50+ Docker Jobs in India

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.

Job Description:

Required Skills

• Experience-4+ years
• Strong backend engineering fundamentals.
• Good understanding of system design concepts for scalable and reliable applications.
• Hands-on experience with at least one backend language such as Golang, Node.js, Java, Rust, Python, or similar.
• Strong understanding of REST APIs, service design, authentication, authorization, and API security.
• Good knowledge of database design, indexing, query optimisation, transactions, and data consistency.
• Experience with SQL databases such as PostgreSQL, MySQL, or similar.
• Understanding of NoSQL databases, caching systems, and when to use them.
• Experience working with Redis or similar caching technologies.
• Understanding of message queues, event-driven architecture, asynchronous processing, and background jobs.
• Ability to reason about memory management, garbage collection, concurrency, and runtime behaviour.
• Experience debugging performance issues in backend systems.
• Good understanding of high TPS systems, load testing, horizontal scaling, and bottleneck analysis.
• Familiarity with containerisation using Docker.
• Working understanding of Kubernetes-based deployments, preferably EKS.
• Understanding of CI/CD pipelines and cloud deployment practices.
• Good communication skills and ability to explain technical decisions clearly.

Good to Have Skills

• Experience with microservices architecture.
• Experience with AWS services, especially EKS, RDS, SQS, CloudWatch, ElastiCache, API Gateway, or Lambda.
• Understanding observability tools such as Prometheus, Grafana, Loki, Tempo, Open Telemetry, or similar.
• Experience with distributed tracing and production monitoring.
• Experience with event streaming platforms such as Kafka.
• Knowledge of security best practices around JWT, OAuth2, RBAC, secrets management, and secure API design.
• Experience designing systems for high availability and fault tolerance.
• Exposure to infrastructure-as-code tools such as Terraform or CloudFormation.
• Experience mentoring junior engineers or reviewing technical designs.

🚀 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

We’re looking for a hands-on builder who can thrive in a fast-paced startup environment. You’ll own features end-to-end, from designing architecture to writing clean, reusable code, testing, deploying, and iterating fast.

What you’ll do

• Build and scale web + mobile applications using Python (Django) and React Native/React.
• Design, develop, and deploy cloud-native solutions using AWS services.
• Work with both SQL and NoSQL databases (PostgreSQL, DynamoDB).
• Ensure applications are secure, scalable, and performance-optimized.
• Collaborate closely with product, design, and business teams to ship features at lightning speed.
• Take ownership of problems - from brainstorming and architecture to debugging in production.
• Bring startup energy: move fast, learn fast, and don’t be afraid to get your hands dirty.

What we’re looking for

• 1-3 years of experience in full-stack development.
• Strong experience in Python (Django).
• Proficiency in React Native/React, with solid knowledge of JavaScript.
• Experience with AWS services (serverless, EC2, S3, etc.).
• Experience with docker or kubernetes.
• Hands-on with databases: PostgreSQL, DynamoDB.
• Strong understanding of data structures, design patterns, and microservices architecture.
• Proficiency with Git and version control workflows.
• A product-first mindset, balancing code quality with speed of execution.
• Great communication skills, detail-oriented, and a true team player.
• Bonus - If you are an AI native developer and try to solve problems using AI

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

Company: BigThinkCode Technologies

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

Experience required: 3-4 years

Work location: Chennai

Joining time: Immediate – 2 weeks

Work Mode: Work from office / Hybrid

About the Role

We're looking for a skilled Node.js Developer with 3+ years of experience building scalable applications using event-driven architecture within distributed systems. The ideal candidate is comfortable working on high-performance backend services and has a strong understanding of asynchronous programming patterns. Exposure to knowledge embedding and vectorization techniques is a strong plus, especially for modern data-driven or AI-powered systems.

Key Responsibilities

• Design, develop, and maintain server-side applications using Node.js
• Build and optimize scalable, event-driven systems in distributed environments
• Implement asynchronous workflows, message queues, and pub/sub architectures
• Collaborate with cross-functional teams to define and deliver backend solutions

Required Skills

• 3+ years of hands-on experience with Node.js
• Strong understanding of event-driven architecture and non-blocking I/O
• Experience working with distributed systems and microservices architecture
• Proficiency in RESTful API design and implementation
• Experience with databases such as MongoDB, PostgreSQL, or MySQL
• Experience with containerization tools like Docker and orchestration tools like Kubernetes

Good to Have

• Experience with knowledge embedding and vectorization techniques
• Familiarity with vector databases (e.g., Pinecone, Weaviate, FAISS)
• Understanding of cloud platforms (AWS, Azure, or GCP)

Why Join Us:

• Collaborative work environment.
• Exposure to modern tools and scalable application architectures.
• Medical cover for employee and eligible dependents.
• Tax beneficial salary structure.
• Comprehensive leave policy
• Competency development training programs.

The problem you are solving

250 million students sit exams in India every year. Every answer sheet is graded by a tired human with a red pen, in a room with no AC, in 45-degree heat, under political pressure. The variance in marks between two evaluators on the same paper can be 15-20%. That is not education. That is luck. We are building the AI that changes this — reading handwriting, understanding context, scoring semantically, flagging uncertainty, matching faculty-level accuracy. We need the engineer who will make this work at scale.

What you will build

HTR

Handwriting recognition on smudged, mixed-script answer sheets — not clean printed text

Layout

Detect question boundaries, diagrams, tables, margin notes across 20+ page booklets

NLP

Semantic scoring — does this answer mean the right thing, not just contain the right words

Confidence

Know when the model is unsure and route to human review with explainability

Scale

Process millions of pages during exam seasons — async pipeline on AWS SQS + GPU workers

Must have built something hard — any of these

Document OCR / HTR pipeline

Fine-tuned LLM for domain scoring

Layout / document understanding model

Semantic similarity / NLI at scale

GPU inference pipeline (TensorRT/ONNX)

Multi-language NLP (Indic languages +)

Competition — 3 rounds

Round 1

Given 50 real (anonymized) answer sheets: build a pipeline that extracts, structures and scores them. Accuracy vs faculty marks is the metric.

Round 2

48-hour sprint: improve your Round 1 model given live feedback on failure cases. Confidence calibration included.

Round 3

Live oral defense with Sachin and Hemant. Walk us through every architectural decision. We will break it.

The problem you are solving

50,000 students. Hundreds of classrooms. Attendance marked on paper by a faculty member who has 90 seconds to call roll before lecture starts. It is inaccurate, gameable, and meaningless as data. We are replacing it with existing CCTV infrastructure — no new hardware, no wristbands, no apps. Just cameras that already exist, a model that recognises faces at scale in real-time, and a system smart enough to also tell you which rooms are overcrowded, which are empty, which have lights burning with nobody inside, and which need security attention. Campus intelligence, from cameras that are already there.

What you will build

Face recog.

Identify 50,000 enrolled students from CCTV feed — low-res, partial occlusion, varying angles

Attendance

Real-time auto-marking at scale, synced to the student ERP — no manual input

Crowd detects

Flag overcrowded rooms vs capacity threshold, real-time alerts to admin

Empty rooms

Detect booked-but-empty rooms and free them up automatically

Utilities

Lights on in empty room, fan running, AC on — flag for facilities team with camera snapshot

Edge + cloud

Low-latency processing at edge where needed, aggregation and analytics on cloud

Must have built something hard — any of these

Face recognition at 10,000+ identities

Real-time video analytics pipeline

YOLO / object detection production deploys

Multi-camera synchronization system

Edge inference (Jetson / Open VINO / ONNX)

Crowd / occupancy detection system

Competition — 3 rounds

Round 1

Given a set of low-res CCTV stills from a real campus: identify occupied vs empty rooms, count heads, detect lights-on-no-occupancy. Submit working code.

Round 2

48-hour sprint: extend your solution to handle a 10-camera simulated feed simultaneously. Latency under 2 seconds per frame is the bar.

Round 3

Live oral defense with Sachin and Hemant. Scale it to 500 cameras. Where does it break? How do you fix it?

Job Title : Mobile DevOps Engineer

Experience : 5+ Years

Location : Nashik / Pune (Remote – Initial 1 Week Onsite in Nashik)

Job Summary :

We are looking for a Mobile DevOps Engineer with expertise in building and maintaining CI/CD pipelines for iOS and Android applications. The ideal candidate will have hands-on experience with mobile build automation, release management, Azure DevOps, and cloud-based DevOps practices to enable faster, secure, and reliable mobile application delivery.

Mandatory Skills :

Azure DevOps, Mobile CI/CD (iOS & Android), Fastlane/Bitrise/Codemagic, GitHub, Xcode, Gradle, App Store & Google Play release automation, YAML Pipelines, GitHub Actions, Docker, Shell/Python scripting, Mobile DevSecOps, Firebase Crashlytics/Sentry, Agile/Scrum.

Key Responsibilities :

• Design, implement, and maintain CI/CD pipelines for iOS and Android applications.
• Automate build, testing, code signing, and deployment processes.
• Manage app releases on Google Play Store and Apple App Store.
• Configure and maintain Azure DevOps pipelines, GitHub workflows, and release automation.
• Integrate automated testing, security scanning, and quality gates into CI/CD pipelines.
• Monitor build performance, troubleshoot pipeline issues, and optimize release processes.
• Collaborate with Mobile, QA, Backend, and Product teams to streamline delivery.
• Maintain DevOps documentation, release procedures, and deployment best practices.
• Explore AI-powered development tools to improve automation and developer productivity.

Required Skills :

• 5+ years of experience in DevOps, Infrastructure, or Software Engineering.
• 2+ years of hands-on experience with Mobile CI/CD (iOS & Android).
• Strong experience with Azure DevOps, GitHub, Fastlane, Bitrise, Codemagic, or similar tools.
• Solid knowledge of Xcode, Gradle, code signing, provisioning profiles, and keystores.
• Experience with Google Play Store and Apple App Store release automation.
• Familiarity with YAML pipelines, GitHub Actions, Shell/Python scripting, and Docker.
• Knowledge of mobile testing frameworks, DevSecOps practices, and monitoring tools such as Firebase Crashlytics, Sentry, or Datadog.
• Understanding of Agile/Scrum methodologies and strong collaboration skills.

Preferred Skills :

• Experience with Flutter, React Native, or native mobile development.
• Exposure to Azure Cloud services.
• Familiarity with AI-assisted development tools and automation.

Job Title: Associate AI/ML Engineer

Location: Gurugram, Haryana

Employment Type: Full-Time

About Aaizel Tech

Aaizel Tech is a pioneering tech startup at the intersection of cybersecurity, AI, geospatial solutions, and more. We drive innovation by delivering transformative technology solutions across industries. As a growing startup, we are looking for passionate and versatile professionals eager to work on cutting-edge projects in a dynamic environment.

Role Overview

As a Associate AI/ML Engineer at Aaizel Tech, you will lead the design, development, and deployment of advanced Machine Learning models and AI solutions. You will work on projects ranging from predictive analytics and NLP to computer vision and anomaly detection. You will also mentor a team of AI/ML professionals, collaborate with cross-functional teams, and drive innovation by integrating state-of-the-art research with scalable production systems.

Key Responsibilities

1. Model Development & Optimization

Design & Implementation:

• Architect and develop end-to-end ML solutions for applications such as predictive analytics, anomaly detection, computer vision, and NLP.
• Utilize advanced techniques including deep learning (CNNs, RNNs), reinforcement learning, and generative models (GANs) to address complex challenges.

Optimization:

• Fine-tune model parameters using techniques such as hyperparameter tuning (Grid Search, Bayesian Optimization, Neural Architecture Search).
• Optimize models for both accuracy and inference speed to meet real-time processing requirements.

2. Advanced Data Engineering & Integration

Data Pipeline Development:

• Build robust ETL pipelines using libraries like Pandas, NumPy, and PySpark to process large-scale datasets from satellite imagery, IoT sensors, and real-time streams.
• Integrate data from diverse sources (APIs, databases, big data platforms like Hadoop and Apache Kafka) to support real-time analytics.

Data Quality & Preprocessing:

• Implement data cleansing, feature engineering, and transformation pipelines to ensure high-quality inputs for ML models.

3. Research & Innovation

Algorithm Research:

• Conduct research on state-of-the-art ML techniques including Transfer Learning, Transformer models, and AutoML to enhance model performance.
• Innovate new algorithms for specialized tasks such as geospatial analysis, environmental modeling, or cybersecurity threat detection.

Prototyping & Experimentation:

• Develop proof-of-concept models and prototypes to validate new approaches before production deployment.

4. Deployment, MLOps & Performance Monitoring

Model Deployment:

• Deploy models using containerization (Docker) and orchestration tools (Kubernetes) to ensure scalable and efficient production environments.
• Work with cloud platforms (AWS, Azure, GCP) and model serving solutions (TensorFlow Serving, ONNX, TorchServe) for high-throughput inference.

MLOps & Lifecycle Management:

• Implement CI/CD pipelines for ML models, ensuring seamless updates and versioning.
• Develop monitoring dashboards (using Prometheus, Grafana) to track model performance and trigger retraining based on real-time feedback.

5. Collaboration & Leadership

Cross-Functional Teamwork:

• Collaborate closely with data engineers, software developers, domain experts, and product managers to integrate AI solutions into end-to-end products.

Mentorship & Code Quality:

• Provide technical leadership and mentorship to junior AI/ML engineers, ensuring adherence to coding standards and best practices.
• Participate in code reviews, maintain detailed documentation, and foster a culture of continuous learning.

Recommended Technology Stack

Backend Framework:

• Python (Django/FastAPI): Ideal for API integration, leveraging Python’s rich AI/ML ecosystem.

AI/ML Frameworks:

• PyTorch + Hugging Face Transformers + scikit-learn: For flexibility in research, multilingual NLP tasks, and classical ML pipelines.

Data Engineering:

• Apache Kafka + Apache Spark + Apache NiFi: To handle both real-time data streaming and batch processing.

Database & Storage:

• PostgreSQL with TimescaleDB extension: For structured and time-series data storage.

DevOps & Monitoring:

• Docker, Kubernetes, GitLab CI/CD, Prometheus/Grafana: For containerized deployments, continuous integration, and comprehensive monitoring.

Media Processing:

• OpenCV, FFmpeg, Tesseract OCR, Wav2Vec2: To support image, video, and speech-to-text processing where needed.

Required Skills & Qualifications

Technical Expertise:

• Experience:
• 5+ years in Machine Learning, AI research, or a related field with a proven track record of delivering production-level AI solutions.
• Programming & Frameworks:
• Expertise in Python and hands-on experience with frameworks like PyTorch, TensorFlow, and scikit-learn.
• Experience with Hugging Face Transformers for NLP applications.
• Data Engineering:
• Proficiency in building data pipelines using Pandas, NumPy, PySpark, and integrating data from diverse sources.
• Familiarity with big data platforms and real-time data processing frameworks.
• Model Deployment & MLOps:
• Hands-on experience with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for ML models.
• Experience with cloud deployment and model serving solutions.
• Research & Innovation:
• Demonstrated ability to apply advanced ML techniques (deep learning, transfer learning, reinforcement learning) to solve real-world problems.
• Testing & Optimization:
• Strong background in model evaluation, hyperparameter tuning, and performance optimization.

Soft Skills:

• Exceptional problem-solving and analytical abilities.
• Strong communication skills, with the ability to present complex technical concepts to diverse stakeholders.
• Leadership and mentoring experience, with a collaborative approach to working in cross-functional teams.
• Ability to thrive in a fast-paced, dynamic environment and drive continuous innovation.

Educational Background:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field from a reputed institution.

What We Offer

• Innovative Projects: Engage in cutting-edge AI/ML projects that influence product strategy and technological innovation.
• Professional Growth: Opportunities for continuous learning, mentorship, and career advancement.
• Collaborative Culture: Work within a diverse team of experts passionate about pushing the boundaries of technology.
• Impactful Work: Play a key role in shaping AI-driven solutions and driving real-world impact.

Apply: https://processity.ai/careers/fullstack-ai-engineer

BigMantra is a Vertical Autonomous AI Agent Builder — we build AI companies that go a mile deep into specific industries. Our products include Mantra Spaces (AI-powered UK HMO property management) and Verity Law (AI-powered legal conveyancing). Our team is small, our stack is modern, and your code ships to production the same week you write it.

We're looking for a Fullstack AI Applied Engineer who can build full applications end-to-end and wire AI agents into production systems that real users depend on.

WHAT YOU'LL DO

• Build and ship full-stack web applications using React / Next.js and Python / Node.js

• Design and implement AI agent workflows using LangChain, LangGraph, Claude Agent SDK, Agno, or similar

• Integrate agents with real-world APIs — Salesforce, Google Workspace, WhatsApp Business, email providers

• Build and optimize database layers — production SQL, schema design, RAG pipelines

• Own deployment and infrastructure — Docker services, CI/CD pipelines on AWS or Azure

• Write tests that matter — E2E, load tests, performance benchmarks

• Collaborate directly with the founding team on architecture and product direction

MUST HAVE

• 3+ years of professional software engineering experience

• Strong JavaScript / TypeScript — React, Next.js, Node.js in production

• Strong Python — backends, agent systems, data pipelines

• Hands-on experience with at least one AI agent framework (LangChain, LangGraph, Claude Agent SDK, Agno, or equivalent)

• Docker services for containerization and deployment

• CI/CD pipelines — GitHub Actions, GitLab CI, or similar

• Deployment experience on AWS or Azure

• Solid SQL and database skills — schema design, query optimization

GOOD TO HAVE

• Experience with autonomous agents — MCP (Model Context Protocol), skills, plugins, tool-use

• Memory and context management for long-running agents

• Prompt engineering and optimization

COMPENSATION & BENEFITS

• ₹30L – 50L per annum (based on experience)

• Equity / ESOPs — early-stage participation

• Remote-friendly — Coimbatore office available

• Learning budget — courses, conferences, AI tooling subscriptions

• Flexible hours — output over seat time

Job Description

We are looking for a hands-on Technical Lead Engineer (Full Stack) to spearhead the design, development, and delivery of our scalable web platforms and core application ecosystems. In this role, you will bridge the gap between front-end experiences and robust back-end systems. You will lead an agile development team through technical architecture, feature implementation, integration, testing, deployment, and production support.

The ideal candidate has deep technical expertise in both frontend and backend modern frameworks, a passion for system design, and practical experience building secure, scalable, and high-performance distributed web applications.

Key Responsibilities

• Technical Leadership: Lead end-to-end full-stack software development, architectural design, and system evolution.
• Backend Architecture: Design scalable, fault-tolerant backend architectures, optimizing high-volume data ingestion pipelines and processing engines.
• Frontend Excellence: Direct the development of highly responsive, intuitive, and modular user interfaces that ensure a seamless user experience.
• API & Integrations: Architect secure RESTful APIs and integrate external enterprise platforms, third-party microservices, and identity providers.
• Team Mentorship: Mentor developers, run strict code reviews, define engineering best practices, and guide sprint-level execution.
• Data & Messaging: Maintain and optimize relational, NoSQL, and time-series databases alongside message queues for real-time application events.
• Production Ownership: Own technical troubleshooting for live production bottlenecks, system latency issues, and deployment bugs.
• Documentation: Create clean technical documentation, structural architecture diagrams, and system deployment guidelines.

Required Skills

• Experience: 6+ years of software development experience with at least 2+ years leading engineering teams or owning technical delivery.
• Backend Core: Advanced hands-on experience with Java, Spring Boot, Spring Cloud, multithreading, and REST API development.
• Frontend Core: Mastery of modern JavaScript/TypeScript frameworks (such as React, Angular, or Vue.js), HTML5, and responsive CSS architectures.
• Data Platforms: Proficient with relational databases (MySQL, PostgreSQL) and NoSQL/Caching systems (Redis, MongoDB).
• Messaging Systems: Experience implementing asynchronous workflows using message brokers like Kafka or RabbitMQ.
• Design Patterns: Strong grasp of microservices patterns, distributed system caching, load balancing, and failover mechanisms.

Preferred / Nice-to-Have Skills

• Experience deploying workloads to Cloud environments (AWS, Azure, or GCP).
• Familiarity with containerization tools like Docker and orchestration via Kubernetes.
• Hands-on experience setting up continuous integration and automated deployment pipelines (CI/CD).
• Exposure to system observability tools (Prometheus, Grafana, ELK stack).

Education Requirement

• Bachelor's degree in Computer Science, IT, Electronics, Electrical Engineering, or a related field. Candidates with equivalent exceptional hands-on full-stack engineering experience will be highly considered regardless of formal degree background.

Tech Lead

Full Stack, Architecture & Client Delivery

📍 Mumbai (On-site) | Full-time | 5-6 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 Tech Lead who will own the technical direction of full stack engagements, lead a small pod of engineers, and represent Unico Connect directly in front of customers.

The mandatory requirement for this role is hands-on production experience as a senior or lead engineer building full stack web applications with React on the frontend and either Node.js or Python on the backend.

The role is hands-on.

Expect to spend meaningful time on architecture, complex implementation, and code reviews, while also driving delivery, mentoring a pod of 3 to 6 engineers, running client conversations, and contributing to solutioning on new opportunities.

A typical week includes a design review on a new module, a working session with a client product owner, paired implementation on a complex flow, and pre-sales input on an active opportunity.

Responsibilities:

Solutioning and Architecture

Own end-to-end architecture for client engagements: system design, API contracts, data models, integrations, deployment topology, and trade-off analysis.

Document and defend decisions in writing and in client reviews.

Hands-on Full Stack Delivery

Lead by example on complex modules, performance-critical paths, and high-risk areas of the system using React (with Next.js where relevant) and Node.js (Express, NestJS) or Python (FastAPI, Django, Flask).

Database Design and Performance

Drive PostgreSQL schema design, indexing strategy, query optimisation, migrations, and capacity planning.

Set the standard for data modelling across the pod.

Cloud and Infrastructure

Set up and operate production workloads on AWS, GCP, or Azure.

Make and own decisions on compute, storage, networking, CI/CD pipelines, observability, and cost.

Code Quality and Engineering Standards

Run code reviews, define engineering conventions, and raise the quality bar across the team.

Set the standard for testing, linting, branching, release management, and incident response.

Team Leadership and Mentorship

Lead, mentor, and grow a pod of 3 to 6 engineers.

Plan sprints, unblock the team, run retros, and own delivery commitments.

Client Engagement

Act as the primary technical point of contact for the client.

Run technical discussions, present trade-offs, manage scope and risks, and keep stakeholders informed in writing.

Pre-Sales and Solutioning

Partner with sales and account leadership on new opportunities, including discovery calls, effort estimation, architecture diagrams, and solution write-ups.

AI-Assisted Development

Use Claude, Cursor, and similar tools day to day.

Set the standard for the team on prompts, patterns, AI-assisted code review, and where these tools are and are not appropriate.

AI Feature Delivery

Where an engagement calls for it, design and ship LLM-based features into production, including prompt design, retrieval pipelines, evaluation, observability, and guardrails.

Requirements:

Hands-on Full Stack Production Experience as a Senior or Lead Engineer (Mandatory)

Must have personally built and shipped production web applications using React on the frontend and either Node.js or Python on the backend.

POCs, internal tools, and coursework do not qualify.

5 to 6 Years of Professional Software Engineering Experience

Including at least 1 to 2 years in a tech lead, team lead, or senior engineering role with direct responsibility for technical decisions and team output.

Hands-on Cloud Experience on at Least One of AWS, GCP, or Azure

Including deploying and operating production workloads.

Comfort with at least three of: EC2 or equivalent compute, S3 or equivalent object storage, Lambda or serverless functions, RDS or managed databases, CloudFront or equivalent CDN, IAM, VPC.

Strong Proficiency in JavaScript and TypeScript

With React and Next.js (SSR, SSG, app router) on the frontend, and either Node.js (Express, NestJS) or Python (FastAPI, Django, Flask) on the backend.

API design experience across REST and GraphQL.

Willingness and demonstrated ability to pick up the other backend stack as engagements demand.

Production Experience with Docker, Git-Based Workflows, and CI/CD Pipelines

(GitHub Actions, GitLab CI, CircleCI, or equivalent).

Strong PostgreSQL Skills

Schema design, normalisation, indexing, query performance, migrations, and at least one production system where you owned the data model end-to-end.

Caching and Event-Driven Architecture

Hands-on with Redis (or equivalent) for caching and session management, and message queues or event-driven patterns (RabbitMQ, SQS, Kafka, or NATS) for asynchronous workflows.

AI and LLM Feature Delivery in Production

Experience designing and shipping at least one AI feature to production, covering prompt design, retrieval-augmented generation (RAG), embeddings, evaluation, observability, and guardrails.

POCs and demos do not qualify.

System Design Depth and End-to-End Ownership

Able to take an ambiguous problem, break it into components, evaluate alternatives, produce an architecture that holds up under review and load, plan execution, and ship to production with limited supervision.

Excellent Written and Spoken English

Experience working directly with international clients.

Confident, clear, and firm in stakeholder communication.

Comfortable presenting to senior stakeholders, pushing back where needed, and managing expectations across time zones.

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

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.
• 
  

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.

Contract Job: DevOps / Azure DevOps

Contract Term: Max 3-6 months

Looking For Immediate joiners only

Remote Opportunity

• CI/CD, deployment, environment management, and release support
• This can be a shared capability/position as well

About NonStop io Technologies:

NonStop io Technologies is a value-driven company with a strong focus on process-oriented software engineering. We specialize in Product Development and have a decade's worth of experience in building web and mobile applications across various domains. NonStop io Technologies follows core principles that guide its operations and believes in staying invested in a product's vision for the long term. We are a small but proud group of individuals who believe in the 'givers gain' philosophy and strive to provide value in order to seek value. We are committed to and specialize in building cutting-edge technology products and serving as trusted technology partners for startups and enterprises. We pride ourselves on fostering innovation, learning, and community engagement. Join us to work on impactful projects in a collaborative and vibrant environment.

Brief Description:

NonStop io is seeking a proficient React.js developer to join our front-end development team. In this position, you’ll be mainly crafting and integrating UI components through React.js methodologies and workflows like Mobx and Redux.

Responsibilities:

● Developing and implementing UI components using React.js

● Collaborating with cross-functional teams to design and ship new features

● Building reusable components and front-end libraries for future use

● Translating designs and wireframes into high-quality code

● Optimizing components for maximum performance across various web browsers

● Troubleshooting and debugging issues to ensure smooth user experiences

● Participating in code reviews to maintain code quality and consistency

● Improvement and optimization of existing codebase

● Keeping up with industry trends

● Identifying issues with technologies and architecture and then implementing solutions

● Assist with ticket creation, refinement, and estimation

● Participate in sprint planning and ticket distribution for frontend team

Qualifications & Skills:

● Proficiency in React.js and its core principles

● Strong JavaScript, TypeScript, HTML5, and CSS3 skills

● Experience with popular React.js state management libraries and approaches (such as Mobx, Redux, and Context API)

● Familiarity with RESTful APIs and integration

● Knowledge of modern authorization mechanisms, such as JSON Web Tokens

● Understanding of front-end build tools and pipelines

● Excellent problem-solving and communication skills

● A strong attention to detail, and a passion for delivering high-quality code

● Expertise in designing scalable and efficient front-end architecture

● Adaptability to changing project requirements and priorities

● Experience with version control systems, particularly Git

● Experience working in Scrum and familiarity with Atlassian (Jira, Confluence, Bitbucket)

● Proven experience in leading teams

● Experience with diverse applications and architectural patterns

● A degree in computer science, software engineering, or a related field

● Strong understanding of object-oriented programming principles and design patterns

● Familiarity with automated testing frameworks and methodologies

● Excellent problem-solving skills and attention to detail

● Strong communication skills and ability to work effectively in a collaborative team environment

Job Description:

Job Description: DevOps Engineer

Experience-3+yrs

As a DevOps Engineer, you will be responsible for designing, implementing, and maintaining the infrastructure that supports our platform and solutions. You will work closely and collaborate with various development and operations teams to ensure seamless integration and deployment of our solutions.

Responsibilities:

• Design, implement, and manage scalable and reliable IoT infrastructure on Raspberry Pi OS, various backend services using Java and AI stack Automate deployment, monitoring, and management of IoT applications.
• Collaborate with development teams to ensure continuous integration and continuous deployment (CI/CD) pipelines are efficient and effective. Manage various AWS services such as EC2, S3, Redis, RDS, Lambda, and VPC, Cognito etc.,
• Manage various Cloud infrastructure using both Kubernetes(k8) and AWS stacks for both lower and production environments Implement security best practices to protect both platform and IoT data and infrastructures.
• Develop and maintain infrastructure as code (IaC) using tools like Terraform, Ansible, or CloudFormation. Troubleshoot and resolve infrastructure-related issues along with operations and development teams
• Monitor system performance, identify issues, and implement solutions to ensure high availability and reliability. Plan and provision on-demand and stable various Cloud infrastructures in AWS and other Clouds with guided planning, scoping, costing and visibility to whole platform infrastructures with cost optimizations and utilization efficiency
• Stay up-to-date with the latest industry trends and technologies DevOps Familiarity with Dev SecOps & ML-Ops, Git-Ops practices

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related field. Strong knowledge of cloud platforms (AWS, Azure, GCP) and containerization technologies using Docker, Kubernetes etc.,
• Experience with CI/CD tools such as Jenkins, GitLab CI, or Circle CI. Proficiency in scripting languages (Python, Bash, Shell etc.).
• Good understanding and hands-on with Networking, security, and system administration in AWS environment will be ideal Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.

Appiness is a Bengaluru-based technology and product engineering company. We work with enterprises and high growth startups across the globe, building digital products that scale. We build enterprise AI, agentic and conversational AI, and cloud-native platforms across web, mobile, and cloud. We invest deeply in modern tech, with a strong bias for clean architecture, automation, and engineering craft across everything we build. With 50+ international design awards and recognition among India's fastest-growing companies, we're proud of the bar we set on both technology and experience. We love what we build, and we have fun building it.

What you'll do

• Design, provision, and manage AWS infrastructure across dev, staging, and production using Terraform modules and remote state.
• Build and maintain CI/CD pipelines for fast, reliable, repeatable deployments across multiple services.
• Containerize applications with Docker and orchestrate workloads on ECS or Kubernetes with sensible scaling and rollout strategies.
• Set up monitoring, alerting, and centralized logging so issues are caught and triaged before customers feel them.
• Own cloud security end to end: IAM hygiene, secrets management, network segmentation, encryption in transit and at rest, and patching across client accounts.
• Harden infrastructure against common attack surfaces, run vulnerability scans on containers and dependencies, and stay aligned with industry security standards.
• Partner with engineering teams to streamline release cycles, reduce lead time, and remove friction from day-to-day workflows.
• Document architecture, runbooks, and post-incident learnings so the platform and the team scale together.

What we're looking for

• 3+ years of hands-on DevOps or Cloud Engineering experience in production environments.
• Strong AWS fundamentals: VPC, EC2, ECS/EKS, RDS, S3, IAM, CloudWatch, Route 53, ALB/NLB.
• Production experience with Terraform, including modules, remote state, drift management, and multi-environment patterns.
• Comfort with Docker, container registries (ECR), and image security and patching practices.
• CI/CD experience with Jenkins or GitHub Actions, including secret handling and approval gates.
• Solid grasp of cloud security: IAM, secrets management, network policies, TLS, and least- privilege design.
• Exposure to vulnerability scanning, container hardening, and security best practices in CI/CD pipelines.
• Scripting in Python or Bash for automation, glue, and small internal tools.
• Solid Linux system administration and networking fundamentals.

Senior Xano Developer

Visual Backend Development, APIs & AI-Assisted Build

📍 Mumbai (On-site) | Full-time | 3-5 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 Xano Developer who will build backend systems and APIs for our customer engagements on Xano, the visual backend development platform.

The mandatory requirement for this role is hands-on production backend engineering experience, including PostgreSQL data modelling and REST API design, in either a Node.js or Python environment.

Prior production work on Xano is strongly preferred.

The role is hands-on and customer-facing. You will own backend delivery across engagements: designing data models, building API flows in Xano, integrating third-party services, and partnering with frontend, mobile, and AI engineers on contracts and behaviour.

The work spans all three Xano build modes: no-code function stacks, custom code through Xano’s scripting and code blocks, and Xano’s AI assistance and agentic features.

A typical week includes a data model review for a new engagement, building a complex API flow in Xano, integrating a third-party webhook, and a customer working session on a new module.

Responsibilities:

Backend Delivery on Xano

Own end-to-end backend implementation on Xano: database schema, API endpoints, function stacks, background tasks, and integrations.

Ship production-ready work that meets customer requirements and engineering quality standards.

Build Across All Three Xano Modes

Use Xano’s no-code function stacks for standard CRUD and business logic.

Drop into custom code (JavaScript, Python through code blocks, expressions) where visual flows would be unwieldy.

Use Xano’s AI assistance and agentic features to accelerate routine build work.

Database Design on PostgreSQL

Own data model decisions for each engagement: table design, relationships, indexes, addons, and query performance.

Make schema choices that hold up as product usage grows and that map cleanly to the API contracts the client needs.

API Design and Integration

Design clean REST API contracts that the frontend, mobile, and third-party consumers can rely on.

Cover authentication, input validation, pagination, error handling, and rate limiting.

Integrate external services (payment gateways, messaging, storage, AI providers) through Xano’s connectors and custom requests.

Product Thinking and Solutioning

Translate fuzzy product asks from customers into concrete backend solutions.

Ask the right questions about edge cases, data lifecycle, multi-tenancy, and access control before building.

Push back on requirements that will cause pain later.

Customer Communication

Work directly with customers in discovery, design reviews, demos, and weekly working sessions.

Explain trade-offs in plain language, present options with clear recommendations, and write tight technical updates.

AI-Assisted Backend Development

Use Xano’s built-in AI features as well as external AI tools (Claude, Cursor, and similar) day to day for schema drafts, function stack scaffolding, query writing, integration setup, and review.

Develop strong instincts for when AI output is usable as-is and when it must be reworked.

Quality, Testing, and Reliability

Test the flows you ship.

Set up sensible error handling, logging, and alerts for the backend services you own.

Participate in incident response when something breaks in production.

Documentation and Handover

Document data models, API contracts, and non-obvious decisions inside Xano and in shared docs so the rest of the team and the customer can pick up the work without you in the room.

Continuous Learning

Track changes to the Xano platform, including new features, performance improvements, and AI capabilities.

Apply them to active engagements where they reduce build effort or improve product outcomes.

Requirements:

Hands-on Production Backend Engineering Experience (Mandatory)

Must have personally shipped backend systems to production for real users, with ownership of API design and data modelling.

POCs, coursework, and internal-only tools do not qualify.

3 to 5 Years of Professional Backend Engineering Experience

In either a Node.js or Python environment.

Candidates with slightly less time but strong demonstrated ownership are welcome to apply.

Strong PostgreSQL Skills

Schema design, indexing, query writing, and migrations on at least one production system.

Able to reason about query performance and design data models that hold up under realistic product usage.

REST API Design and Integration Depth

Comfort designing API contracts that are clean, predictable, and easy for frontend, mobile, and third-party consumers to work with.

Experience integrating external services such as payment gateways, messaging providers, storage, and AI APIs.

Familiarity with at Least One Node.js or Python Backend Stack

Such as Express, NestJS, Fastify, FastAPI, Django, or Flask.

Comfort reading and writing application code outside of visual environments when the situation calls for it.

Product Thinking and Solutioning

Ability to take a fuzzy product brief, ask the right questions, and propose a backend design that is fit for purpose.

Strong instincts for what to build first, what to defer, and what not to build.

Strong Written and Spoken English Communication

Confident in customer working sessions and design reviews.

Comfortable writing precise technical documentation and explaining trade-offs to non-engineering stakeholders.

Cloud and Deployment Fundamentals

Working knowledge of at least one of AWS, GCP, or Azure: deploying services, reading logs, managing environments, and basic operational tasks.

Familiarity with Docker is a plus.

Bachelor’s Degree

Bachelor’s degree in Computer Science, Information Technology, or a related engineering discipline.

Exceptional candidates with demonstrable production experience and strong portfolios may be considered without a formal degree.

Nice to Have

• Prior production experience on Xano, Bubble, Retool, or comparable visual or low-code backend platforms
• Full stack experience with React, Next.js, React Native, or Flutter
• Experience integrating LLM APIs (OpenAI, Anthropic, Google) into backend workflows
• Multi-tenant SaaS product experience
• Prior agency, consulting, or product-engineering experience

About Us

CLOUDSUFI, a Google Cloud Premier Partner, is a global leading provider of data-driven digital transformation across cloud-based enterprises. With a global presence and focus on Software & Platforms, Life sciences and Healthcare, Retail, CPG, financial services and supply chain, CLOUDSUFI is positioned to meet customers where they are in their data monetization journey.

Hybrid - 2 days in a week from Noida office

Key Responsibilities

• Design, develop, and maintain robust and scalable big data solutions
• Implement and manage CI/CD pipelines to automate the build, test, and deployment of data applications.
• Write high-quality, maintainable, and efficient code in Java.
• Create and manage build configurations using tools like Maven, Gradle, or Ant.
• Utilize Git for version control and to manage code repositories.
• Develop automation scripts using Bash and Python.
• Perform in-depth logging and debugging to identify and resolve issues in complex data systems.
• Develop and execute comprehensive test scripts to ensure the quality and reliability of data pipelines.

Requirement:

• Cloud Computing: Practical knowledge of GCP services, including VMs, GCS, and Dataproc or similar cloud data services.
• Programming: Proven proficiency in Java development.
• Build Tools: Solid experience with build automation tools like Maven, Gradle, or Ant.
• Version Control: Proficient in using Git.
• Big Data: Strong hands-on experience with the Hadoop ecosystem and Apache Spark.
• IDE: Experience with IntelliJ IDEA or similar development environments.
• CI/CD: A strong understanding of how CI/CD pipelines work and experience with relevant tools (e.g., Jenkins, GitLab CI).
• Scripting: Proficiency in Bash and Python.
• Operating Systems: In-depth knowledge of Linux distributions (Debian, Ubuntu, Rocky).
• Core Competencies:
• Excellent logging and debugging skills.
• Experience in writing test scripts and a commitment to software quality.
• Familiarity with the process of CVE resolutions.

Behavioural competencies required:

• Must have worked with US/Europe based clients in onsite/offshore delivery model
• Should have very good verbal and written communication, technical articulation, listening and presentation skills
• Should have proven analytical and problem solving skills
• Should have demonstrated effective task prioritization, time management and internal/external stakeholder management skills
• Should be a quick learner and team player
• Should have experience of working under stringent deadlines in a Matrix organization structure
• Should have demonstrated appreciable Organizational Citizenship Behavior (OCB) in past organizations

Senior MLOps Engineer

LLM Operations, Observability & Eval Infrastructure

📍 Mumbai (On-site) | Full-time | 5-7 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 MLOps Engineer for a dedicated client engagement focused on building an AI-powered application builder platform. The platform consumes LLMs at scale through provider APIs.

This role owns the operational discipline around production LLM consumption - increasingly called LLMOps - covering observability, evaluation infrastructure, model lifecycle, cost operations, prompt deployment, and agent run reliability.

The mandatory requirement is hands-on production experience operating LLM-backed systems, with a strong DevOps or SRE foundation. This is not a model training or ML science role.

The work is making the system around the AI engineer's designs observable, controlled, reliable, and economically accountable. You will pair daily with the Senior AI Engineer, who designs prompts, evals, and agent behaviour - you operationalise those systems for production.

A typical week includes a tracing audit on a degraded agent run, an eval pipeline build for a new model release, a cost attribution review, and a staged prompt rollout.

Responsibilities:

Observability and Tracing

Build and own end-to-end tracing for agent runs: every prompt, response, tool call, token count, latency, and cost, linked to user session and project.

Stand up and operate LLM observability tooling (Langfuse, LangSmith, Braintrust, or Arize Phoenix).

Make debugging a single bad agent run among thousands a routine workflow through searchable traces, failure taxonomies, and dashboards segmented by task type.

Evaluation Infrastructure as a Production System

Operationalise the eval suite designed by the Senior AI Engineer: automated execution in CI on every prompt or model change, with results stored and trended over time.

Implement regression gates that block quality-degrading changes from shipping.

Build production sampling to continuously score a sample of real agent runs and catch quality drift that offline evals miss.

Model Lifecycle Management

Pin model versions, never "latest".

Own the upgrade process: run the eval suite against new model releases and manage eval-gated migrations.

Maintain fallback chains across providers for graceful degradation or queueing during outages.

Track provider deprecation schedules and plan migrations ahead of forced cutoffs.

Cost Operations

Implement per-user and per-task cost attribution - token spend is the platform's largest variable cost and requires the same rigour as cloud cost management.

Set up budget alerts and anomaly detection so a single user or bug cannot burn significant spend overnight.

Monitor prompt cache hit rates and quantify savings.

Manage capacity planning around provider rate limits, including quota negotiation and throughput tiering.

Prompt and Configuration Deployment

Treat prompts as production artifacts: version control for prompts and agent configurations, staged rollout infrastructure (deploy a prompt change to a percentage of traffic before full rollout), A/B testing infrastructure, instant rollback, and audit history covering which prompt version served which user and when.

Reliability Engineering for Agent Runs

Agent runs are long, stateful, and failure-prone.

Own retry and resume semantics so a run that fails mid-way does not restart from scratch.

Implement timeouts and circuit breakers on provider calls, dead-letter handling for failed runs, and queue and concurrency management for agent workloads.

SLO Ownership and Incident Response

Define and track SLOs for agent run latency and completion rates.

Lead incident response when SLOs are breached.

Write postmortems.

Surface reliability risks proactively before they reach users.

Safety and Compliance Operations

Run the moderation pipeline (prompt and output classification) in production.

Monitor for abuse patterns and own incident response when the agent misbehaves at scale.

Maintain audit logs and implement data retention and residency policies for prompts and generated code as enterprise requirements emerge.

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 LLM-backed systems in operation (mandatory).

Must have personally shipped and operated at least one LLM-powered system in production, with operational responsibility including oncall, incident response, and reliability ownership.

Alternatively: strong DevOps or SRE background with demonstrated hands-on familiarity with LLMOps tooling (Langfuse, LangSmith, Braintrust, Arize, or equivalent).

POCs and lab work do not qualify.

5+ years of overall engineering experience

With at least 2 years in DevOps, SRE, platform engineering, or LLM operations roles.

This is not an ML science role.

A DevOps or SRE background with a substantive pivot into LLMOps is a strong qualification.

Observability and Tracing Depth

Production experience with LLM observability tooling - Langfuse, LangSmith, Braintrust, or Arize Phoenix.

Comfortable instrumenting with OpenTelemetry, Prometheus, and Grafana.

Able to build and search trace pipelines, define failure taxonomies, and surface quality signals from production traffic.

CI/CD and Quality Gate Experience

Strong with GitHub Actions or GitLab CI.

Experience building automated quality gates: eval-gated pipelines, regression enforcement, or coverage gates that block degrading changes from shipping.

Cost Management and Attribution for Usage-Based Services

Experience owning cost attribution for cloud API spend or equivalent.

Comfortable with budget alerts, anomaly detection, and per-user or per-task cost breakdowns.

Reliability Engineering for Long-Running, Stateful Workloads

Experience with queues, retry patterns, idempotency, and failure recovery on asynchronous or multi-step workloads.

Comfortable defining SLOs and being accountable for them on production systems.

Multi-Provider API Management

Familiarity with LLM provider rate limits, version pinning, fallback chains, and quota management across OpenAI, Anthropic, Google, or equivalent.

Infrastructure as Code and Deployment Automation

Hands-on with Terraform or Pulumi and Docker.

AWS working knowledge (EC2, S3, IAM, EKS or ECS).

Strong with CI/CD for deploying services and configuration changes safely.

Nice to Have

• Experience with prompt A/B testing or staged rollout infrastructure
• Workflow orchestration (BullMQ, Temporal, Celery)
• Content moderation pipeline experience
• Data residency and compliance requirements for AI systems
• Kubernetes (EKS) in production
• AWS certifications

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 Backend Engineer for a dedicated client engagement building an AI-powered application builder platform.

The backend is the operational core of the product: it manages user projects and sessions, coordinates long-running AI agent workloads, maintains project state, and serves as the integration layer between the frontend, the AI system, and the underlying infrastructure.

The mandatory requirement is hands-on production experience shipping Node.js services, with end-to-end ownership of API design, data modelling, and at least one production system involving background job processing or event-driven patterns.

Responsibilities

API and service development: Design and build REST APIs in Node.js with TypeScript. Cover authentication, session management, input validation, structured error handling, streaming responses (SSE, WebSockets), and rate limiting. Maintain clean API contracts that the frontend and AI system can rely on.

Database design and management: Own PostgreSQL schema design for product domains including user accounts, projects, file trees, session state, and generated artefacts. Write efficient queries, manage migrations, and optimise for read patterns that serve a real-time editor experience.

Caching strategy: Implement and maintain caching with Redis for session data, project state, and frequently read configuration. Design cache invalidation logic that keeps the editor experience consistent without stale reads.

Queue and background job management: Implement and operate background job infrastructure using BullMQ or equivalent. AI agent runs are long-running and stateful; handle retries, failure states, priority queues, and concurrency limits.

AI system integration: Build the integration layer between the backend and the AI agent system. Manage job dispatch, result handling, streaming output to the frontend, and error propagation.

Multi-tenancy and access control: Implement tenant data isolation, RBAC, and resource ownership enforcement across all API surfaces.

Observability and reliability: Instrument services with structured logging, metrics, and tracing. Write defensive code with sensible timeouts, fallback behaviour, and circuit breaking on external dependencies.

Testing and code quality: Write unit and integration tests for the services you ship. Review the work of peers and contribute to shared engineering conventions.

Requirements

• Hands-on production Node.js experience (mandatory) — must have personally shipped at least one feature area end to end in a production Node.js service, owning API design, data modelling, and testing.

• 3 to 5 years of professional backend engineering experience. Candidates with slightly less time but strong demonstrated ownership are welcome to apply.

• Strong Node.js and TypeScript. Production experience with Express, NestJS, or Fastify. Solid with async patterns, streaming, error handling, and building services that run reliably under sustained load.

• PostgreSQL depth. Schema design, query writing, indexing, and migrations on at least one production system.

• Redis and caching. Production experience using Redis for caching and session management. Understands cache invalidation trade-offs.

• Queue and background job systems. Hands-on with BullMQ, RabbitMQ, SQS, or equivalent. Experience managing retries, dead-letter queues, job priority, and concurrency control.

• AWS working knowledge. Comfortable with EC2, S3, RDS, SQS, and IAM. Familiar with Docker and basic deployment and environment management.

• Strong written and spoken English. Able to communicate clearly with engineers across disciplines and write precise technical documentation.

Nice to Have

Experience integrating with AI or LLM services (streaming responses, structured outputs, retry patterns); WebSocket or SSE implementation for real-time features; multi-tenant SaaS product experience; GraphQL; OpenTelemetry instrumentation; prior work on developer tools or editor-style products.

Job Title : API Lead

Experience : 8+ Years

Location : Remote (Laptop pickup required for 2 days from Noida, Hyderabad, Chennai, Pune, or Bengaluru)

Shift : IST (Regular Day Shift)

Role Overview :

We are looking for an experienced API Lead with strong expertise in C#.NET, Azure Cloud, Azure Functions, and Azure Kubernetes Service (AKS) to design, develop, and lead scalable, secure, and high-performance APIs and microservices for cloud-native applications.

Mandatory Skills :

C#, .NET, .NET Core/.NET 6+, Azure Cloud Services, Azure Functions, Azure Kubernetes Service (AKS), REST API Development, Docker, Kubernetes, Azure SQL/Cosmos DB, and CI/CD using Azure DevOps or GitHub Actions.

Mandatory Skills :

• C#.NET (.NET Core/.NET 6+)
• Azure Cloud Services
• Azure Functions
• Azure Kubernetes Service (AKS)
• REST API Development
• Docker and Kubernetes
• Azure SQL and/or Cosmos DB
• CI/CD (Azure DevOps or GitHub Actions)

Key Responsibilities :

• Design and develop RESTful APIs and microservices using C# and .NET Core/.NET 6+.
• Build and integrate solutions using Azure services such as Azure Functions, APIM, App Services, and Storage.
• Deploy and manage containerized applications using Docker and AKS.
• Implement API security using OAuth2, JWT, and Managed Identities.
• Optimize API performance and collaborate with Architecture, DevOps, and QA teams.

Required Technical Skills :

Must-Have Skills :

• Strong expertise in C#, .NET Core, and .NET 6+.
• Hands-on experience with Azure Functions and Azure Kubernetes Service (AKS).
• Strong understanding of REST API architecture and best practices.
• Experience with Docker and Kubernetes concepts.
• Knowledge of Azure API Management (APIM) and Azure PaaS services.
• Experience with Azure SQL Database and Cosmos DB.
• Familiarity with CI/CD pipelines using Azure DevOps and/or GitHub Actions.
• Strong understanding of API authentication and security mechanisms (OAuth2, JWT, Managed Identities).
• Experience with monitoring, troubleshooting, and performance tuning of APIs.

Good to Have :

• Experience with microservices architecture and distributed systems.
• Exposure to Infrastructure as Code (Terraform/Bicep).
• Experience with Application Insights and Azure Monitor.
• Knowledge of Agile/Scrum methodologies.

Job Description

Team Lead – Full Stack Developer

Experience

3–5 Years

Location

Bangalore (Onsite)

Role Summary

We are looking for a highly skilled, hands-on, and ownership-driven Team Lead – Full Stack Developer who can independently architect, design, develop, deploy, and support enterprise-grade web, mobile, and cloud-native applications.

The ideal candidate should have strong expertise in ReactJS, Next.js, Java, Spring Boot, Microservices, Distributed Systems, Cloud Technologies, DevOps, AI-Assisted Development, and Product Engineering.

The candidate will be responsible for owning end-to-end product development, including frontend architecture, backend services, APIs, databases, deployment, production support, stakeholder communication, sprint planning, team leadership, and successful delivery of scalable, secure, and high-performance solutions.

Key Responsibilities

Architecture & Product Ownership

• Design end-to-end application architecture, HLDs, LLDs, deployment architecture, integration architecture, and security architecture.
• Build products from scratch and independently drive projects from concept to production.
• Convert business requirements into technical solutions, user stories, sprint plans, and delivery roadmaps.
• Design scalable, secure, fault-tolerant, multi-tenant, and enterprise-grade applications.
• Evaluate and recommend suitable technologies, frameworks, and development approaches.

Full Stack Development

Frontend Development

• Design and develop responsive and modern web applications.
• Build reusable UI components and scalable frontend architectures.
• Develop Single Page Applications (SPA) using ReactJS and Next.js.
• Implement state management using Redux Toolkit and Context API.
• Integrate REST APIs, GraphQL APIs, and WebSocket-based applications.
• Ensure application accessibility, responsiveness, performance optimization, and SEO best practices.
• Collaborate closely with UI/UX designers to deliver intuitive user experiences.

Backend Development

• Develop enterprise-grade backend applications using Java and Spring Boot.
• Design and develop REST APIs, Microservices, SOAP Services, gRPC Services, and Webhooks.
• Build reusable frameworks, service layers, and integration modules.
• Implement authentication, authorization, API security, and enterprise integrations.
• Optimize application performance, scalability, reliability, and maintainability.

Distributed Systems & Enterprise Solutions

• Design distributed systems using Event-Driven Architecture, CQRS, Saga Pattern, DDD, Hexagonal Architecture, and Clean Architecture.
• Implement resilience patterns, service discovery, circuit breakers, distributed transactions, and failover mechanisms.
• Build workflow automation platforms, document management systems, enterprise integration solutions, and business process automation systems.

Team Leadership & Delivery

• Lead and mentor development teams.
• Conduct code reviews, architecture reviews, and technical discussions.
• Drive sprint planning, stand-ups, reviews, and retrospectives.
• Collaborate with Product, Business, QA, DevOps, AI, and Management teams.
• Ensure successful project delivery while maintaining engineering standards and best practices.
• Support hiring, onboarding, mentoring, and technical growth of team members.

DevOps, Deployment & Production Support

• Manage CI/CD pipelines and deployment processes.
• Work with Docker, Kubernetes, and cloud-native environments.
• Implement Blue-Green, Canary, Rolling, and Zero-Downtime deployment strategies.
• Monitor application health and troubleshoot production issues.
• Ensure application reliability, security, scalability, and operational excellence.

AI & Innovation

• Leverage AI tools to improve development productivity and software quality.
• Build AI-powered Proof of Concepts (POCs) and enterprise applications.
• Utilize AI for development, testing, documentation, architecture reviews, and automation.
• Collaborate with AI teams to integrate intelligent capabilities into business applications.

Mandatory Technical Skills

Frontend Technologies

• ReactJS
• Next.js
• JavaScript (ES6+)
• TypeScript
• HTML5
• CSS3
• Tailwind CSS
• Material UI
• Bootstrap
• Redux Toolkit
• Context API
• React Query
• Responsive Design
• Progressive Web Applications (PWA)

Backend Technologies

• Java 8/11/17/21
• Core Java
• Spring Boot
• Spring MVC
• Spring Security
• Spring Data JPA
• Spring Cloud
• Spring Batch
• Spring WebFlux
• Spring Integration
• Spring AOP
• Spring Validation

APIs & Enterprise Integrations

• REST APIs
• SOAP Services
• GraphQL
• gRPC
• Webhooks
• OpenAPI / Swagger
• OAuth2
• JWT
• OpenID Connect
• SAML

Microservices & Distributed Systems

• Microservices
• Event-Driven Architecture
• CQRS
• Saga Pattern
• Domain-Driven Design (DDD)
• Event Sourcing
• Hexagonal Architecture
• Clean Architecture
• Service Discovery
• Circuit Breakers

Messaging & Streaming

• Apache Kafka
• RabbitMQ
• Event Streaming
• Message Brokers
• Asynchronous Processing

Databases

• PostgreSQL
• Oracle Database
• Oracle FLEXCUBE
• MySQL
• SQL Server
• MongoDB
• Redis
• Database Design
• Query Optimization
• Indexing
• Migration
• Replication

DevOps & Cloud

• Docker
• Kubernetes
• Jenkins
• GitHub Actions
• GitLab CI/CD
• AWS
• Azure
• GCP

Monitoring & Quality

• Grafana
• Prometheus
• ELK Stack
• OpenTelemetry
• JUnit
• Mockito
• SonarQube
• Unit Testing
• Integration Testing
• API Testing
• Performance Testing
• Security Testing

AI-Assisted Development Tools

• ChatGPT
• Claude
• Cursor
• GitHub Copilot
• Replit
• Lovable
• IntelliJ IDEA
• Prompt Engineering
• AI-Based Code Review
• AI-Based Testing & Documentation

Preferred Domain Experience

• Banking & Financial Services
• FinTech
• Enterprise SaaS
• Workflow Automation
• Digital Transformation
• AI-Powered Applications
• OCR & Document Processing
• Payment Systems
• Enterprise Integration Platforms
• Identity & Access Management
• Multi-Tenant Platforms

Soft Skills

• Strong leadership and ownership mindset.
• Excellent communication and stakeholder management skills.
• Strong analytical and problem-solving abilities.
• Ability to manage multiple projects simultaneously.
• Strong mentoring and team collaboration skills.
• Innovation-driven and continuous learning attitude.

Education

Bachelor's Degree or Master's Degree in:

• Computer Science
• Information Technology
• Software Engineering
• Electronics & Communication
• Or equivalent practical experience

Preferred Candidate Profile

A highly motivated Full Stack Engineering Leader with experience building products from scratch, owning frontend and backend architecture, leading engineering teams, driving innovation, and delivering scalable enterprise-grade applications across web, mobile, cloud, and enterprise platforms. The candidate should be capable of independently managing architecture, development, deployment, production support, and successful project delivery while mentoring and growing engineering teams.

mandatory one w

Role: Azure Devops Consultant

Location: Bangalore

Fulltime

Work Mode: 5 Days Work From Office.

Responsibilities:

· Design and architect CI/CD pipelines and development automation solutions.

· Lead implementation of build versioning, packaging, and dependency

management strategies

· Define standards for code quality, security scanning, and automated testing

integration

· Create reference architectures for development workflows and automation

patterns

· Collaborate with security teams to implement "shift-left" security practices

· Guide implementation of A/B testing and feature flagging architectures

Skills:

· Strong expertise in Azure DevOps,PAAS, Git, CI/CD practices

· Deep understanding of SDLC and automation

· Containerization (Docker, Kubernetes)

· Security scanning tools (Veracode, SonarQube)

· Build tools and artifact management

· IaC (Terraform, ARM templates)

Job Title: Technical Lead – Python/Django

Location- Delhi

Job type: Full time, On site

About Us: TIMBLE is leading Authentication Company, delivering cutting edge technology and alternate data analysis for Identity management, Onboarding & Verification and Business Intelligence. We provide solutions across three verticals

1. BFSI Solutions

2. KYC and background check Solutions

3.AI Solutions

Key Responsibilities

·      Architecture & Design: Design, develop, and maintain robust, scalable, and secure backend microservices and RESTful APIs using Python and Django.

·      Technical Leadership: Lead code reviews, enforce engineering best practices (TDD, clean code, documentation), and optimize database queries and system performance.

·      Team Mentorship: Guide, mentor, and unblock a team of mid-to-senior software development engineers (SDEs), fostering a high-performance execution culture.

·      System Optimization: Optimize application performance, enhance caching mechanisms, manage task queues, and ensure system uptime and smooth deployment pipelines.

·      Cross-functional Collaboration: Work closely with Frontend, Product Management, DevOps, and AI/ML teams to align backend capabilities with the product roadmap.

Required Skills & Qualifications

·      Experience: 6+ years of core software engineering experience, with at least 2+ years in a technical leadership or mentoring role.

·      Core Expertise: Exceptional command over Python and deep, production-level expertise in the Django/Django framework.

·      Database Management: Strong proficiency with relational databases (PostgreSQL, MySQL) and optimization (indexing, complex query tuning).

·      Caching & Queues: Practical experience with caching layers (Redis, Memcached) and asynchronous task queues (Celery).

·      Architecture Patterns: Solid understanding of microservices architecture, system design principles, API security, and RESTful web services.

·      DevOps Awareness: Familiarity with Docker, CI/CD pipelines, and cloud infrastructure (AWS/GCP) is a major plus.

·      Education: B.Tech/M.Tech or MCA / MBA in a technical specialization from a reputed institute.

What We Offer

·      Opportunity to lead a core engineering vertical in a fast-growing AI startup.

·      A collaborative, high-energy work culture with zero bureaucratic friction.

·      Competitive compensation packages and performance-driven growth paths.

Learn more about us at: https://timbleglance.com

Client: Capgemini

Location: Hyderabad

Experience: 8+ Years

Senior Software Engineer

As a Senior Software Engineer, you will design, develop, test, and deploy sophisticated Generative AI applications. You will work within a dedicated engineering pod, partnering with technical leaders to translate architectural designs into robust, scalable, and secure software. This role requires hands-on development experience and a strong interest in solving complex technical problems using modern AI capabilities.

In this role, you will:

• Lead moderately complex initiatives and deliverables within technical engineering environments.
• Contribute to large-scale planning of strategies across Consumer Technology.
• Design, code, test, debug, and document applications and services, including upgrades and deployments.
• Review technical challenges that require in-depth evaluation of technologies, procedures, and engineering approaches.
• Resolve moderately complex issues while guiding teams to meet existing and emerging business needs.
• Collaborate with peers, colleagues, and mid-level managers to resolve technical challenges and meet project goals.
• Lead projects and act as an escalation point, providing direction to less experienced engineers.
• Design, develop, and deploy AI applications using enterprise APIs, LLMs, agent frameworks, and related technologies.
• Implement prompt engineering, retrieval-augmented generation, fine-tuning, and agentic design patterns.
• Integrate LLM models with existing enterprise systems and ensure that AI solutions meet governance, security, and compliance standards.
• Troubleshoot complex application and model-related issues and contribute to the continuous improvement of AI systems.
• Assist and mentor engineers in advanced software development and AI engineering practices.
• Stay informed of advancements in AI, LLMs, and agent frameworks and apply relevant updates to products and systems.

Required Qualifications:

• 4+ years of software engineering experience or equivalent through a combination of work experience, training, military service, or education.
• 2+ years of experience working with Generative AI, large language models, or foundation models.
• 2+ years of experience with either GCP, Azure, Kubernetes, or OpenShift.
• 2+ years of experience with Python.
• 2+ years of experience with REST API development and containerization technologies such as Docker and Kubernetes.
• 2+ years of experience using Git for source code version control, including branching, pull requests, and collaborative development workflows.

Desired Qualifications:

• Understanding of cloud security principles including identity and access management, encryption, and network security in public or hybrid cloud environments.
• Experience working in highly regulated industries such as financial services.
• Experience as a technical lead or architect, including mentoring senior engineers.
• Experience integrating or contributing to open-source AI or ML projects.
• Experience integrating applications with enterprise data platforms, APIs, and secure data pipelines.
• Strong communication and documentation skills to collaborate across engineering, product, and oversight teams.

Preferred Skills and Experience:

• Experience with LLM development using OpenAI, Anthropic, or Google Gemini models.
• Experience with agentic frameworks and AI workflow orchestration.
• Experience designing applications that incorporate retrieval-augmented generation, fine-tuning, and structured prompting.
• Experience with vector databases and retrieval systems such as Elasticsearch, OpenSearch, Pinecone, or Weaviate.
• Experience with LLM evaluation, observability, and monitoring, including latency, cost, accuracy, grounding, drift detection, and safety assessments.
• Familiarity with ML lifecycle tools and processes such as feature stores, model registries, and CI/CD pipelines for AI services.
• Familiarity with responsible AI principles, compliance, and governance processes related to AI systems in regulated environments.
• Experience optimizing AI application performance, including prompt efficiency, model selection, caching, batching, and cost management.

Key Focus Areas:-

• Scalable SaaS and distributed systems

• Microservices architecture

• Backend performance and API optimization

• Cloud infrastructure and DevOps

• Multi-tenant platforms

• Reliability, scalability, and engineering governance

Main Responsibilities:-

• Design fault-tolerant backend systems

• Lead architecture decisions and technical planning

• Improve system performance, scalability, and deployment workflows

• Guide senior developers and enforce engineering standards

• Reduce technical debt and solve complex production issues

• Collaborate with DevOps on CI/CD, monitoring, and AWS infrastructure.

• You will work on complex, enterprise-scale systems including large SaaS platforms, distributed backend architectures, pricing intelligence engines, CRM solutions, 3D configuration ecosystems, route optimization modules, payment integrations, high-volume APIs, and modern cloud infrastructure.

• We are not looking for a “people manager who used to code.

Required Skills:-

• Backend: Node.js, TypeScript, REST APIs, event-driven systems

• Frontend Understanding: React.js architecture concepts

• Databases: PostgreSQL, MySQL, Redis, query optimization

• Cloud/DevOps: AWS, Docker, CI/CD, Kubernetes (preferred)

• System Design: Microservices, distributed systems, high-availability SaaS platforms

Preferred Experience:-

• SaaS product companies

• Enterprise CRM systems

• Large-scale production platforms

• Pricing engines, WebGL/3D systems, AI-assisted workflows

• U.S.-based product engineering environments

Experience Needed:-

• 10–15 years in software engineering

• 3+ years in architect/principal engineer/engineering lead roles

• Proven experience building scalable production systems

Ideal Candidate:-

A technically strong, ownership-driven architect who:

• Thinks strategically

• Stays calm under pressure

• Solves complex engineering problems

• Mentors teams effectively

• Builds long-term scalable systems rather than quick fixes

If your code breaks here, it doesn’t just throw an error.

Jobs don’t get fulfilled. Farmers lose trust during crop windows that don’t wait.

We’re hiring a Software Development Engineer in Bangalore to build the systems that keep real-world operations running — from customer-facing products to the internal tools field teams depend on every morning.

→ Design, build, and ship across the stack: backend services, APIs, mobile/web field apps, and operational dashboards

→ Build systems for deployment, attendance, check-in/check-out, work verification, and issue resolution

→ Make products work in low-connectivity, field-heavy conditions with offline-first and vernacular-first experiences

→ Own features end to end — from design discussions to deployment to on-call

→ Work closely with Product, Ops, and field users to solve what’s actually happening on the ground

→ Contribute to data pipelines and analytics that power planning, forecasting, and unit economics

• 1–5 years building production software

• Comfortable across the stack, or deep in one area and ready to stretch

• Strong ownership mindset — you ship, debug production issues, and care if it works for the user

• Pragmatic with trade-offs and able to balance speed with quality

• Bonus if you’ve built for low-bandwidth, offline-first, next-billion-user contexts

Stack: Python, Django, React, PostgreSQL, Redis, AWS/GCP, Docker, CI/CD

You’ll be building software for the real economy — farmers, labour, livelihoods — not another dashboard for another SaaS tool.

📍 Bangalore (on-site) | Reporting to CTO

If this sounds like you — or someone you’d bet on — tag them in the comments or DM me.

#Hiring #SoftwareEngineer #BackendEngineer #FullStackDeveloper #BangaloreJobs #TechJobs

About NonStop io Technologies

NonStop io Technologies is a value-driven company with a strong focus on process-oriented software engineering. We specialize in Product Development and have a decade's worth of experience in building web and mobile applications across various domains. NonStop io Technologies follows core principles that guide its operations and believes in staying invested in a product's vision for the long term. We are a small but proud group of individuals who believe in the 'givers gain' philosophy and strive to provide value in order to seek value. We are committed to and specialize in building cutting-edge technology products and serving as trusted technology partners for startups and enterprises. We pride ourselves on fostering innovation, learning, and community engagement. Join us to work on impactful projects in a collaborative and vibrant environment.

Brief Description

We are looking for a skilled DevSecOps Engineer who can help design, automate, and secure cloud-native platforms for healthcare and life sciences clients. The ideal candidate will have hands-on experience with cloud security, infrastructure automation, CI/CD pipelines, compliance controls, and platform operations in regulated environments.

You will work closely with engineering teams, architects, security stakeholders, and client representatives to build secure-by-design systems that meet healthcare security and compliance requirements. Experience supporting AI/ML platforms, healthcare data platforms, or regulated workloads is highly desirable.

Roles and Responsibilities

• Design and implement security controls aligned with healthcare regulations, including HIPAA, HITRUST, and industry security best practices
• Ensure secure handling of Protected Health Information (PHI), Personally Identifiable Information (PII), and sensitive healthcare datasets
• Support client security reviews, vendor assessments, penetration testing remediation, and compliance audits
• Partner with engineering teams to establish secure SDLC practices and shift-left security initiatives
• Implement cloud governance policies, security baselines, and compliance automation across multiple client environments
• Build and maintain audit-ready logging, monitoring, and evidence collection mechanisms
• Support disaster recovery, business continuity, and security incident response processes
• Collaborate with healthcare product teams working on FHIR APIs, healthcare integrations, clinical applications, genomics platforms, or AI-enabled healthcare solutions
• Experience working with healthcare, life sciences, biotech, genomics, digital health, or regulated SaaS platforms is strongly preferred
• Understanding of PHI, PII, healthcare security controls, and healthcare compliance requirements
• Familiarity with healthcare interoperability standards such as FHIR, HL7, SMART on FHIR, or healthcare APIs is a plus
• Experience securing healthcare data platforms, analytics environments, AI/ML workloads, or regulated cloud environments is highly desirable
• Ability to work directly with client stakeholders and communicate security risks, recommendations, and remediation plans
• Experience participating in security assessments, audits, compliance reviews, and client-facing technical discussions
• Strong documentation and security governance skills

Requirements

• 4–7 years of experience in DevOps, DevSecOps, SRE, or Platform Engineering
• Strong experience with AWS, Azure, or GCP and cloud security best practices
• Hands-on experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps
• Experience with security tools, including SonarQube, Snyk, Checkmarx, Fortify, Veracode, or similar platforms
• Strong understanding of vulnerability management, IAM, threat detection, and security scanning
• Experience implementing compliance controls aligned with one or more of the following frameworks:
• HIPAA
• HITRUST
• SOC 2
• ISO 27001
• NIST Cybersecurity Framework
• PCI-DSS (where applicable)
• FDA-regulated software environments (preferred)
• Proficiency with Terraform, CloudFormation, ARM, Docker, Kubernetes, Linux, and shell scripting
• Experience with monitoring and observability tools such as Prometheus, Grafana, ELK, or Datadog
• Exposure to MLOps/AI platforms, model deployment, or AI workload management is desirable
• Strong troubleshooting, automation, networking, and cloud security skills

Why Join Us?

• Opportunity to work on a cutting-edge healthcare product
• A collaborative and learning-driven environment
• Exposure to AI and software engineering innovations
• Excellent work ethic and culture

If you're passionate about technology and want to work on impactful projects, we'd love to hear from you!

Role:

We're scaling an AI platform that powers Computer Vision and real-time video analytics, and we need someone to own the architecture, not just contribute to it. Our AI workloads are moving to the cloud, our models need hardening for production, and our engineering practices need a north star. The gap between prototype and production is costing us velocity.

Responsibilities:

• Architect and govern the end-to-end AI platform from data lake to model serving on AWS (SageMaker preferred).
• Lead cloud migration of AI workloads with a cloud-native, containerised approach (Docker, Kubernetes, CI/CD).
• Own the AI roadmap model accuracy, MLOps maturity, observability, and scalability.
• Set engineering standards across ML development, deployment, and monitoring.
• Mentor engineers and data scientists; reduce key-person dependency across the org.
• Drive productionisation, turn research into reliable, monitored, high-performance systems.

Requirements:

• Deep expertise in Computer Vision, Deep Learning, and Video/Real-Time Analytics.
• Fluency in PyTorch and/or TensorFlow, Python, and ML architecture patterns.
• Hands-on with AWS SageMaker, Docker, Kubernetes, CI/CD pipelines.
• Experience with model monitoring, observability tools, and data lake architectures.
• A track record of leading AI strategy, not just executing it.

About the Role

We're looking for a hands-on AI Architect to lead the design and delivery of AI-native applications. You will define the AI stack, establish engineering standards, and drive adoption of AI-assisted development across teams.

Responsibilities

• Architect and build production-grade AI applications.
• Evaluate and standardize AI frameworks, tools, and platforms.
• Design agentic systems, RAG pipelines, and AI workflows.
• Establish AI evaluation, testing, guardrails, and observability practices.
• Drive AI-native development and delivery acceleration initiatives.
• Partner with engineering and product teams on technical roadmap decisions.

Requirements

• 7+ years of software engineering experience.
• Strong experience with LLMs, RAG, embeddings, prompt engineering, and agent frameworks.
• Experience with LangGraph, AutoGen, MCP, or similar ecosystems.
• Hands-on experience with AI evaluations (DeepEval, Ragas), guardrails, and structured outputs.
• Strong Python and TypeScript/Java skills.
• Experience with Kubernetes, CI/CD, IaC, observability, and event-driven architectures.
• Proven experience shipping AI applications to production.

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.

Role & Responsibilities

Responsibilities

• Contribute to the development and optimization of enterprise-wide search systems and models.

• Design and implement algorithms to improve indexing, query relevance, and search accuracy.

• Support taxonomy, ontology, and metadata model creation for better search outcomes.

• Collaborate with business units (Loans, Insurance, Investments) to build AI-enabled search features.

• Conduct analysis of user behavior and system metrics to refine search performance.

• Work with engineers, product managers, and designers to deliver integrated search solutions.

• Develop production-grade ML systems for ranking, personalization, and recommendations.

• Participate in proof-of-concept initiatives with internal and external partners.

• Follow best practices in software engineering including CI/CD, testing, and monitoring.

• Keep abreast of emerging developments in AI/ML to apply them in practical solutions.

Ideal Candidate

Strong Data Scientist / AI Engineer / Machine Learning Engineer profiles.

Mandatory (Experience 1) – Must have minimum 5+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.

Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.

Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.

Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.

Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.

Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.

Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.

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

Mandatory (Age) - Candidate's Age should be below 30 Years

Preferred (Experience 1) – Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or MLOps/LLMOps frameworks.

Preferred (Experience 2) – Experience working with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems..

Preferred (Experience 3) – Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architecture.

Preferred (Company) – Candidates from AI-first startups, Fintech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies.

Kindly provide the following details while sending your CV: (Mandatory details)

1) Date of Birth

2) Current Location-

3) Current CTC-

4) Expected CTC-

5) Notice Period-

6) Ready to relocate to Pune?

Regards,

The Supreme Consultancy

Website- https://lnkd.in/eawfxfxU

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

Experience : 5 to 12 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 12 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

Company Overview:

Pripton Innovations is a dynamic technology company focused on developing cutting-edge AI-powered solutions for the AI services industry. We build and deploy sophisticated platforms that leverage large language models (LLMs) to automate complex processes, enhance decision-making, and improve customer experiences. Our solutions are currently utilised by several leading institutions, impacting millions of users globally.

Role Overview:

As a Fullstack Product Engineer at Pripton Innovations, you will be instrumental in designing, developing, and deploying innovative features for our core AI platform. You will collaborate closely with product managers, designers, and other engineers to translate product requirements into robust, scalable, and user-friendly solutions. Your work will directly impact the efficiency and effectiveness of our AI-driven tools, ultimately driving better outcomes for our clients and their customers.

Key Responsibilities:

- Develop and maintain high-quality, performant APIs using NestJS and FastAPI to support our AI-powered applications.

- Build and enhance interactive user interfaces with Next.js and Tailwind CSS, ensuring a seamless and engaging user experience.

- Implement real-time communication features using Socket.io to facilitate dynamic interactions within our platform.

- Design and optimise database schemas and ORM configurations to ensure efficient data storage and retrieval.

- Deploy and manage applications using Docker and container orchestration technologies to maintain high availability and scalability.

- Write clean, well-documented, and testable code, adhering to industry best practices.

- Collaborate with cross-functional teams to define, design, and ship new features.

- Troubleshoot and resolve production issues, ensuring minimal disruption to our users.

- Contribute to the continuous improvement of our development processes and tools.

Required Skillset:

- Demonstrated ability to design and implement scalable and maintainable full-stack applications.

- Proven experience with backend technologies such as NestJS, FastAPI, and Python.

- Expertise in frontend development using Next.js and Tailwind CSS.

- Proficiency in working with databases and ORM frameworks.

- Solid understanding of real-time communication protocols and experience with Socket.io.

- Experience with containerization technologies like Docker and Git version control.

- Strong problem-solving skills and the ability to work independently and as part of a team.

- Excellent communication and collaboration skills, with the ability to articulate technical concepts clearly.

- Bachelor's degree in Computer Science or a related field.

- Adaptability to a remote work environment and ability to manage time effectively.

About the Role 

We are looking for a Senior DevOps Engineer to lead the design, automation, and scaling of our hybrid cloud infrastructure spanning public cloud and private/on-premises environments. You will partner closely with software engineering, security, and product teams to build reliable, secure, and high-performance systems that support rapid product delivery. This is a hands-on role with significant influence over our infrastructure strategy, deployment workflows, and engineering culture. 

Key Responsibilities 

• Architect, deploy, and maintain scalable, highly available infrastructure across both public cloud (AWS, Azure, GCP) and private cloud platforms (OpenStack, VMware vSphere/Tanzu, Nutanix, or similar). 
• Operate and maintain on-premises infrastructure: hypervisors, compute, storage (Ceph, NetApp, SAN/NAS), networking (SDN, VLANs, BGP, MPLS), and hardware capacity planning, alongside their public cloud equivalents. 
• Design and own CI/CD pipelines that deploy seamlessly across public and private environments. 
• Implement and manage Infrastructure as Code (Terraform, Ansible, Pulumi) with strong version control and review practices, using providers for both public and private cloud platforms. 
• Manage container orchestration (Kubernetes, ECS, OpenShift, Rancher) across managed cloud services and self-managed/bare-metal clusters, including upgrades, autoscaling, and workload reliability. 
• Build observability into all systems through logging, metrics, tracing, and alerting (Prometheus, Grafana, Datadog, ELK, or similar) with unified visibility across hybrid environments. 
• Champion security best practices: secrets management, IAM hardening, network segmentation, vulnerability scanning, and compliance (SOC 2, ISO 27001, HIPAA, or data-sovereignty requirements). 
• Lead incident response, root-cause analysis, and post-mortems; drive long-term reliability improvements and SLO/SLA adherence. 
• Optimize cost, capacity, and resource utilization across public cloud spend and on-premises hardware without compromising performance or availability. 
• Partner with data center operations and network providers on hardware provisioning, firmware management, MPLS circuit management, and lifecycle planning. 
• Mentor junior DevOps and software engineers; promote DevOps culture, automation-first thinking, and shared ownership of production. 
• Evaluate and introduce new tools, platforms, and processes that improve developer productivity and system reliability. 

Required Qualifications 

• 5+ years of experience in DevOps, SRE, or Platform Engineering roles, with at least 2 years at a senior level. 
• Deep expertise with at least one major public cloud provider (AWS, Azure, or GCP) in production. 
• Hands-on experience operating private cloud or virtualization platforms (OpenStack, VMware, Nutanix, or equivalent) in production. 
• Strong experience with virtualization, storage systems, and enterprise networking in on-premises environments. 
• Strong hands-on experience with Kubernetes in production, including both managed cloud and self-managed/bare-metal clusters. 
• Proficiency in Infrastructure as Code (Terraform and Ansible strongly preferred). 
• Solid scripting and programming skills in Python, Go, Bash, or similar. 
• Experience designing and operating CI/CD pipelines using tools such as GitHub Actions, GitLab CI, Jenkins, CircleCI, or ArgoCD. 
• Strong Linux systems administration and networking fundamentals (TCP/IP, DNS, load balancing, VPNs, firewalls, routing, MPLS). 
• Experience with monitoring and observability stacks (Prometheus, Grafana, Datadog, New Relic, ELK, or OpenTelemetry). 
• Proven track record of leading incident response and improving system reliability. 
• Excellent communication skills and the ability to collaborate across engineering, security, infrastructure, and product teams. 

Preferred Qualifications 

• Experience designing hybrid and multi-cloud architectures, including secure connectivity (Direct Connect, ExpressRoute, MPLS, VPN, SD-WAN) between public and private environments. 
• Familiarity with service meshes (Istio, Linkerd), API gateways, and GitOps workflows (ArgoCD, Flux). 
• Background in security-focused or regulated environments and exposure to compliance frameworks. 
• Experience with database administration (PostgreSQL, MySQL, Redis, MongoDB) in cloud-managed and self-hosted setups. 
• Contributions to open-source DevOps or cloud infrastructure tooling. 
• Relevant certifications (AWS Solutions Architect / DevOps Engineer, Azure Administrator, CKA, CKAD, RHCE, VMware VCP, OpenStack Certified Administrator, HashiCorp Terraform Associate). 

About My Client Company

We're building the learning infrastructure that transforms AI agents into true digital workers. While today's agents can reason and plan, they fail to do meaningful work because they lack real experience operating in apps. My Client Product gives agents continuously improving, reusable skills across 1000+ production-grade app connectors including Gmail, Linear, and Hubspot. We handle authentication, tool routing, retries, failure handling, and observability, making every action safe and dependable.

About the Role

Every enterprise is racing to make AI work — not as a demo, but as infrastructure that runs their business. My Client Product is becoming the critical layer that makes this possible: the platform that connects AI agents to 250+ real-world applications with production-grade auth, execution, and reliability.

We've built this for the cloud. Now we need to build it for the enterprise — and that means rethinking the platform from the ground up with the right abstractions, primitives, and architectural decisions that let us serve a massive, diverse set of enterprise customers without bespoke engineering for each one. This is a founding role.

Your Impact

• Agent infrastructure platform: The foundational layer that enterprise AI agents run on — governance, observability, and control planes for MCP-powered agent ecosystems. You'll define how organizations monitor, audit, and manage AI agents operating at scale across their systems
• The integration gateway: The secure, reliable bridge between an enterprise's AI agents and the outside world — every SaaS tool, internal system, and API they need to act on. Not just connectors, but a platform-grade gateway with the right trust, permissioning, and routing primitives
• Platform primitives for scale: Multi-tenancy, isolation, configuration, and extensibility abstractions that let Composio serve thousands of enterprise customers without linear engineering cost
• Enterprise-grade architecture: Deployment flexibility, security, and compliance as first-class platform capabilities — not bolted-on afterthoughts
• The repeatable deployment motion: Turn enterprise onboarding from a services engagement into a product experience. Shorter cycles, fewer custom touches, more self-serve

What you bring

• You've built platforms at genuine scale — not just high user counts, but high complexity: many customer types, deployment models, and integration surfaces
• You think in abstractions and primitives. Your instinct is to find the right foundational model, not to solve each problem individually
• You've shipped enterprise product capabilities (deployment flexibility, security, admin tooling, compliance) and understand them as product problems, not just checkboxes
• You've built or shipped an AI product — or you're the person who can't stop tinkering. You're building agents on weekends, stress-testing the latest models, experimenting with MCP, and forming your own opinions on where agent architectures are headed. You have a point of view on this space, not just a resume line
• You're a force multiplier. When you join a team, the entire product moves faster because the platform decisions are right

Skills & Expertise

Platform Engineering, AI Infrastructure, Agentic AI, AI Agents, MCP (Model Context Protocol), Distributed Systems, Enterprise Architecture, Multi-Tenant Architecture, Backend Platform Engineering, Enterprise SaaS, API Platform Engineering, Integration Platforms, SaaS Connectors, Cloud Infrastructure, AWS, GCP, Kubernetes, Docker, Terraform, Microservices, Event-Driven Architecture, API Gateway, OAuth 2.0, RBAC, IAM, Observability, OpenTelemetry, Prometheus, Grafana, Reliability Engineering, SRE, Python, Golang, Node.js, TypeScript, REST APIs, GraphQL, AI Orchestration, LLM Infrastructure, LangChain, LangGraph, OpenAI APIs, Claude APIs, RAG, Workflow Automation, AI Tool Routing, Enterprise Security, Compliance Engineering, Deployment Architecture, Configuration Management, Extensible Systems, Scalability Engineering, High-Scale Systems, Technical Strategy, Platform Primitives, Developer Platforms, Enterprise Integrations, Infrastructure Engineering, Founding Engineer Mindset.

This role demands deep platform thinking. You've designed systems where the abstractions were the product — where getting the primitives right meant the difference between a product that scales and one that drowns in customer-specific code.

You've done this within large organizations and seen what "enterprise-grade" actually means when thousands of teams depend on your platform. But you've also operated in environments where you had to build fast, make tradeoffs, and ship before the architecture was perfect.

The combination matters. Big-company pattern recognition with small-company intensity.

What We Offer

• Lunch and dinner are provided in the office
• $200/month learning and development budget
• $1,000/month AI tool experimentation budget to automate, accelerate, and improve how you work
• High-ownership role with direct exposure to leadership and company-building decisions
• Competitive salary and equity

Location: Bangalore 

Experience: 4-8 years

Interview Process - Two Rounds - First Round Virtual

Second Round-Face to Face at Bangalore

Key Skills Required

☁️ Cloud & Infrastructure

• Strong hands-on experience with AWS Cloud Services
• Proficiency in Terraform for Infrastructure as Code (IaC)
• Experience in managing scalable cloud environments

⚙️ Containerization & Orchestration

• Solid experience in Kubernetes (K8s) for container orchestration
• Understanding of microservices architecture

🔄 CI/CD & DevOps

• Hands-on experience with Azure DevOps (CI/CD pipelines)
• Experience in build, release, and deployment automation

📊 Observability & Monitoring

• Strong experience with Prometheus & Grafana
• Expertise in setting up alerts, dashboards, and monitoring system health

🔐 API Gateway & Security

• Experience with Kong or equivalent API Gateway
• Understanding of API security controls (authentication, rate limiting, policies)

🧠 Core Technical Competencies

• Strong Linux troubleshooting and system debugging skills
• Proficiency in scripting (Bash / Python / Shell)
• Understanding of networking concepts: TCP/IP, HTTP, DNS, Load Balancing
• Experience with system architecture and distributed systems

🚨 SRE Responsibilities

• Monitor system performance, reliability, and availability
• Handle incidents, perform troubleshooting, and conduct RCA
• Automate operational tasks to improve efficiency
• Build and maintain scalable, resilient infrastructure
• Collaborate with development and DevOps teams for system improvements

🧪 Good to Have

• Experience with Finacle operations
• Exposure to API/load testing tools like JMeter or Gatling
• Familiarity with logging tools like Loki

🤝 Soft Skills

• Strong communication and collaboration skills
• Ability to document processes and technical workflows clearly

🎯 Ideal Candidate

A hands-on SRE/DevOps Engineer with strong exposure to:

• AWS + Terraform + Kubernetes
• CI/CD (Azure DevOps)
• Monitoring + API Gateway security 

Company: Amura Health

Location: Velachery, Chennai

Work Model: 6 Days Work From Office (Mandatory)

About Amura Health:

Amura Health is building a transformative health platform focused on improving human potential through better health outcomes. The company believes that healthier bodies lead to healthier brains, enabling people to solve more complex problems, contribute meaningfully to society, and create a better future.

The organization is building next-generation healthcare technology products and platforms that aim to redefine the way medicine is practiced globally. With a strong focus on innovation, scale, and impact, Amura Health operates in a fast-paced, high-ownership environment where engineers work on meaningful and technically challenging problems.

Role Overview

We are looking for a highly skilled Senior Backend Engineer with strong expertise in Node.js and distributed backend systems. The ideal candidate should have experience building scalable APIs, microservices, and backend infrastructure capable of handling high-performance workloads.

This role requires end-to-end ownership of backend modules, including architecture, development, testing, deployment, optimization, and production support. The candidate will collaborate closely with engineering, DevOps, and product teams to build reliable and scalable systems.

Key Responsibilities

Develop scalable backend services, APIs, and microservices using Node.js frameworks such as Express.js and NestJS.

Own backend modules end-to-end from design and implementation to testing and deployment.

Write clean, maintainable, reusable, and high-quality production-grade code.

Optimize application performance, scalability, reliability, and system efficiency.

Troubleshoot production issues, perform root cause analysis (RCA), and improve platform stability.

Work with relational and NoSQL databases for scalable data management.

Implement caching solutions using Redis and optimize API response times.

Work with queues and asynchronous processing systems such as Kafka, RabbitMQ, or Amazon SQS.

Collaborate with DevOps teams for CI/CD pipelines, deployment automation, and infrastructure improvements.

Participate in system design discussions and architectural decision-making.

Contribute to engineering best practices, documentation, and code review processes.

Work effectively in a fast-paced startup environment with high ownership and accountability.

Required Skills & Technical Expertise

Strong expertise in Node.js and backend development.

Hands-on experience with TypeScript, Express.js, and NestJS.

Strong understanding of asynchronous programming and event-driven systems.

Experience designing and consuming REST APIs.

Strong knowledge of microservices architecture and distributed systems.

Experience with SQL databases such as PostgreSQL and MySQL.

Experience with NoSQL databases such as MongoDB, DynamoDB, and Redis.

Knowledge of caching strategies and performance optimization.

Hands-on experience with messaging systems such as Kafka, RabbitMQ, or SQS.

Understanding of Docker, Git, and CI/CD pipelines.

Exposure to AWS cloud infrastructure and deployment environments.

Strong debugging, monitoring, and performance tuning skills.

Knowledge of scalable backend architecture and system reliability.

Eligibility Criteria

4 to 7 years of hands-on backend development experience.

Bachelor’s degree in Computer Science, Information Technology, or related engineering discipline.

Candidates from strong product engineering backgrounds will be preferred.

Experience working in fast-paced startup or high-growth product environments is preferred.

Strong communication, ownership, and problem-solving abilities are essential.

Must be comfortable working from office 6 days a week in Velachery, Chennai.

Ideal Candidate Profile

The ideal candidate is a strong backend engineer who has experience building scalable systems in product-driven environments. They should be comfortable taking ownership of backend services, solving complex engineering challenges, debugging production issues, and collaborating across teams.

The candidate should possess a startup mindset, demonstrate accountability, move quickly, and contribute proactively to engineering excellence.

Work Environment & Expectations

Work from Office model with mandatory in-office presence.

6 working days per week from the Velachery, Chennai office.

High ownership and accountability-driven engineering culture.

Collaborative and fast-paced startup environment.

Candidates should be comfortable working on high-impact systems and solving challenging technical problems.

Company Website

https://amura.ai

Job Description:

Profile: Senior Python AI/ML Engineer

Required experience: 5-9 Years

Location: Mohali, Punjab (WFO only, no hybrid )

B.tech/ MCA preferred

Immediate joiners

We are looking for a Senior Python (AI/ML) Engineerto build and scale a production-grade AI-powered platform focused on image understanding, scene reconstruction, and automated media generation. This is a backend-heavy role requiring strong expertise in system design, asynchronous processing, and scalable API development.

You will work closely with AI/ML, frontend, and DevOps teams to deliver high-performance systems that power object detection, segmentation, and 3D reconstruction pipelines.

Key Responsibilities:

- Design and develop scalable backend services and APIs using FastAPI

- Build modular,maintainable systems with clear service contracts and abstractions

- Implement asynchronous processing pipelines for compute-heavy AI workloads

- Design and manage job queues (Celery, RQ, or similar) and integrate Redis

- Handle long-running and GPU-based tasks- Work with PostgreSQL and integrate object storage (S3 or equivalent)

- Integrate and productionize ML models

- Optimize inference pipelines for latency, batching, and throughput

- Ensure system reliability with retries, fallbacks, and monitoring

- Collaborate with Data Science, Frontend, and DevOps teams

Required Skills:

- 5+ years of Python development experience

- Hands-on experience with FastAPI and REST APIs

- Strong understanding of async programming and scalable systems

- Experience with Redis and queue systems (Celery, RQ, Kafka)

- Strong PostgreSQL experience

- Experience with Docker (mandatory); Kubernetes is a plus

- Familiarity with AWS, GCP, or Azure

Good to Have:

-Exposure to AI/ML pipelines (YOLO, DETR, SAM, etc.)

- Experience deploying ML models in production

- Understanding of GPU workloads and optimization

- Background in image/video processing or real-time systems

What We’re Looking For:

- Strong problem-solving and system design mindset

- Ability to handle real-world scale and unstructured data

- Experience in AI-integrated backend systems

Benefits:

• Flexible schedule
• Health insurance
• Leave encashment
• Provident Fund

Key Responsibilities

• Develop high-quality, scalable, and robust web applications using Angular (latest version) and modern front-end technologies.
• Design, code, debug, test, and optimize user-facing features with a focus on responsiveness, maintainability, and performance.
• Collaborate with backend developers, UX/UI designers, and cross-functional teams to deliver high-quality solutions.
• Ensure adherence to coding standards, application security practices, and cross-browser compatibility.
• Perform unit testing and integration testing to identify and resolve bugs, coding errors, and technical issues.
• Proactively identify opportunities for system improvements and performance optimization.
• Stay updated with the latest trends, tools, and best practices in Angular and front-end development.
• Manage project lifecycle activities including milestone tracking, task coordination, and progress reporting.

Desired Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
• 4–6 years of strong software development and engineering experience with expertise in front-end technologies.
• Strong proficiency in Angular, JavaScript, TypeScript, HTML5, and CSS3.
• Hands-on experience with RxJS, NgRx (or similar state management libraries), and RESTful API integration.
• Good understanding of UI/UX principles and user-centric design practices.
• Experience working with Git, JIRA, Confluence, and CI/CD pipelines.
• Strong knowledge of Agile development methodologies.
• Understanding of front-end performance optimization and security best practices.
• Experience with backend integration and API development will be an added advantage.
• Relevant Angular or related technology certifications preferred. 

Job Title: Agentic AI Intern (Full-Stack)

Location: Borivali, Mumbai (Onsite)

Position Type: Summer Internship

Job Overview

We are seeking a highly motivated and technically proficient Agentic AI Intern with a strong foundation in full-stack development. In this role, you will work at the intersection of modern web development and cutting-edge Artificial Intelligence, designing autonomous AI agents and integrating AI capabilities into robust applications. The ideal candidate is adaptable, language-agnostic, and eager to leverage modern AI tools to accelerate development velocity.

Key Responsibilities

• AI Agent Development: Assist in designing, building, and deploying autonomous AI agents and workflows.
• Full-Stack Development: Support backend architecture design and frontend interface development across various modern stacks.
• API & Tool Integration: Connect external LLM APIs and manage database configurations.
• Workflow Automation: Actively integrate modern AI-assisted development tools (such as Cursor, Windsurf, or GitHub Copilot) into your daily coding workflow.
• Technical Collaboration: Collaborate with the technical team to build prototypes and maintain clean, documented code.

Technical Requirements

• Backend Ecosystems: Solid foundational knowledge in backend development, with a primary preference for Python or Node.js.
• Frontend Frameworks: Competency in building modern user interfaces (experience with React, Next.js, or similar frontend technologies).
• Adaptability & Emerging Tech: High adaptability and a strong willingness or curiosity to work with high-performance ecosystems like Go, Rust, or other modern stacks as project demands evolve.
• AI Tooling & APIs: Familiarity with utilizing AI APIs and developing within modern AI-first IDEs.

Eligibility & Location Criteria

• Education: Open to current final-year students (looking for a Summer Internship) and recent graduates in CS, IT, or related engineering disciplines.
• Geographic Requirement: Candidates must reside along the Western Line within a 25km radius of Borivali to ensure a sustainable daily onsite commute.
• Competencies: A strong problem-solving mindset, a self-driven approach to learning new technologies quickly, and clear technical communication skills.

Why this role exists

Our infrastructure footprint is growing faster than our headcount, and we believe most of that

gap should be closed by automation and AI agents — not by hiring more humans to do toil. We

need someone early in their career who treats manual work as a bug, ships scripts and agents

instead of tickets, and wants to grow into deeper ownership over the next two years.

You will not be the most senior person on the team. You will be the one who multiplies the team.

What you'll own

In your first 1 months

• Take ownership of one slice of our CI/CD pipeline and make it measurably

faster, more reliable, or cheaper. We expect a number on a dashboard to move.

• Build at least three internal automations that replace manual ops toil —

using AI agents (Claude Code, agentic CLIs, scripted LLM workflows) as your force

multiplier.

• Be the first responder for a defined set of alerts. Write the runbooks. Drive

the alert volume down.

• Support senior engineers on AI/ML infrastructure (GPU nodes, inference

services, model deployment) — observe, document, and gradually take on contained

changes under review.

By 3 months you should be

• The go-to person for at least two production systems.

• Shipping routine infrastructure changes without needing senior review.

• Treating "manual" as a code smell.

Required (we will reject without these)

• 0–3 years hands-on experience with one major cloud (AWS, GCP, or

Azure — one is fine, depth beats breadth).

• Fluent in Linux command line, bash, and at least one scripting language

(Python or Go preferred).

• Have shipped something to production that real users hit. A side project

counts; a graded coursework lab does not.

• Comfortable with Docker — you can explain what an image vs. a

container is and why it matters.

• Working knowledge of networking fundamentals: DNS, HTTP/HTTPS,

TLS, ports, basic subnets — enough to debug "it works on my machine."

• Git fluency: branches, merges, rebases, conflict resolution.

• CI/CD pipelines — you have authored or substantially modified pipelines

in GitHub Actions, GitLab CI, ArgoCD, Jenkins, or similar. Not just "I clicked Re-run."

• Kubernetes basics — kubectl for real work, can read pod logs,

understand deployments and services, can debug a CrashLoopBackOff without

panicking. You do not need to have run a cluster; you do need to have lived inside one.

• Active user of AI coding agents (Claude Code, Cursor, Copilot, agentic

CLIs, etc.). You should be able to walk us through specific tasks where they made you

faster, and specific tasks where they failed you and how you noticed. "I have tried it" is

not enough.

Bonus (real plus, not required)

• Infrastructure as Code: Terraform, Pulumi, or Ansible.

• Observability: Prometheus/Grafana, Datadog, OpenTelemetry, any APM.

• Have built or extended an LLM-based agent — a custom MCP server, a

scripted multi-step workflow, an internal tool that calls models in a loop. Anything beyond

chat-with-Claude.

• Exposure to GPU workloads, model serving (vLLM, Triton, TGI, etc.), or

ML pipelines.

What we don't care about

• Whether your degree is in CS — or whether you have a degree at all.

• Brand-name companies on your resume.

• Certifications. They are fine. They do not substitute for having shipped.

How we work

• We default to automation. If you do something manually twice, the third

time you script it or hand it to an agent.

• AI agents are part of the workflow, not a novelty. Expect interview

questions about exactly how you use them — and where you have caught them being

wrong.

• Small, reversible changes beat big-bang rollouts.

• Postmortems are blameless and written down.

• We push back on each other. If you only execute, you will be unhappy

here.

How to apply

Send:

• Your resume.

• A short note (≤200 words) describing one infra or automation problem you

solved, and how AI agents factored in — or did not, and why. We read these. Generic

notes get rejected.

Internal note — delete before posting externally

• Comp band, location policy, team name, and reporting line marked

[CONFIRM] need to be filled in before this goes external.

• The Required list is intentionally tight: CI/CD and Kubernetes basics

promoted from bonus. Expect this to filter ~80% of typical junior DevOps applicants. The

remaining pool will skew toward people who have actually shipped infra at a startup, not

bootcamp grads or pure cloud-cert holders.

• IaC, observability, agent-building, and GPU/ML serving stay as bonus.

Promoting any of these to required at 0–3 yrs collapses the pool to near-zero or forces

hiring senior people at junior comp. If you want IaC required, re-level this to mid (3–5

yrs) and raise the band.

• Screening implication: the resume screen should explicitly check for

CI/CD pipeline authorship and any K8s-touching production work. If neither is on the

resume, reject at screen. Do not waste interview slots.

• Pipeline watch: if fewer than ~15 qualified resumes after 2 weeks of

active sourcing, the first thing to relax is the AI-agent-fluency bar (move to bonus and

screen for it in interview instead). Do not relax the "shipped to production" requirement

— that is the load-bearing filter.

Job Title : Senior Node.js Developer (SDE 2)

Experience : 5+ Years

Location : Bengaluru (Whitefield)

Work Mode : Hybrid (3 Days WFO)

Openings : 2

Notice Period : Immediate–20 Days Preferred

Role Overview :

We are looking for an experienced Senior Node.js Developer (SDE 2) professional with strong expertise in building scalable backend applications, microservices, and distributed systems in Agile environments.

Mandatory Keywords :

Node.js, JavaScript, TypeScript, GraphQL, Microservices, Cloud, REST APIs, Docker, Kubernetes, Redis, System Design.

Key Responsibilities :

• Design, develop, and deploy scalable backend systems using Node.js & TypeScript.

• Build REST APIs and GraphQL services.

• Develop secure, reusable, and high-performance applications.

• Work on microservices, cloud platforms, and production support.

• Follow best practices including TDD, testing, and DevOps processes.

• Mentor team members and contribute to technical excellence.

Mandatory Skills :

• 5+ years of software development experience.

• Strong hands-on experience in Node.js, JavaScript, TypeScript.

• Experience with Express.js/Koa/Sails.js.

• GraphQL, REST APIs, Microservices

• AWS/Azure/GCP Cloud

• Docker, Kubernetes, Redis

• Strong understanding of distributed systems, Git, and DevOps.

Good to Have :

Kafka, RabbitMQ, Apollo Federation, New Relic, Datadog, Splunk, React.js/Next.js, Jest/Mocha/Cucumber

Interview Process :

• L1 – Technical
• L2 – Coding
• L3 – System Design (HLD + LLD)

Title: Sr. Python Developer (Full-Stack & AI)

Location: Onsite – Mumbai, Maharashtra (Western Line)

Experience: 2 - 5+ years

Pay: ₹400,000.00 - ₹600,000.00 per year

Joining: Immediate

About the Role

We are building AI products for enterprise use and need a Senior Python Developer for our core team. You will be responsible for the full-stack architecture—designing both the backend and frontend. We want someone who works smart by using AI tools to build fast, but also has great skills to code manually when the logic is complex or needs high precision.

Key Responsibilities

• Build and maintain full-stack applications using Python and Django.
• Use AI-powered IDEs and development tools as your primary method to ship code quickly.
• Perform manual coding and deep debugging for complex logic that AI cannot handle alone.
• Collaborate with AI/ML teams to put machine learning models into production.
• Design how the entire system (frontend, backend, and database) works together.
• Optimize the application for speed, security, and reliability.
• Participate in technical discussions and help make architecture decisions.

Required Skills & Experience

• Minimum 5 years of professional Python development experience.
• Strong expertise in Django (Primary) and experience with FastAPI or Flask.
• Full-stack capability: Ability to design and build both the frontend and backend.
• Modern Tooling: High proficiency in using AI-powered IDEs and AI dev-agents to speed up your workflow.
• Manual Coding: Strong ability to write clean, manual code for complex backend logic.
• Solid understanding of databases like PostgreSQL, MySQL, or Redis.
• Familiarity with Cloud platforms (AWS/Azure/GCP) and Docker.
• Experience or strong interest in AI/ML pipeline integration.

Good to Have

• Experience with React or Next.js for the frontend.
• Exposure to message brokers like RabbitMQ or Kafka.
• Knowledge of Vector databases or RAG pipelines.
• Experience with CI/CD and basic DevOps.

Experience:

• Total: 3 years (Required)
• Python/Django: 3 years (Required)

Work Location: In person (Borivali, Mumbai)