracle infrastructure including Data Guard, replication, backup, and disaster recovery.
• Experience with infrastructure monitoring, observability, logging, and operational support.
• Strong knowledge of infrastructure security, hardening, patch management, encryption, and compliance.
• Familiarity with Infrastructure as Code (Terraform, Ansible, CloudFormation) and CI/CD tools.
• Excellent stakeholder management, documentation, analytical, and presentation skills

Job Title : Data Platform Engineer (SDE 2 / SDE 3)

Experience : 3 to 8 Years (SDE2 : 3 to 5 Years | SDE3 : 5.5 to 8 Years)

Location : Remote (Contract) → Pune (Post Conversion)

Employment Type : Contract-to-Hire (3 Months)

Mandatory Skills :

Java / Python / Go, SQL, Data Engineering, ETL / ELT, Apache Airflow, Apache Spark / Flink, Kafka, AWS/GCP/Azure, Distributed Systems, API Development, Docker, Kubernetes, CI/CD, System Design

Role Overview :

We are looking for a Data Platform Engineer with strong backend engineering expertise to build scalable, high-performance data platforms and distributed systems. The ideal candidate should have hands-on experience in developing production-grade backend applications along with designing and maintaining modern data pipelines.

Key Responsibilities :

• Build and maintain scalable ETL/ELT and data processing pipelines.
• Develop backend services and APIs using Java (preferred), Python, or Go.
• Design batch and real-time data pipelines using Spark, Flink, Kafka, and Airflow.
• Optimize SQL queries, data models, and distributed data systems.
• Work with cloud platforms (AWS, GCP, or Azure) and container technologies (Docker, Kubernetes).
• Implement CI/CD, monitoring, logging, and performance optimization.
• Collaborate with product and engineering teams on scalable system design and architecture.

Required Qualifications :

• SDE 2 : 3 to 5 years of Backend + Data Engineering experience.
• SDE 3 : 5.5 to 8 years of Backend + Data Engineering experience.
• Strong coding skills in Java (preferred), Python, or Go.
• Excellent SQL and data modeling knowledge.
• Hands-on experience with Airflow, Apache Spark / Apache Flink, or similar technologies.
• Experience building scalable backend services and APIs.
• Good understanding of distributed systems, system design. and scalable architecture.
• Experience with cloud platforms (AWS, Azure, or GCP).
• Hands-on experience with Docker and Kubernetes.
• Strong understanding of CI/CD pipelines.
• Excellent problem-solving and debugging skills.

Good to Have :

• Experience with Snowflake, BigQuery, or Redshift.
• Understanding of Kafka, Kinesis, or Pub/Sub
• Performance optimization of large-scale distributed systems
• FinTech or high-scale distributed systems experience.
• Knowledge of data governance, security, and compliance.

Preferred Candidate Profile :

• Strong Backend + Data Engineering experience
• Experience building scalable production systems
• Strong ownership mindset
• Good system design knowledge
• Experience processing millions of events using Kafka/Spark
• Built APIs supporting data infrastructure
• Production engineering experience

Interview Process :

1. Take-home Coding Assignment (48 Hours)
2. Leadership & Strategy Round (1 Hour)
3. Technical Depth – Data Engineering & Performance (1 Hour)
4. Culture & Values Fit (30 Minutes)

Cloud Expertise(Azure):

• Strong understanding of cloud services and resources like AI services, webapp, database, including monitoring tools like Azure Monitor and Log Analytics.

• Experience with Infrastructure as Code (IaC) tools such as Arm template / Bicep/Terraform.

• Deep understanding of Networking concepts(DNS, DHCP , Hub and Spoke).

• Understanding on policies and security aspects of cloud.

Kubernetes & Helm:

• In-depth knowledge of Kubernetes concepts such as pods, services, ingress, config maps, and secrets.

• Understand of Kubernetes templates and its deployment.

• Proficiency with Helm/ Kustomize or equivalent for Kubernetes package management and deployment automation.

• Implement Kubernetes best practices, including security, networking, and scaling.

• Concepts of Docker and Containers

CI/CD & Programming:

• Hands-on experience with YAML-based CI/CD pipelines (e.g., Azure DevOps, GitHub Actions).

• Familiarity with scripting and automation tools such as PowerShell, Azure CLI, or Bash.

• Proven skill in python programming and concepts.

Monitoring and Observability:

Expertise in creating and managing Grafana dashboards for visualizing metrics and logs.

• Knowledge of Log Analytics & Azure Application Insights for performance monitoring and tracing.

🚀 Job Title : DevOps Engineer / Site Reliability Engineer (SRE)

Experience Level : 4+ Years

Location : Gurugram Sector 48, Haryana (On-site)

Employment Type : Full Time Opportunity

About the Role :

We are looking for a proactive DevOps / Site Reliability Engineer (SRE) with around 4 years of hands-on experience designing, automating, and scaling cloud infrastructure and CI/CD delivery pipelines.

In this role, you will bridge the gap between development and operations. You will be responsible for orchestrating containerized applications, automating infrastructure via Code (IaC), establishing SRE best practices (SLIs, SLOs, SLAs), and ensuring maximum uptime, resiliency, and operational efficiency across multi-cloud environments (AWS/Azure/GCP).

Mandatory Skills :

AWS, Kubernetes, Docker, Terraform, Ansible, Jenkins, GitLab CI/CD, GitHub Actions, Python, Bash, CI/CD, Infrastructure as Code (IaC), Grafana, Prometheus, ELK, New Relic, CloudWatch, SRE, SLI/SLO/SLA, Linux

Key Responsibilities :

1. Cloud Infrastructure & Infrastructure as Code (IaC) :

• Provision, configure, and maintain scalable, high-availability infrastructure on multi-cloud platforms, primarily AWS (EC2, VPC, IAM, S3, RDS, Route53, ALB/ASG, Lambda, EBS).
• Build, deploy, and manage Infrastructure as Code (IaC) using Terraform, Ansible, and CloudFormation to enforce consistency and eliminate configuration drift.
• Execute disaster recovery (DR) planning, automated failover / failback mechanisms, and chaos engineering exercises to validate system resiliency.

2. CI/CD, Automation & Development :

• Design, end-to-end maintain, and optimize robust CI/CD pipelines using Jenkins, GitLab CI, and GitHub Actions.
• Automate release pipelines, versioning, branching strategies, and approval gates using Groovy, Python, and Bash scripting. Integrate automated code quality and security scanning tools (SonarQube, Black Duck, or Fortify) directly into delivery pipelines.
• Develop custom tools, scripts, or microservices (e.g., Python / Node.js) to automate manual operational tasks and operational toil.

3. Containerization & Orchestration :

• Onboard and orchestrate containerized microservices utilizing Docker and Kubernetes (including Helm charts).
• Ensure high availability, auto-scaling, resource management, and fault tolerance for Kubernetes pod deployments.

4. Observability, SRE & Incident Management :

• Drive Site Reliability Engineering (SRE) maturity by establishing, tracking, and reporting SLIs, SLOs, and SLAs with cross-functional engineering teams.
• Build, configure, and manage full-stack observability tools : Grafana, Prometheus, New Relic, Elasticsearch / Logstash / Kibana (ELK), Sentry, and AWS CloudWatch.
• Set up real-time alerting, custom metric dashboards, and automated log rotation / pruning scripts.
• Handle production incidents, lead Root Cause Analysis (RCA) investigations, and implement preventive measures to reduce Mean Time to Resolution (MTTR).

Required Qualifications & Skills :

• Education : Bachelor’s Degree in Electronics and Communication Engineering, Computer Science, or a related technical field.
• Experience : ~4 years of experience in DevOps, SRE, or Cloud System Administration roles.
• Cloud & Infrastructure : Hands-on experience with AWS (Core services like EC2, S3, VPC, RDS, IAM, Lambda, Auto Scaling) and exposure to Azure / GCP.
• CI/CD & Version Control : Proficiency with Jenkins, GitLab CI, GitHub Actions, and Git workflows.
• Containerization : Core proficiency in Docker and Kubernetes cluster management / onboarding.
• Infrastructure as Code : Expertise in Ansible, Terraform, or AWS CloudFormation.
• Scripting & Languages : Strong hands-on automation skills with Python, Bash, and foundational knowledge of Node.js, Java or C++.
• Observability & Logging : Strong experience with Grafana, Prometheus, New Relic, ELK stack, or Splunk.
• Database & SQL : Familiarity with relational databases (MySQL, RDS) for monitoring setup and operational analytics.

Amura’s Vision 

We believe that the most under-appreciated route to releasing untapped human potential is to build a healthier body, and through which a better brain. This allows us to do more of everything that is important to each one of us.

Billions of healthier brains, sitting in healthier bodies, can take up more complex problems that defy solutions today, including many existential threats, and solve them in just a few decades.

Billions of healthier brains will make the world richer beyond what we can imagine today. The surplus wealth, combined with better human capabilities, will lead us to a new renaissance, giving us a richer and more beautiful culture.

These healthier brains will be equipped with deeper intellect, be less acrimonious, more magnanimous, and have a kinder outlook on the world, resulting in a world that is better than any previous time.

We find this vision of the future exhilarating. Our hopes and dreams are to create this future as quickly as possible and ensure that it is widely distributed and optimized to maximize all forms of human excellence. 

Role Overview 

We are looking for a highly skilled Senior DevOps Engineer (AI-Native Infrastructure & Platform Engineering) with deep expertise in AWS cloud infrastructure, automation, AI infrastructure operations, and modern DevOps/SRE practices.

This role goes beyond traditional DevOps and requires a seasoned specialist capable of building and operating AI-ready infrastructure platforms that support high-throughput APIs, LLM/AI workloads, GPU-based compute, data-intensive systems, real-time inference pipelines, and scalable ML platforms.

You will be responsible for architecting, automating, securing, and optimizing highly scalable and cost-efficient cloud environments that enable high-velocity engineering and AI teams. This is an ideal position for someone who combines technical ownership, an automation-first mindset, and a passion for developer productivity and platform reliability. 

Key Responsibilities 

Cloud Infrastructure & Platform Engineering (AWS) 

• Architect, deploy, and manage highly scalable and secure infrastructure on AWS. Design cloud platforms supporting AI/ML workloads, data pipelines, real-time APIs, and high-concurrency backend systems.
• Hands-on expertise with key AWS services including EC2, ECS/EKS, Lambda, RDS, DynamoDB, S3, VPC, CloudFront, IAM, CloudWatch, and GPU-enabled instances.
• Build and maintain Infrastructure-as-Code (IaC) using Terraform, CloudFormation, or AWS CDK.
• Design multi-AZ and multi-region architectures for high availability and disaster recovery (HA/DR).
• Build reusable platform templates and shared infrastructure modules. 

AI/ML Infrastructure & MLOps 

• Build and maintain infrastructure for LLM applications, AI inference workloads, model serving platforms, vector databases, and feature stores.
• Support GPU-based workloads and optimize compute/storage usage.
• Enable scalable deployment patterns for AI applications using Kubernetes/EKS. Collaborate with Data Science and ML Engineering teams on model deployment, training/tuning of models, CI/CD for ML systems, experiment environments, and reproducibility.
• Support orchestration and deployment of AI workflows and inference services while implementing observability and reliability for AI pipelines. 

CI/CD, Automation & Developer Productivity 

• Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline.
• Automate deployments, environment provisioning, and release workflows.
• Build self-service developer platforms, preview environments, and reusable deployment workflows to improve developer productivity.
• Implement automated patching, scaling, backups, cleanup workflows, and drift detection. 

Containers, Kubernetes & Platform Reliability

• Manage Docker-based environments, containerized applications, and optimize workloads using Kubernetes (EKS) or ECS/Fargate.
• Manage autoscaling, cluster health, node pools, ingress, service mesh, and workload isolation.
• Optimize infrastructure for performance, resilience, and cost-efficiency.
• Implement progressive deployment strategies including blue/green, canary, and rolling deployments. 

Observability, Incident Response & SRE Practices

• Implement observability stacks using CloudWatch, Prometheus, Grafana, ELK, Datadog, OpenTelemetry, or New Relic.
• Build actionable dashboards and intelligent alerting systems while defining and tracking SLIs, SLOs, and SLAs.
• Lead incident response, root cause analysis, and blameless postmortems to reduce operational toil and improve MTTR.

FinOps, Cost Governance & Security

• Continuously monitor and optimize cloud costs (compute utilization, storage lifecycle, GPU usage, and data transfer) using AWS Cost Explorer, Budgets, Trusted Advisor, CloudHealth, or Kubecost.
• Implement AWS security best practices for IAM, VPCs, security groups, NACLs, encryption, and manage secrets using KMS, SSM Parameter Store, or Vault.
• Build secure CI/CD pipelines with automated security checks, least-privilege access, audit logging, and ensure compliance readiness for ISO 27001, SOC2, and GDPR.

Collaboration, Leadership & Platform Culture

• Work closely with engineering, AI/ML, QA, product, and operations teams to drive a DevOps, SRE, GitOps, and automation-first culture.
• Mentor junior DevOps and Platform Engineers while creating and maintaining detailed runbooks, architecture diagrams, and platform documentation.

Skills & Qualifications

Must-Have:

• 7+ years of experience in DevOps, SRE, Platform Engineering, or Cloud Infrastructure Engineering.
• Strong expertise in AWS cloud architecture, services, and deep understanding of Kubernetes (EKS), containers, and cloud-native systems.
• Strong Infrastructure-as-Code expertise using Terraform, CloudFormation, or CDK. Strong Linux administration, networking, DNS, routing, and load balancing knowledge. Strong scripting/programming experience in Python, Bash, or Go (preferred). Experience with CI/CD automation, GitOps workflows, and observability platforms supporting scalable production systems.

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Here are answers to some questions you may have

Where is your office?

Chennai (Velachery)

Work Model

Work from Office – because great stories are built in person!

Do you have an online presence?

https://amura.ai (we are @AmuraHealth on all social media)

You have strong experience supporting cloud environments within the AWS platform.

* You have hands-on experience with cloud platforms, Docker, Kubernetes, Jenkins, Terraform, Artifactory, infrastructure automation, CI/CD pipelines, monitoring, and operational support in enterprise environments.

* You have hands-on experience with infrastructure automation, scripting, and configuration management.

* You understand monitoring, logging, alerting, and incident management practices in cloud operations.

* You have experience working with containers, orchestration platforms, and deployment pipelines.

* You are comfortable supporting Linux and/or Windows server environments in cloud-based ecosystems.

* You understand identity and access management, security controls, patching, and operational compliance practices.

* You have experience with disaster recovery, backup processes, and platform resilience planning.

* You have the technical depth required to support and guide Cloud Operations activities while contributing to the overall effectiveness of the function from the India side.

You have experience supporting DevOps or Site Reliability Engineering practices.

* You have exposure to cost management and cloud optimization tools.

* You are comfortable presenting operational updates, recommendations, and risk considerations to stakeholders.

* You work well in team-based environments and contribute to shared goals.

* You have effective documentation skills for processes, runbooks, and support knowledge.

* You have experience working in regulated or enterprise-scale environments.

* You have familiarity with service management tools and structured change management processes.

* You demonstrate the potential to take on broader operational ownership and support the leadership of the Cloud Operations function from the India side.

* You are comfortable coordinating with multiple stakeholders and contributing to operational decision-making in a global delivery model.

Job Title : DevOps Engineer / Site Reliability Engineer (SRE)

Experience : 5+ Years

Location : Gurugram, Haryana

Work Mode : On-site (Full-time)

About the Role :

We are looking for a skilled DevOps Engineer with 5+ years of experience in cloud infrastructure, CI/CD, automation, Kubernetes, and Site Reliability Engineering (SRE). The ideal candidate will be responsible for building scalable cloud infrastructure, automating deployments, improving system reliability, and ensuring high availability across production environments.

Mandatory Skills :

AWS, Terraform, Ansible, CloudFormation, Jenkins, GitLab CI, GitHub Actions, Docker, Kubernetes, Helm, Python, Bash, Grafana, Prometheus, ELK Stack, CloudWatch, New Relic, SRE, CI/CD, Infrastructure as Code (IaC), Linux

Key Responsibilities :

• Design, deploy, and manage cloud infrastructure primarily on AWS (EC2, VPC, IAM, S3, RDS, Route53, ALB, Auto Scaling, Lambda).
• Build and maintain Infrastructure as Code (IaC) using Terraform, Ansible, and CloudFormation.
• Develop and optimize CI/CD pipelines using Jenkins, GitLab CI, and GitHub Actions.
• Deploy and manage containerized applications using Docker, Kubernetes, and Helm.
• Implement monitoring and observability using Grafana, Prometheus, ELK Stack, CloudWatch, and New Relic.
• Drive SRE practices by defining SLIs, SLOs, SLAs, handling production incidents, conducting RCA, and improving system reliability.
• Automate operational tasks using Python, Bash, and Groovy scripting.
• Collaborate with Development, QA, Security, and Operations teams to ensure reliable and secure software delivery.

Required Skills & Qualifications :

• Bachelor's degree in Computer Science, IT, Electronics, or a related field.
• 5+ years of experience in DevOps, SRE, or Cloud Infrastructure.
• Strong expertise in AWS, with exposure to Azure/GCP.
• Hands-on experience with Terraform, Ansible, CloudFormation, Docker, Kubernetes, Helm, Jenkins, GitLab CI, GitHub Actions, and Git.
• Strong scripting skills in Python and Bash.
• Experience with monitoring tools such as Grafana, Prometheus, ELK Stack, CloudWatch, and New Relic.
• Good understanding of Linux, networking, SQL, and cloud security best practices.

Preferred Skills :

• Experience with multi-cloud environments and DevSecOps practices.
• Knowledge of disaster recovery, automation, and microservices architecture.
• Strong troubleshooting, communication, and problem-solving skills.

Very strong infra engineer to administer Linux based VMs (and few Windows VMs as well).

Must have strong knowledge and hands-on on docker, Kubernetes

Must be good at monitoring (AppDynamics, Prometheus, Grafana) and logging (Splunk)

Develop automation scripts using Shell and Python. Must have good knowledge in Ansible.

Should be good at optimize/finetune server configurations.

 Should be good in troubleshoot issues and fix them.

Key Responsibilities

Build and maintain data transformation pipelines using Spark

Develop and optimize large-scale/CPU intensive data processing using Apache Spark

Orchestrate workflows using Airflow

Implement data quality checks, testing, and monitoring for pipeline. Good to have exposer into managing metadata, cataloguing, and lineage

Support schema evolution, backfills, and incremental processing

Ensure pipelines meet SLAs for freshness, reliability, and performance

Expertise/working knowledge in Spark and HBase(semantic layer, virtual datasets, Reflections)

Required Skills & Qualifications

hands-on experience with HBase

Apache Spark

Experience with HBase or similar lakehouse query engines

Airflow 

Understanding of data catalogs and lineage (e.g., OpenLineage, DataHub, Apache Polaris , openlineage)

Proficiency in Java

Experience with Git-based development and CI/CD

Nice-to-Have Skills

OpenTable format/Iceberg ,Apache Arrow

CDC-based analytics pipelines

Cloud platforms (AWS)

Kubernetes-based data platforms

About the opportunity:

This role is with Sporty Group. CareersInCloud shares this opportunity to help professionals discover relevant technology careers.

Hiring Company: Sporty Group

Sporty Group is looking for an experienced DevOps Engineer to join its remote engineering team.

This role involves managing AWS cloud infrastructure, Kubernetes environments, CI/CD pipelines, monitoring, automation, and improving system reliability.

Key Responsibilities:

• Manage AWS infrastructure and cloud operations

• Maintain Kubernetes clusters and Docker environments

• Build and improve CI/CD pipelines

• Monitor production systems using Grafana, Prometheus, and CloudWatch

• Troubleshoot Linux, networking, and infrastructure issues

Requirements:

• 3+ years of DevOps experience

• Strong AWS and Kubernetes experience

• Experience with Docker, Linux, CI/CD tools

• Good understanding of cloud infrastructure and automation

Apply here:

https://careersincloud.com/jobs/sporty-group-hiring-devops-engineer-remote-experienced

We are seeking a skilled and experienced Senior DevOps Engineer to join our team. As a Senior DevOps Engineer, you will play a crucial role in designing, implementing, and managing our cloud infrastructure on AWS, while utilizing Docker, Kubernetes, Terraform and Argo CD for containerization and deployment. You will collaborate closely with development teams to ensure smooth software releases, scalability, and reliability of our systems. Also, you will be working on Airflow and Spark configurations for Data pipelines.

Responsibilities:

• Design, implement, and maintain scalable and secure cloud infrastructure on AWS, utilizing services such as EC2, S3, VPC, IAM, and Lambda.
• Build, deploy, and manage containerized applications using Docker and Kubernetes.
• Develop and maintain CI/CD pipelines to enable continuous integration, automated testing, and deployment using tools like Jenkins, GitLab CI/CD, or AWS CodePipeline.
• Implement and manage infrastructure as code (IaC) using tools like Terraform or CloudFormation to automate the provisioning and configuration of AWS resources.
• Monitor and troubleshoot infrastructure and application issues, ensuring high availability, performance, and scalability of the system.
• Collaborate with development teams to ensure smooth and efficient software releases, including version control, branching strategies, and release management.
• Implement and maintain robust security practices, including access control, network security, and data encryption.
• Automate manual tasks and processes using scripting languages (e.g., Python, Bash) and configuration management tools (e.g., Ansible).
• Collaborate with cross-functional teams to gather requirements, provide technical guidance, and implement best practices for infrastructure and deployment processes.
• Stay up-to-date with the latest DevOps tools, technologies, and best practices, and identify opportunities for improvement and optimization in our infrastructure and processes.

Requirements:

• Bachelor’s or master’s degree in computer science, Software Engineering, or a related field.
• Proven experience as a DevOps Engineer, with a focus on AWS, Docker, Kubernetes, and Argo CD.
• Strong experience in designing, implementing, and managing cloud infrastructure on AWS, including services like EC2, S3, VPC, IAM, and Lambda.
• Hands-on experience with containerization technologies, specifically Docker and Kubernetes.
• Proficiency in CI/CD pipeline setup and management using tools like Jenkins, GitLab CI/CD, or AWS CodePipeline.
• Solid understanding of infrastructure as code (IaC) principles and experience with tools like Terraform or CloudFormation.
• Experience in monitoring and troubleshooting complex infrastructure and application issues.
• Strong scripting and automation skills using languages such as Python, Bash, or PowerShell.
• Excellent problem-solving and analytical skills, with the ability to handle and prioritize multiple tasks in a fast-paced environment.
• Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams.

Preferred Qualifications:

• AWS certifications, such as AWS Certified DevOps Engineer or AWS Certified Solutions Architect.
• Experience with infrastructure monitoring and logging tools like CloudWatch, ELK stack, or Prometheus/Grafana.
• Knowledge of serverless architectures and experience with AWS Lambda.
• Familiarity with other cloud platforms (e.g., Azure, Google Cloud Platform).
• Understanding of security best practices and experience implementing security measures in cloud infrastructure.

Senior DevOps Engineer

Location: India, Remote

Type: Contract

Department: Engineering

About Us

OpenAssets is building open standards for the next generation of capital markets, providing the trusted foundation for real-world asset tokenization and digital currencies.

We specialize in alternative asset digitization, offering regulatory-conscious tools to design, issue, and manage digital assets in complex financial environments. We also develop loyalty solutions that turn customer engagement into programmable digital assets, helping brands create personalized experiences that drive growth.

OpenAssets operates at the intersection of finance, technology, and regulation focused on building secure, scalable, and open infrastructure for the future of digital markets. Join OpenAssets and be part of shaping the future of digital finance!

Overview

We are seeking a Senior DevOps Engineer to lead the evolution of our cloud infrastructure and deployment ecosystems.

This role acts as the foundation of our engineering reliability, bridging the gap between high-performance blockchain development and robust, secure cloud operations. You will be responsible for architecting scalable AWS environments, automating mission-critical CI/CD pipelines, and ensuring the absolute integrity of our security and observability frameworks.

What You’ll Do

Cloud Infrastructure & Architecture

• Design, provision, and maintain OpenAssets’ AWS infrastructure: including EC2, ECS/Fargate, Lambda, S3, RDS, VPC, IAM, CloudFront, SQS, ElastiCache, and CloudWatch.
• Architect for high availability, fault tolerance, and cost efficiency across production and non-production environments.
• Manage networking, security groups, subnets, load balancers, and access controls to ensure a secure and well-segmented cloud environment.
• Scale infrastructure dynamically to handle platform growth, partner onboarding, and peak load events.
• Deploy, configure, and manage blockchain node infrastructure supporting on-chain integrations and smart contract interactions.

CI/CD & Automation

• Implement and maintain CI/CD pipelines using GitHub Actions and/or AWS CodeBuild for frontend, backend, and smart contract deployments.
• Manage infrastructure as code using Terraform (or OpenTofu) and/or CloudFormation to ensure reproducible, auditable environments.
• Automate build, test, and deployment processes to minimize manual effort and reduce release risk.
• Develop and maintain automation scripts in Python and Bash for operational and provisioning workflows.
• Administer and scale Kubernetes clusters (EKS) for deploying services and blockchain node infrastructure.

Security & Compliance

• Implement and enforce security best practices across infrastructure: TLS, VPNs, IAM roles, private key management, secrets management, and patch management.
• Work with the CISO to conduct infrastructure security audits and maintain compliance with data handling, uptime, and audit logging requirements.
• Manage secrets and environment configuration securely using AWS Secrets Manager or HashiCorp Vault.
• Ensure encryption at rest and in transit across all critical data stores and communication channels.
• Apply knowledge of blockchain security, including consensus mechanisms, smart contract interactions, and Layer 2 infrastructure, to harden on-chain components.

Observability & Incident Response

• Set up and maintain monitoring, alerting, and dashboards for key platform metrics using CloudWatch, Prometheus, Grafana, or equivalent.
• Establish structured logging and distributed tracing practices (OpenTelemetry or similar) across services.
• Lead incident response for production issues, triaging, communicating, resolving, and writing blameless postmortems.
• Design, implement, and regularly test backup and disaster recovery strategies to minimize data loss and downtime.

Collaboration & Enablement

• Support engineering teams in troubleshooting environment-specific issues across development, staging, and production.
• Document infrastructure architecture, runbooks, and operational procedures — keeping them current and actionable.
• Train developers on deployment tooling, CI/CD workflows, and on-call processes.
• Evaluate and introduce new tooling and practices to improve DevOps maturity across the organization.

Qualifications & Experience

• 5+ years of experience in DevOps, SRE, or cloud infrastructure engineering.
• Deep hands-on expertise with AWS: EC2, ECS/Fargate, Lambda, RDS, S3, VPC, IAM, CloudWatch, SQS, CloudFront, and ElastiCache.
• Strong experience with infrastructure as code using Terraform, OpenTofu, and/or CloudFormation.
• Proficiency with containerization and orchestration (Docker, Kubernetes / EKS).
• Experience designing and maintaining CI/CD pipelines using GitHub Actions, AWS CodeBuild, GitLab CI, or similar.
• Solid Linux systems administration and scripting skills (Bash, Python).
• Strong understanding of cloud networking and security: TLS, VPCs, security groups, IAM, private key management, secrets management.
• Experience with monitoring and observability tooling: CloudWatch, Prometheus, Grafana, ELK stack, or equivalent.
• Familiarity with distributed tracing (OpenTelemetry, Jaeger, or similar).
• Working knowledge of blockchain technologies: consensus mechanisms, smart contract infrastructure, or Layer 2 scaling solutions.
• Calm, systematic problem-solving approach to production incidents and outages.
• Strong communication skills, able to explain infrastructure concerns clearly to both technical and non-technical stakeholders.
• Fluid in English

Nice to Have

• AWS certifications (Solutions Architect, DevOps Engineer Professional, or equivalent).
• Experience deploying and operating blockchain node infrastructure (Ethereum, Polygon, or similar).
• Background in fintech, capital markets, payments, or regulated infrastructure environments.
• Experience with security frameworks and compliance standards (SOC 2, ISO 27001).
• Multi-tenant SaaS infrastructure experience.
• Experience with event-driven architectures (Kafka, SQS, BullMQ).
• Cost optimization practices: reserved instances, Savings Plans, right-sizing.
• Infrastructure as code with Pulumi or CDK.
• Open-source contributions or technical writing.

We are committed to providing equal opportunity for qualified applicants to contract positions, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. This is a contract opportunity, not a direct employment role.

Company Name – Wissen Technology

Group of companies in India – Wissen Technology & Wissen Infotech

While you may already know about Wissen and the company history, here is a quick rundown for you.

About Wissen Technology:

·        The Wissen Group was founded in the year 2000. Wissen Technology, a part of Wissen Group, was established in the year 2015.

·        Wissen Technology is a specialized technology company that delivers high-end consulting for organizations in the Banking & Finance, Telecom, and Healthcare domains. We help clients build world class products.

·        Our workforce has highly skilled professionals, with leadership and senior management executives who have graduated from Ivy League Universities like Wharton, MIT, IITs, IIMs, and NITs and with rich work experience in some of the biggest companies in the world.

·        Wissen Technology has grown its revenues by 400% in these five years without any external funding or investments.

·        Globally present with offices US, India, UK, Australia, Mexico, and Canada.

·        We offer an array of services including Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud, Mobility, Agile & DevOps, Quality Assurance & Test Automation.

·        Wissen Technology has been certified as a Great Place to Work®.

·        Wissen Technology has been voted as the Top 20 AI/ML vendor by CIO Insider in 2020.

·        Over the years, Wissen Group has successfully delivered $650 million worth of projects for more than 20 of the Fortune 500 companies.

·        We have served client across sectors like Banking, Telecom, Healthcare, Manufacturing, and Energy. They include likes of Morgan Stanley, Goldman Sachs, MSCI, StateStreet, Flipkart, Swiggy, Trafigura, GE to name a few.

Job Title: Software Developer

Experience: 4–6 Years

Location: Pune / 3 days' work from Office.

Employment Type: Full-Time

Job Summary

We are looking for a highly skilled Java Developer with strong experience in Java application development, Kubernetes, and CI/CD pipelines. The ideal candidate should have hands-on experience in building scalable backend applications, working with microservices architecture, and deploying applications in containerized cloud environments.

Key Responsibilities

• Design, develop, test, and maintain scalable Java-based applications.
• Develop RESTful APIs and microservices using Java frameworks.
• Build and deploy containerized applications using Docker and Kubernetes.
• Design, implement, and maintain CI/CD pipelines for automated build, testing, and deployment.
• Collaborate with DevOps, QA, and product teams to ensure smooth software delivery.
• Monitor application performance and troubleshoot production issues.
• Write clean, maintainable, and reusable code following coding standards and best practices.
• Participate in code reviews, technical discussions, and architecture decisions.
• Optimize application performance, security, and scalability.

Required Skills

• Strong experience in Java development
• Hands-on experience with Spring / Spring Boot
• Good understanding of Microservices Architecture
• Strong knowledge of Kubernetes (K8s) and container orchestration
• Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or Bamboo
• Experience with Docker / Containerization
• Strong knowledge of REST APIs
• Good understanding of SQL / Databases
• Experience with Git version control
• Strong debugging and problem-solving skills

Good to Have

• Cloud platform exposure: AWS / Azure / GCP
• Monitoring tools: Grafana, Prometheus, Datadog
• Messaging systems: Kafka / RabbitMQ
• Scripting knowledge: Shell / Python
• Exposure to Agile / Scrum environment

Preferred Background

• Experience working in BFSI, FinTech, Credit Risk, Lending, or Enterprise Product Development environments.
• Ability to work independently and mentor junior developers.

Work Model: Hybrid (3–4 days from Pune office)

Job Title : Senior Azure Data / MLOps / AI Platform Engineer

Experience : 6+ Years

Employment Type : Contract

Role Level : Senior

Project : Leading South Africa Telecommunications Operator

Department : Data & AI Engineering

Job Overview :

We are looking for a Senior Azure Data / MLOps / AI Platform Engineer to design, build, and manage Azure-native cloud infrastructure, MLOps pipelines, and AI platforms supporting enterprise-scale data products and AI applications.

The ideal candidate will have strong expertise in Azure Cloud, Azure Databricks, Infrastructure as Code, CI/CD, Kubernetes, and MLOps, enabling scalable deployment of machine learning, GenAI, and AI Agent solutions.

Mandatory Skills :

Microsoft Azure, Azure Databricks, Terraform/Bicep, Azure DevOps or GitHub Actions, Docker, Kubernetes (AKS), MLflow, Azure ML, Kubeflow, CI/CD, MLOps, Infrastructure as Code, Azure Monitor, Prometheus, Grafana, Vector Databases, AI Platform Engineering.

Key Responsibilities :

• Design, deploy, and maintain Azure cloud infrastructure, landing zones, networking, storage, and compute environments.
• Build and manage Azure Databricks environments for data engineering and AI workloads.
• Develop Infrastructure as Code using Terraform or Bicep.
• Create and maintain CI/CD pipelines using Azure DevOps or GitHub Actions.
• Implement MLOps solutions including model deployment, MLflow, model registry, monitoring, drift detection, and automated retraining.
• Deploy and manage AI platform components such as vector databases, model-serving endpoints, and AI infrastructure.
• Manage containerized workloads using Docker, Kubernetes (AKS), and cloud-native deployment practices.
• Monitor platform performance, observability, security, reliability, and infrastructure costs.
• Collaborate with Data Engineering, AI/ML, GenAI, Cybersecurity, and Solution Architecture teams to deliver scalable enterprise AI platforms.

Required Skills :

• 6+ years of experience in Cloud, Platform, or MLOps Engineering.
• Strong hands-on experience with Microsoft Azure services and Azure infrastructure.
• Expertise in Azure Databricks, Terraform/Bicep, and Infrastructure as Code.
• Experience with Azure DevOps or GitHub Actions for CI/CD.
• Strong MLOps knowledge including MLflow, Azure ML, Kubeflow, Model Registry, Model Deployment, Monitoring, and Drift Detection.
• Experience with Docker, Kubernetes (AKS), and Container Orchestration.
• Familiarity with Vector Databases, GenAI infrastructure, LLM deployment, and AI platform engineering.
• Experience with monitoring tools such as Azure Monitor, Prometheus, and Grafana.

Good to Have :

• Experience with Azure OpenAI, AI platforms, or enterprise GenAI deployments.
• Telecom, Banking, or other large enterprise domain experience.
• Microsoft Azure, Databricks, or MLOps certifications.

Job Title : Senior API Developer (Spring Boot Microservices + Apigee/APIM)

Experience : 6+ Years

Employment Type : Contract

Role Level : Senior

Project : Leading South Africa Telecommunications Operator

Department : Application & Experience Engineering

Job Overview :

We are seeking a Senior API Developer with strong expertise in Spring Boot Microservices and API Gateway technologies (Apigee/Azure API Management) to design, develop, and manage secure, scalable APIs for enterprise applications and partner integrations.

The ideal candidate will build high-performance APIs exposing business insights, analytics, and AI/ML services while ensuring security, scalability, and reliability.

Mandatory Skills :

Java, Spring Boot, Microservices, REST APIs, Apigee or Azure API Management (APIM), OAuth2, OpenID Connect (OIDC), JWT, Docker, Kubernetes (AKS), API Security, API Gateway, Microservices Architecture, Kafka (Preferred).

Key Responsibilities :

• Design, develop, and maintain secure RESTful APIs using Spring Boot Microservices.
• Build scalable microservices following best practices for resilience, performance, and maintainability.
• Configure and manage APIs using Apigee or Azure API Management (APIM), including authentication, rate limiting, traffic management, and analytics.
• Implement API security using OAuth2, OpenID Connect (OIDC), API Keys, and Mutual TLS.
• Collaborate with Full Stack, AI/ML, Solution Architecture, and Cybersecurity teams to deliver enterprise-grade integrations.
• Support external partner integrations and internal enterprise systems through well-designed API contracts.
• Optimize API performance, monitor usage, troubleshoot issues, and maintain API lifecycle, versioning, and documentation.

Required Skills :

• 6+ years of experience in Backend/API Development.
• Strong hands-on experience with Java, Spring Boot, and Microservices Architecture.
• Expertise in Apigee or Azure API Management (APIM).
• Strong understanding of REST APIs, API versioning, and API lifecycle management.
• Experience implementing OAuth2, OpenID Connect (OIDC), JWT, API Security, and Authentication.
• Experience with Docker, Kubernetes (AKS), and Cloud-native deployments.
• Familiarity with Kafka or other event-driven messaging platforms is a plus.
• Excellent understanding of enterprise integration patterns and scalable API design.

Good to Have :

• Experience with Azure Cloud.
• Telecom, Banking, FinTech, or other regulated industry experience.
• Certifications in Apigee, Microsoft Azure, or Microservices Architecture.

At BigThinkCode, our technology solves complex problems. We are looking for talented Azure Cloud Devops engineer to join our Cloud Infrastructure team at Chennai.

Please find below our job description, if interested apply / reply sharing your profile to connect and discuss.

Company: BigThinkCode Technologies

URL: https://www.bigthinkcode.com/

Role: Devops Engineer

Experience required: 3–5 years

Work location: Chennai

Joining time: Immediate – 2 weeks

Work Mode: Work from office (Hybrid)

About the Role:

We are looking for a DevOps Engineer with 3+ years of hands-on experience to build and manage CI/CD pipelines, cloud infrastructure, containerized deployments, and operational monitoring. The engineer will work closely with Architects, Developers, QA, and Integration teams to deliver secure, scalable, and production-ready applications across AWS and Microsoft Azure environments.

Key Responsibilities

· Design, implement, and maintain CI/CD pipelines using GitHub Actions, Azure DevOps, Jenkins, or similar tools.

· Deploy, manage, and monitor applications on AWS and/or Microsoft Azure.

· Build and manage containerized applications using Docker.

· Provision cloud infrastructure using Terraform or Infrastructure as Code (IaC).

· Configure IAM, Key Vault/Secrets Manager, networking, SSL, and secure deployments.

· Implement monitoring, logging, alerting, backup, and disaster recovery solutions.

· Collaborate with development teams to troubleshoot build, deployment, and production issues.

· Maintain deployment documentation, runbooks, and operational procedures.

Required Skills & Qualifications

· 3+ years of experience in DevOps / Cloud / Infrastructure Engineering.

· Strong understanding of DevOps principles and CI/CD practices.

· Hands-on experience with AWS and/or Microsoft Azure.

· Experience with GitHub Actions, Azure DevOps, Jenkins, or similar CI/CD tools.

· Strong Linux administration skills.

· Hands-on experience with Docker and container lifecycle management.

· Working knowledge of Terraform or other Infrastructure as Code tools.

·  Experience with cloud services such as:

· AWS: EC2, IAM, S3, VPC, RDS, CloudWatch, ECR

· Azure: App Services, Container Apps, Key Vault, Azure Monitor, Application Insights, Azure Container Registry

· Good understanding of networking concepts (DNS, SSL, Load Balancers, Firewalls, Virtual Networks).

· Basic operational knowledge of PostgreSQL/MySQL.

· Strong troubleshooting and production support skills.

Good to Have

· Kubernetes (AKS/EKS) or Azure Container Apps.

· Monitoring tools such as Prometheus, Grafana, ELK, CloudWatch, or Azure Monitor.

· Experience with GitHub Enterprise, Branch Protection, and CI/CD quality gates.

· Exposure to security tools such as CodeQL, Dependabot, Trivy, or SonarQube.

· Shell, Bash, PowerShell, or Python scripting.

· Experience with Microsoft Entra ID (Azure AD), OAuth, or SSO.

· Exposure to enterprise integration environments (Oracle, Kafka, REST APIs, OIC).

Soft Skills

· Strong ownership and problem-solving mindset.

· Good communication and documentation skills.

· Ability to work collaboratively in Agile teams.

· Passion for automation, security, and continuous improvement. 

🚀 We're Hiring | Site Reliability Engineer (SRE)

📍 Location: Hyderabad (Hybrid)

💼 Experience: 4–6 Years

P99Soft is looking for a skilled Site Reliability Engineer (SRE) to join our engineering team. If you're passionate about building highly available, scalable cloud infrastructure and driving automation across modern DevOps environments, we'd love to hear from you.

Key Responsibilities

- Design, implement, maintain, monitor, and support backend servers and microservices infrastructure.

- Build and maintain automation tools for development, testing, operations, and IT infrastructure.

- Participate in 24/7 on-call support for production incidents (PagerDuty).

- Collaborate with cross-functional teams to ensure seamless deployments and operational excellence.

- Define and improve SRE processes across development, testing, releases, and support.

- Troubleshoot complex infrastructure and production issues.

- Drive infrastructure automation and continuous process improvements.

Implement security best practices, vulnerability assessments, and risk management.

- Perform incident management and root cause analysis (RCA).

- Monitor system health, customer experience, and operational KPIs.

Required Skills

- Cloud Platforms: AWS, GCP

- Containerization & Orchestration: Docker, Kubernetes, Rancher, Amazon EKS, Amazon ECS, GKE, Elastic Beanstalk, Google App Engine

- Infrastructure as Code (IaC): Terraform, AWS CloudFormation, GCP Deployment Manager, Ansible

- Monitoring & Observability: Prometheus, Datadog, Alertmanager, Thanos, AWS CloudWatch

- CI/CD: GitLab CI/CD, Jenkins

- Scripting: Python, Golang

- Version Control: GitLab, Perforce, Subversion

- Operating Systems: Ubuntu, CentOS, Amazon Linux, Red Hat Enterprise Linux

If you have hands-on experience managing cloud-native infrastructure, Kubernetes environments, DevOps automation, and production operations, we'd love to connect with you.

📩 Share your resume:

Know someone who would be a great fit? Feel free to like, share, or tag them in the comments.

#Hiring #SiteReliabilityEngineer #SRE #CloudEngineer #DevOps #AWS #GCP #Kubernetes #Docker #Terraform #Jenkins #GitLab #Python #Golang #Infrastructure #CloudComputing #HyderabadJobs #HybridJobs #TechJobs #P99Soft

On the Job

● Build and maintain scalable cloud infrastructure on AWS

● Improve CI/CD pipelines, deployment systems, and developer workflows

● Automate infrastructure provisioning using Infrastructure-as-Code (Terraform/Pulumi)

● Manage and optimize Kubernetes clusters and containerized workloads

● Improve observability across systems through monitoring, logging, and alerting

● Drive reliability initiatives including incident response, root cause analysis, and operational

improvements

● Collaborate with engineering teams to improve service scalability, performance, and security

● Implement IAM, secrets management, and infrastructure security best practices

● Optimize infrastructure costs and improve resource efficiency

● Actively leverage AI tools and workflows to improve engineering productivity and automation

Must Haves

● 3–6 years of experience in DevOps, Platform Engineering, or SRE roles

● Strong hands-on experience with AWS infrastructure and services

● Good understanding of Kubernetes, Docker, and container orchestration

● Experience with Infrastructure-as-Code tools like Terraform or Pulumi

● Strong scripting/coding skills in Python, Go, or Bash

● Experience building and maintaining CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI,

etc.)

● Understanding of networking fundamentals, Linux systems, and cloud security practices

● Familiarity with monitoring and observability tools like Prometheus, Grafana, ELK, Datadog,

etc.

● Strong debugging and problem-solving skills

● Ability to work independently in a fast-moving environment

Good To Haves

● Experience working in fintech or high-scale startup environments

● Exposure to service mesh, zero-trust security, or secrets management systems

● Experience with multi-cluster Kubernetes environments

● Familiarity with incident management, SLOs, and reliability engineering practices

● Experience building internal developer platforms or automation tooling

SENIOR PLATFORM ENGINEER

LOCATION: BENGALURU

It is a leading global sports activity platform with over 5 million

users across 5 countries, that connects players, venues, trainers, and

brands in one full stack ecosystem across 50+ sports. We operate at

the intersection of consumer technology, social networking,

marketplaces & real-world logistics and are building a scalable, multi-

vertical sports-tech venture with a focus on long-term sustainability

and global dominance.

Senior Platform Engineer

The Opportunity: This is a high-ownership, foundational role. You will set the direction for how we

run our systems — incident response, reliability, security, quality and cost — and build the systems

and practices.

Roles and Responsibilities:

● Infrastructure: Be the accountable owner of our Cloud Infra across AWS and GCP —

including ECS, RDS, ElastiCache, networking (VPC), and IAM services

● Observability & SLOs: Define SLIs/SLOs and error budgets and build the metrics, logs, tracing,

and alerting that catch problems before customers do.

● Reliability engineering: Incident management & on-call. Own end to end incident process —

severity levels, paging, an incident bridge, and act as incident commander.

● Cost/FinOps: Own cloud cost — right-sizing, commitments (Savings Plans / RIs), cost-

allocation tagging, and resource lifecycle — balancing efficiency against performance.

● Security: Drive security best practice — least-privilege IAM, MFA/SSO, secrets management

www.playo.co

and rotation, network segmentation, detective controls, and encryption.

Requirements:

● 4 - 6 years experience with end-to-end ownership of production including platform,

infrastructure and SRE responsibilities

● Hands-on depth across AWS - compute, data stores, networking, and IAM, and fluency with

the AWS Well-Architected Framework and its trade-offs.

● Deep observability understanding — SLIs/SLOs/error budgets, metrics/logs/traces, and

alerting that pages on real user-facing symptoms

● Passion for sports and fitness

● Excitement about working in a fast-paced startup environment

Principal DevOps Engineer

Note - Screening Requirement: Please note that this position requires a minimum of 8+ years of hands-on Architecting DevOps/SRE/Platform Engineering experience specializing in AWS, EKS/Kubernetes, Terraform, Python, Jenkins, and AI workflows (Mandatory skills) from scratch.

We are looking for an absolute builder who has a proven track record of personally architecting, designing and setting up production-grade AWS EKS clusters entirely from scratch. If your experience is primarily limited to managing, maintaining, or optimizing pre-existing environments that were already stood up by another team, this is not the right opportunity for you.

Who are we?

Securin is an AI-driven cybersecurity company focused on proactive, adversarial exposure and vulnerability management. Our mission is to help organizations reduce cyber risk by identifying, prioritising, and remediating the issues that matter most. Powered by a seasoned team of threat researchers and status as a Certified Naming Authority (CNA), Securin combines artificial intelligence / machine learning, threat intelligence, and deep vulnerability research (including the Dark Web) to deliver an adversarial approach to cyber defense. We help enterprises shift from reactive patching to strategic, risk-based exposure and vulnerability management – driving smarter security decisions and faster remediation.

What do we promise?

We are a highly effective tech-enabled cybersecurity solutions provider and promise continual security posture improvement, enhanced attack surface visibility, and proactive prioritized remediation for every one of our client businesses.

What do we provide?

● A chance to be on the leading edge of cybersecurity and AI

● Ability to have direct impact on company growth and revenue strategy

● An opportunity to mentor and be mentored by experts in multiple disciplines

What do we deliver?

Securin helps organizations to identify and remediate the most dangerous exposures, vulnerabilities, and risks in their environment. We deliver predictive and definitive intelligence and facilitate proactive remediation to help organizations stay a step ahead of attackers. By utilising our cybersecurity solutions, our clients can have a proactive and holistic view of their security posture and protect their assets from even the most advanced and dynamic attacks.

Securin has been recognized by national and international organizations for its role in accelerating innovation in offensive and proactive security. Our combination of domain expertise, cutting-edge technology, and advanced tech-enabled cybersecurity solutions has made Securin a leader in the industry.

Core Technology Stack

AWS , EKS / Kubernetes, Jenkins , Python ,Terraform ,CI/CD , AI

Key Responsibilities:

● Architect and manage the end-to-end SaaS platform infrastructure on AWS, including EKS cluster design, VPC networking, IAM, and multi-region availability.

● Build, maintain, and optimize Jenkins-based CI/CD pipelines and develop Python automation scripts for provisioning, deployments, and runbook automation.

● Define and enforce platform SLOs/SLAs; own the observability strategy across logging, metrics, and tracing.

● Manage and participate in the on-call rotation; act as escalation point for P1/P2 incidents and drive post-incident reviews.

● Drive Infrastructure-as-Code (IaC) practices with Terraform/CloudFormation and champions a culture of automation and operational excellence.

● Collaborate cross-functionally with product, security, and engineering teams to align infrastructure roadmap with business goals.

● Identify opportunities to leverage AI to automate operational and DevOps workflows.

● Design and implement AI-assisted solutions for incident triaging, root cause analysis, log analysis, and performance optimization.

● Drive the adoption of AI-powered tools for infrastructure management, deployment automation, monitoring, and troubleshooting.

● Build intelligent workflows that reduce manual effort in release management, capacity planning, and operational support.

● Integrate AI capabilities into CI/CD pipelines to improve code quality, deployment reliability, and operational efficiency.

● Collaborate with engineering teams to automate repetitive tasks and improve developer productivity.

● Define best practices and governance for the safe and effective use of AI across DevOps processes.

● Measure and report on productivity gains, operational improvements, and cost savings achieved through AI adoption.

Requirements:

● 8+ years of experience in DevOps, SRE, or cloud infrastructure engineering roles.

● Deep hands-on expertise with AWS services (EC2, EKS, RDS, S3, IAM, VPC, CloudFront, Route53, Lambda, etc).

● Strong Kubernetes experience: cluster management, Helm, autoscaling (HPA/KEDA).

● Proficiency with Jenkins for complex CI/CD pipeline design and maintenance.

● Solid Python scripting skills for automation, tooling, and infrastructure management tasks.

● Experience with Infrastructure-as-Code using Terraform and/or AWS Cloud Formation.

● Proven track record of architecting and managing end-to-end SaaS products in a cloud-native environment.

● Strong understanding of networking fundamentals, security best practices, and compliance frameworks (SOC 2, ISO 27001 a plus).

● Hands-on experience with on-call processes and incident management frameworks.

Preferred Qualifications:

● AWS certifications: Solutions Architect Professional, DevOps Engineer Professional, or equivalent.

● Familiarity with service mesh, secrets management (Vault, AWS Secrets Manager), and zero-trust security models.

● Experience with multi-tenant SaaS architectures and tenant isolation strategies.

● Knowledge of FinOps principles and AWS cost management tooling.

● Experience with database DevOps: RDS, Aurora schema migrations, and backup strategies.

Core Competencies:

● Strategic Thinking – ability to translate business goals into scalable technical architecture.

● Operational Excellence – strong bias for reliability, automation, and continuous improvement.

● Communication – ability to clearly articulate complex technical topics to non-technical stakeholders.

● Ownership Mindset – proactively identifies and resolves risks without waiting to be asked.

● Resilience Under Pressure – calm and decisive during incidents; leads by example in high-stress situations.

Why should we connect?

We are a bunch of passionate cybersecurity professionals who are building a culture of security. Today, cybersecurity is no more a luxury but a necessity with a global market value of $150 billion.

At Securin, we live by a people-first approach. We firmly believe that our employees should enjoy what they do. For our employees, we provide a hybrid work environment with competitive best-in-industry pay, while providing them with an environment to learn, thrive, and grow. Our hybrid working environment allows employees to work from the comfort of their homes or the office if they choose to. For the right candidate, this will feel like your second home.

If you are passionate about cybersecurity just as we are, we would love to connect and share ideas

About Us

We are a fast-growing startup based in Pune, India, specializing in cutting-edge Data Science and Data Engineering solutions. Our team of dedicated professionals is committed to solving complex data challenges for companies worldwide.

Our Culture We foster a vibrant startup culture that values: • Intellectual curiosity • Continuous learning • Positive work environment • Collaborative problem-solving

Role Overview

We are seeking a versatile and proactive Data Scientist to join our dynamic team. The ideal candidate will possess a blend of technical expertise in modern AI/ML technologies, strategic planning, and effective communication skills. This role demands critical thinking, applying data science and problem-solving skills to a wide variety of real-world problems, adaptability to rapidly evolving technologies, and a strong foundation in both traditional and generative AI principles.

Key Responsibilities • Deliver end-to-end data science projects by applying Machine Learning and Deep Learning fundamentals to solve complex problems • Derive actionable insights for a variety of problems, industries, and domains using statistical analysis and advanced data science techniques • Develop high-quality software solutions with Python and other programming languages. Collaborate with developers to understand and improve existing code or create new solutions • Build and deploy production-ready LLM applications using modern frameworks and best practices • Design and implement RAG (Retrieval-Augmented Generation) architectures using vector databases and embedding models • Perform prompt engineering and optimization to maximize LLM performance for specific use cases • Implement agentic AI systems and multi-agent workflows for complex automation tasks • Evaluate and benchmark LLM outputs using appropriate metrics and testing frameworks • Build sophisticated data pipelines for large-scale data processing using modern orchestration tools • Optimize database performance and create efficient SQL queries • Deploy and monitor ML models in production using MLOps practices and containerization • Practice active listening to understand project requirements and team inputs • Collaborate with clients to translate business requirements into data science solutions • Communicate complex ideas and results clearly to stakeholders through both verbal and written formats • Apply responsible AI principles and ensure ethical considerations in model development • Demonstrate punctuality and a strong sense of ownership in all tasks • Plan strategically and multitask efficiently to meet project deadlines • Employ critical thinking to break down problems and debug effectively • Take initiative and be biased towards action to drive project progress Required Skills Core Programming & ML • Strong Python programming skills with hands-on project experience • Expertise in Machine Learning and Deep Learning algorithms (Random Forests, GBMs, Neural Networks, CNNs, RNNs, Transformers, Ensemble methods) • Proficiency in TensorFlow or PyTorch, along with scikit-learn and pandas • Familiarity with modern ML techniques: Transfer Learning, Few-shot Learning, Self-supervised Learning • Experience with NLP, Computer Vision, or Time Series Analysis Generative AI & LLMs • Hands-on experience with LLM providers (OpenAI, Anthropic Claude, Google Gemini, or open-source models) • Proficiency with GenAI orchestration frameworks (LangChain, LangGraph, LlamaIndex, or DSPy) • Experience building RAG applications with vector databases (Pinecone, Weaviate, Chroma, FAISS) • Strong prompt engineering skills and understanding of prompt optimization techniques • Knowledge of fine-tuning techniques (LoRA, QLoRA) and when to apply them • Understanding of LLM evaluation metrics and benchmarking methodologies • Familiarity with agentic AI architectures and multi-agent systems MLOps & Deployment • Experience with MLOps practices and tools (MLflow, Kubeflow, Weights & Biases) • Proficiency with containerization using Docker and orchestration with Kubernetes • Experience with cloud platforms (AWS, Azure, or GCP) for ML model deployment and monitoring • Understanding of CI/CD pipelines for ML applications • Knowledge of model serving frameworks and API development (FastAPI, Flask, or Django) Data Engineering & Databases • Solid understanding of SQL, including advanced concepts like windowing functions and query optimization • Experience with data pipeline orchestration tools (Airflow, Prefect, or similar) • Familiarity with both SQL and NoSQL databases Soft Skills & Professional Attributes • Strong critical thinking and problem-solving skills • Excellent written and verbal communication abilities • Demonstrated ability to work well in a team and independently • High degree of flexibility and adaptability to rapidly evolving technologies • Understanding of AI safety principles and responsible AI practices

Nice-to-Have • Experience with big data technologies (Spark, Hadoop, Databricks) • Familiarity with BI tools and dashboard creation (Tableau, Power BI, Looker) • Knowledge of graph databases and knowledge graph construction • Experience with real-time streaming data processing • Active participation in data science competitions (Kaggle, DrivenData) • Contributions to open-source AI/ML projects or technical blog • Experience with multimodal AI models (vision-language models, audio processing) • Published research papers or conference presentations

Qualifications • Data Scientist I: 0-2 years of hands-on experience in Data Science projects • Data Scientist II: 2-5 years of hands-on experience in Data Science projects • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related technical field • Demonstrated commitment to continuous learning through courses, certifications, or self-study (especially in GenAI and modern ML techniques)

What We Offer • Competitive salary commensurate with experience • Opportunity to work on diverse, cutting-edge AI/ML projects • Collaborative and innovation-driven work environment • Rapid growth and continuous learning opportunities • Exposure to latest AI technologies and industry best practices

Link for application -  https://forms.gle/9GENVfPeXdtgi7Zj7

Role : .NET Developer Location – Gurgaon Key Responsibilities What role will you play? In this role, you will collaborate with stakeholders and analysts to define requirements, while working closely with the team on development, testing, and deployment activities. You will support production operations, engage directly with users, and help maintain system stability, using this experience as a key learning opportunity. You will also deliver high-quality platform enhancements, build strong relationships with technical and non-technical stakeholders, and act as a subject matter expert to ensure best practices and professional standards are consistently upheld. • 9–14 years of hands-on experience in C# and .NET full-stack development • Strong extensive experience in financial markets and low-latency, multithreaded systems • Solid expertise in SQL and database design and optimization • Proven experience leading small development teams • Familiarity with message-based integration, including protocols such as FIX • Actively learn and apply financial domain knowledge • for this role we are specifically looking for candidates with strong domain expertise as well. • This is a Front Office Trading Engineering role, so it’s important that the candidate understands key business concepts and nuances, such as sell-side vs buy-side, equities vs derivatives, and instruments like futures, options, and swaps. • Ability to work in an agile environment and handle end-to-end development responsibilities Required Skills & Experience • 3–10 years of professional experience in .NET development • Strong hands-on experience with C#, ASP.NET, and .NET Core • Excellent understanding of data structures, algorithms, and problem-solving techniques • Experience and strong interest in algorithm-driven or computation-intensive applications • Excellent communication skills, with the ability to bridge business language and technical implementation • Proven ability to learn quickly and work effectively in a highly collaborative environment • Strong inclination to work within the financial services domain; experience with repo products, secured funding, or lending is highly regarded

DevOps Engineer

AWS Infrastructure, CI/CD & Production Operations

Mumbai (On-site) | Full-time | 2-4 years

About the role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies. We are hiring a DevOps Engineer who will own day-to-day cloud infrastructure, deployment automation, and production operations across active customer engagements.

The mandatory requirement for this role is hands-on production experience on AWS, with infrastructure as code, container orchestration, and CI/CD pipelines owned end to end on at least one live customer workload. The role is hands-on. Expect to operate Kubernetes clusters, build CI/CD pipelines, automate environment provisioning, manage TLS and DNS, set up observability, and partner with backend and AI engineers to ship reliably. A typical week includes a Terraform refactor, a deployment pipeline build for a new service, an incident response on a production cluster, and a cost review.

Responsibilities:

• AWS infrastructure: Design and operate production infrastructure on AWS using EC2, EKS or ECS, S3, RDS, IAM, VPC, CloudFront, and Route53. Own configuration, networking, and cost.
• Infrastructure as code: Write and maintain Terraform or Pulumi modules. Drive consistency across environments and tenants through IaC rather than manual configuration.
• Kubernetes and containers: Operate production EKS clusters. Manage Helm charts, Ingress, autoscaling, secrets, and workload isolation.
• CI/CD pipelines: Build and maintain pipelines using GitHub Actions, GitLab CI, or equivalent. Include automated tests, security scans, and rollback paths.
• TLS, DNS, and CDN automation: Automate domain provisioning, TLS issuance (Let's Encrypt, cert-manager, ACM), and CDN configuration (CloudFront, Cloudflare).
• Observability and incident response: Set up monitoring, logging, and alerting using Prometheus, Grafana, ELK, Loki, or CloudWatch. Lead incident response and write postmortems.
• Secrets and security: Manage secrets through Vault, AWS Secrets Manager, or KMS. Apply least-privilege IAM and review access regularly.
• Cost monitoring: Track and optimise AWS spend across environments. Surface waste and propose remediations.
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Requirements:

• Hands-on AWS production experience (mandatory). Must have personally operated production workloads on AWS, with responsibility for IaC, deployments, and incident response on at least one live customer or internal-platform deployment. POCs and lab environments do not qualify.
• 2 to 4 years of hands-on DevOps or infrastructure experience. Candidates with slightly less experience but strong demonstrated ownership are welcome to apply.
• AWS depth. Hands-on with EC2, S3, IAM, VPC, EKS or ECS, RDS, CloudFront, and Route53. Working knowledge of CloudWatch and AWS cost tooling.
• Kubernetes in production. Hands-on operation of EKS or equivalent. Comfort with Helm, Ingress controllers, autoscaling, and resource quotas.
• Infrastructure as code. Strong with Terraform (preferred) or Pulumi. Modular code, state management, and review discipline.
• CI/CD pipelines. Production experience with GitHub Actions, GitLab CI, or equivalent. Comfort with multi-environment pipelines and release strategies.
• Scripting and automation. Strong Bash and Python (or Go) for tooling. Linux fluency at the command line.
• Observability stack. Hands-on with Prometheus, Grafana, ELK or Loki, and at least one APM tool (Datadog, New Relic, or equivalent).
• Networking, TLS, and security fundamentals. Comfortable with DNS, TLS certificate lifecycle, VPC peering, and security groups.



Nice to have: multi-tenant SaaS infrastructure experience; service mesh (Istio, Linkerd); GitOps (ArgoCD, Flux); sandboxed execution environments (Firecracker, gVisor); exposure to platform engineering or developer-platform teams.

Job Details:

• Role: Staff Engineer, ArgoCD
• Experience: 5.5-7.5 Years
• Employment Type: Full-time
• Work Mode: Gurugram (Hybrid)

Job Description

REQUIREMENTS:

• Strong hands-on experience with Kubernetes (K8s) administration, deployment, and troubleshooting
• Expertise in GitOps implementation using ArgoCD
• Strong experience with Crossplane for infrastructure provisioning and orchestration
• Hands-on experience with New Relic for monitoring, observability, and performance management
• Experience building and maintaining CI/CD pipelines and deployment automation
• Strong knowledge of Infrastructure as Code (IaC) using Terraform
• Experience working with AWS cloud services and cloud-native architectures
• Hands-on experience with Docker and containerization technologies
• Strong Linux administration and scripting skills
• Experience implementing platform reliability, security, and automation best practices
• Strong understanding of monitoring, logging, and observability frameworks

RESPONSIBILITIES:

• Manage, maintain, and optimize Kubernetes-based infrastructure and application deployments
• Implement and support GitOps workflows using ArgoCD
• Design and manage infrastructure provisioning using Crossplane
• Monitor platform performance, reliability, and user experience using New Relic
• Build, enhance, and maintain CI/CD pipelines for automated software delivery
• Collaborate with development and platform engineering teams to deliver scalable cloud-native solutions
• Implement Infrastructure as Code practices using Terraform and automation tools
• Ensure platform stability, security, scalability, and operational excellence
• Troubleshoot infrastructure, deployment, and performance-related issues
• Drive continuous improvement initiatives across DevOps processes, tooling, and automation practices
• Support cloud infrastructure management and containerized application environments on AWS
• Promote DevOps best practices, governance, and operational standards across teams

Qualifications

Bachelor’s or master’s degree in computer science, Information Technology, or a related fields