298 Google Cloud Platform (GCP) Jobs in Bangalore (Bengaluru) | Google Cloud Platform (GCP) Job openings in Bangalore (Bengaluru)

About the role

We are hiring a Principal Engineer to own the hardest technical problems in our product and see them through from first sketch to stable production. You will set technical direction, design systems that scale, and raise the engineering bar through your own work and the people around you. This is a hands-on leadership role: you write code, review designs, and ship.

What will you do?

You will own outcomes, not just tasks. Expect to spend your time on the following.

• Own projects end to end. Take an ambiguous problem, shape the requirements, design the solution, break down the work, deliver it to production, and stay accountable for how it runs afterwards.

• Lead system design. Author and review architecture for services, data pipelines and integrations, with clear trade-offs on scale, latency, cost, consistency and reliability.

• Write and review critical code. Build the hardest components yourself, and set standards for code quality, testing and maintainability through code and design reviews.

• Own deployment and operations. Design CI/CD, infrastructure and release strategies. Drive observability, on-call readiness, incident response and post-incident learning.

• Solve hard problems. Debug production issues across the stack, and find root causes in performance, concurrency, data and scaling problems.

• Mentor and multiply. Coach senior and junior engineers, grow future tech leads, and make the whole team faster and more confident.

• Partner across functions. Work with product, design, data and business teams to turn goals into technical plans, and to say no or reshape scope when needed.

• Shape technical strategy. Guide build-versus-buy decisions, manage tech debt, evaluate new technologies, and contribute to the engineering roadmap.

• Raise the bar. Help define engineering practices, hiring standards and culture, and take part in interviewing.

What are we looking for?

• Bachelor's degree in Computer Science or a related field, or equivalent practical experience.

Core engineering

• 10+ years of professional software engineering, with a track record of shipping and running production systems.

• Strong computer science fundamentals: data structures, algorithms and complexity, operating systems, networking, databases and concurrency.

• Fluency in at least one major backend language (for example Python, Go, Java, or Node.js/ TypeScript) and the ability to pick up others quickly.

• Deep knowledge of relational and NoSQL data stores: schema design, indexing, transactions, query tuning and replication.

System design and problem solving

• Proven ability to design distributed systems that are scalable, fault tolerant and cost aware, and to explain the trade-offs clearly.

• Experience with APIs, event-driven and asynchronous architectures, queues, caching and service-to-service communication.

• A structured approach to ambiguous problems: break them down, test assumptions, decide with incomplete data, and measure results.

• Strong debugging instincts, including performance profiling and production troubleshooting.

Delivery and operations

• Have led at least two significant projects from inception to production, including planning, milestones, risk management and launch.

• Hands-on experience with deployment: CI/CD pipelines, containers (Docker, Kubernetes), a major cloud (AWS, GCP or Azure), and infrastructure as code.

• Practical experience with monitoring, logging, alerting, SLOs and incident management.

• Habit of writing tests and automation, and of leaving systems more reliable than you found them.

Leadership and communication

• Experience leading engineers without formal authority, through influence, mentoring and clear technical writing.

• Excellent written and verbal communication: design docs, RFCs and concise updates to non-technical stakeholders.

• Ownership mindset, sound judgment on priorities, and comfort working in a fast-moving environment.

Nice to have

• Experience in fintech, lending or another regulated, data-heavy domain.

• Exposure to AI/ML or LLM-based systems in production: model serving, evaluation, retrieval, and cost and latency management.

• Deep experience with data engineering: streaming, batch pipelines, warehouses or search systems.

• Security and compliance awareness: authentication, encryption, audit trails, secure SDLC.

• Experience with multi-tenant SaaS, high-throughput systems or zero downtime migrations.

• Open-source contributions, conference talks, or technical writing.

• Experience scaling an engineering team or helping set up hiring and onboarding practices.

Responsibilities:

• Add a new feature to existing infrastructure platforms.
• Collaborate across teams and lead technical discussions with clients and internal teams.
• Mentor junior team members through mob-pairing/1:1 pairing sessions.
• Adapt to different roles and technologies as project needs evolve.
• Proactive mindset with excellent client communication, collaboration, and writing skills.
• Use methodologies like Agile and Lean to manage projects and deliverables.
• Document technical solutions and knowledge for team reference.
• Stay current with industry trends and emerging technologies.

Requirements:

• Experience with managing large-scale infrastructure systems.
• Experience as a reliability engineer is good.
• Proficiency in at least one programming language.
• Good understanding of software delivery principles.
• Ability to adapt to different roles and technologies when needed

Required Technical Skills:

• You have spent some time building software systems or self-service systems for internal teams.
• You have a good understanding of Linux, software-defined, and cloud networking.
• You have work experience in configuration management and using tools like Ansible and Chef.
• You must have a good understanding of continuous integration and continuous delivery concepts, not just tools.
• Experience with tools like Jenkins, GitHub Actions, GitLab CI, etc. is required.
• It would be a plus if you have worked with GitOps tools like Argo CD or Flux CD.
• You are familiar with the cloud-native ecosystem and tools like Prometheus, OpenTelemetry, and Envoy.
• In-depth understanding of containers and container orchestrators like Nomad, Kubernetes, etc.
• You should deeply understand managing and organizing infrastructure as code and have worked with tools such as Terraform, Pulumi, CloudFormation, and AWS CDK.
• You are familiar with at least one primary cloud provider, such as Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure.
• You understand observability well and can collaborate with dev teams to improve their observability systems.
• You have a good understanding of the principles of distributed systems.
• You understand how SQL and NoSQL databases work and what is needed to manage them.
• You have familiarity with basic cloud security.

Job Summary

We are looking for an experienced DevOps Engineer with strong hands-on expertise in GitHub Actions, Harness CI/CD, Google Cloud Platform (GCP), and Microsoft Azure. The candidate will be responsible for designing, implementing, and maintaining CI/CD pipelines, automating cloud infrastructure deployments, and improving application delivery through DevOps best practices.

Key Responsibilities

• Design, develop, and maintain CI/CD pipelines using GitHub Actions and Harness.
• Implement automated build, test, deployment, and release workflows.
• Manage and support cloud infrastructure across GCP and Microsoft Azure.
• Configure GitHub Actions workflows, reusable workflows, secrets, runners, and deployment environments.
• Develop and manage Harness pipelines for continuous integration, continuous delivery, and automated deployments.
• Automate infrastructure provisioning using Terraform and Infrastructure as Code (IaC) practices.
• Work with containerization technologies such as Docker and Kubernetes.
• Deploy and manage applications on GCP services such as GKE, Compute Engine, Cloud Storage, and Cloud Run.
• Work with Azure services such as Azure Kubernetes Service (AKS), Azure Virtual Machines, Azure Storage, and Azure networking.
• Implement secure credential management, access controls, and cloud security best practices.
• Integrate automated testing, code quality checks, vulnerability scanning, and security gates into CI/CD pipelines.
• Monitor deployments, troubleshoot pipeline failures, and resolve build and release issues.
• Collaborate with development, QA, security, and infrastructure teams to improve deployment efficiency.
• Implement logging, monitoring, rollback strategies, and deployment governance.
• Support production releases, incident troubleshooting, and continuous improvement of DevOps processes.

Mandatory Skills

• Strong hands-on experience with GitHub Actions.
• Practical experience with Harness CI/CD.
• Good experience with GCP and Microsoft Azure cloud platforms.
• Strong understanding of CI/CD concepts, build automation, and release management.
• Experience with Git, branching strategies, pull requests, and version control.
• Scripting knowledge in Python, Bash, or PowerShell.
• Experience with Terraform or other Infrastructure as Code tools.
• Understanding of Docker and Kubernetes.
• Knowledge of cloud IAM, secrets management, networking, and security best practices.

Job Description: DevOps Engineer – Terraform + GCP

Experience: 5+ Years

Locations: Bangalore / Hyderabad

Key Responsibilities:

• Set up, configure, and manage cloud infrastructure on Google Cloud Platform (GCP).
• Develop and maintain Infrastructure as Code (IaC) using Terraform.
• Handle infrastructure provisioning, deployment, and configuration management.
• Perform product installation, setup, configuration, and environment readiness.
• Manage GCP services, compute instances, networking, storage, and access permissions.
• Troubleshoot infrastructure, installation, and deployment-related issues.
• Automate infrastructure provisioning and repetitive operational tasks using scripts.
• Monitor infrastructure performance, availability, and reliability.
• Collaborate with development and operations teams to support deployments and production environments.

Mandatory Skills:

• Hands-on experience with Terraform.
• Strong experience with Google Cloud Platform (GCP).
• Infrastructure setup and provisioning.
• Product installation and configuration.
• Cloud infrastructure troubleshooting.

Preferred Skills:

• Linux administration and shell scripting.
• CI/CD tools and deployment automation.
• Cloud monitoring and logging.
• Infrastructure maintenance and operational support.

Required Experience: 5+ years in DevOps / Cloud Infrastructure.

🚀 Hiring: Senior GCP Data Engineer

We are looking for experienced Senior Data Engineers with strong hands-on expertise in Google Cloud Platform (GCP), Python, PySpark, and SQL. Candidates with team lead experience will be preferred.

📌 Job Details:

• Role: Senior GCP Data Engineer
• Experience: 8+ Years
• Budget: Up to ₹30 LPA
• Location: Bangalore / Hyderabad
• Relocation: Candidates from Chennai and Pune willing to relocate are welcome.
• Notice Period: Immediate to 15 days
• Interview Process: L1 – Virtual | L2 / DM – Face-to-Face (F2F)

💻 Required Technical Skills:

• Strong hands-on experience with GCP data engineering.
• Excellent proficiency in Python, PySpark, and SQL.
• Experience in designing, developing, and optimizing data pipelines.
• Good understanding of ETL/ELT processes and large-scale data processing.
• Experience working with cloud-based data platforms and data warehousing.
• Strong analytical, problem-solving, and communication skills.

⭐ Preferred Skills:

• Previous experience as a Technical Lead or leading a data engineering team.
• Knowledge of GCP services such as BigQuery, Dataproc, Dataflow, and Cloud Storage.

Job Title: GCP Data Engineer

Experience: 6–8 years

Location : Bangalore

What are they looking for?

They need a Google Cloud Platform (GCP) Data Engineer who can build and maintain data pipelines, process large volumes of data, and manage data storage using Google Cloud services.

The candidate should have hands-on experience with batch and real-time data processing, ETL workflows, and cloud data warehousing.

Mandatory / Core Skills

• Google Cloud Platform (GCP)
• Google Cloud Dataflow
• Pub/Sub
• Apache Beam
• BigQuery
• Cloud Storage / Bigtable
• Cloud Composer (Apache Airflow)
• ETL / data pipeline development
• Apache Spark / Hadoop using Dataproc

Supporting Skills

• Cloud Data Fusion
• NoSQL databases
• Data quality and governance
• Data security, access controls, and encryption
• Batch and real-time streaming
• Preparing datasets for BI, analytics, and machine learning

GCP Data Engineer

Job Description

Experience: 4-10 Years Location: Bangalore, India Employment:

Role Overview

We are seeking a GCP Data Engineer to design, build and maintain data systems on Google Cloud Platform. The role focuses on building pipelines with BigQuery, Dataflow and Pub/Sub, managing cloud storage, and enabling real-time data processing for fast, reliable analytics.

Key Responsibilities

• Design, develop and maintain scalable batch and real-time data pipelines on GCP.

• Build ETL/ELT pipelines with rollback strategies, bad-record handling and performance optimization.

• Design end-to-end data integration flows across systems.

• Design scalable fact/dimension schemas in cloud data warehouses.

• Handle structured, semi-structured and unstructured data at scale.

• Implement data quality checks, security and compliance policies; protect sensitive information.

• Optimize data systems by identifying bottlenecks, tuning queries and adopting new technologies.

• Collaborate with data scientists, analysts and business stakeholders to deliver tailored data solutions.

Technical Skills

• GCP Services: Cloud Run functions, Cloud Scheduler, Workflows, Pub/Sub, GCS, Dataflow, BigQuery, Cloud Build.

• Programming: Strong SQL / PL-SQL, Python and object-oriented languages (Java, Python); API development.

• CI/CD: Deployment using GitHub Actions and Jenkins.

• Data Modelling: Top-down and bottom-up database design, data masking, normalization, denormalization, dimensional modeling.

• Big Data & Streaming: Streaming architectures, NoSQL stores and key-value databases under high concurrency and volume.

Qualifications

• Bachelor's degree in Computer Science, IT, Engineering or a related field.

• 4-10 years of data engineering experience with hands-on GCP delivery.

• Strong problem-solving, communication and stakeholder management skills.

• GCP Professional Data Engineer certification preferred.

Sourcing Preference

• Priority 1: Internal profiles (TCSers).

• Priority 2: If no suitable internal profile is identified, external candidates available for immediate joining.

Desirable Skills:

Keyword:

Skills: Digital : Python~Digital : NOSQL~Digital : Google Cloud

Experience Required: 6-8

Job Title : Senior Data Engineer – GCP & Apache Spark

Job Details :

• Number of Positions : 3
• Employment Type : Contract-to-Hire (C2H)
• Experience Required : 5 to 8 Years
• Location : Manyata Tech Park, Bengaluru
• Work Mode : Hybrid – 3 Days in Office per Week
• Preferred Notice Period : Immediate to 15–20 Days
• Project Duration : Initially 6–8 months, with a strong possibility of extension for long-term projects
• Relocation : Candidates from outside Bengaluru can apply if they are willing to relocate.

Role Overview :

We are looking for experienced Senior Data Engineers with strong expertise in Google Cloud Platform (GCP), Apache Spark, BigQuery, and SQL to design, develop, and maintain scalable data pipelines and distributed data processing solutions.

The ideal candidate should have hands-on experience with cloud-based data engineering, end-to-end pipeline architecture, system design, performance optimization, debugging, and CI/CD practices.

Mandatory skills :

Apache Spark (PySpark / Scala), SQL, GCP, BigQuery, GCP Dataproc, Data Pipelines, System Design, CI/CD, Debugging & Problem-Solving.

Key Responsibilities :

• Design, develop, and maintain scalable data pipelines using Apache Spark, PySpark, and/or Scala.
• Build and optimize batch and distributed data processing workflows on GCP.
• Work extensively with BigQuery for data transformation, validation, analytics, and query optimization.
• Develop and maintain data workflows using GCP services, including Dataproc, BigQuery, and Cloud Storage.
• Design end-to-end data pipeline architectures with a focus on scalability, reliability, and performance.
• Write and optimize complex SQL queries for large-scale datasets.
• Troubleshoot and resolve data processing issues, pipeline failures, and performance bottlenecks.
• Implement CI/CD practices for data engineering workflows, testing, and deployments.
• Monitor pipeline performance and identify opportunities for continuous improvement.
• Collaborate with cross-functional teams to understand requirements and deliver reliable data solutions.
• Participate in code reviews, testing, production deployments, and production support.

Mandatory Skills :

• Strong hands-on experience with Apache Spark, including PySpark and/or Scala.
• Strong SQL skills and experience working with large-scale datasets.
• Hands-on experience with Google Cloud Platform (GCP).
• Practical experience with BigQuery and data warehousing concepts.
• Working knowledge of GCP Dataproc.
• Strong understanding of data pipelines, end-to-end workflows, and system design.
• Practical experience with CI/CD and deployment processes.
• Excellent debugging, troubleshooting, and problem-solving skills.

Preferred Skills :

• Experience with Apache Airflow, Google Cloud Composer, or similar orchestration tools.
• Knowledge of Kafka or other streaming and messaging technologies.
• Proficiency in Python for data engineering and automation.
• Experience with Git-based development workflows.
• Knowledge of Linux/Unix environments and shell scripting.
• Familiarity with monitoring, logging, data quality, and governance practices.

Required Qualifications :

• 5 to 8 years of experience in Data Engineering, Big Data Engineering, or a related field.
• Proven experience developing and maintaining scalable data pipelines.
• Strong understanding of distributed data processing and cloud-based data architecture.
• Ability to troubleshoot complex technical issues and optimize pipeline performance.
• Strong communication, collaboration, and ownership skills.

Interview Process :

Round 1 : AI-Based Interview

• Candidates must complete the AI interview as soon as possible after receiving the invitation.

Round 2 : Virtual Interview Drive

• Interviews are planned for the upcoming drive; exact dates will be communicated separately.

Round 3 : Online Client Interview

• Shortlisted candidates will attend the online interview.
• Candidates must be available throughout the day on the scheduled interview date.

Principal Software Engineer

Location: Bangalore India

Department: AI Engineering / Quality Assurance

Experience Level: Mid to Senior

We are looking for a highly motivated Senior AI Test / Automation Engineer to design and scale automated validation frameworks for AI/ML models, LLM-based applications, and agentic systems. This role is critical to ensure that AI solutions meet enterprise standards for quality, reliability, safety, and compliance before and after production deployment.

Key Responsibilities

• Build and maintain AI test automation frameworks for pre-qualification and continuous validation of models and agent workflows
• Develop comprehensive test suites, including:
• Unit, integration, and end-to-end (E2E)
• Functional, regression, performance, and safety testing
• Validate AI system behavior, including:
• Non-deterministic LLM outputs
• Hallucinations and edge cases
• Multi-step agent decision-making
• Design and manage evaluation systems:
• Golden datasets
• Benchmarking pipelines (accuracy, latency, reliability)
• Automate testing within CI/CD pipelines for model updates, prompt changes, and tool integrations
• Implement observability and telemetry to enable traceability, monitoring, and audit readiness
• Collaborate cross-functionally with ML, MLOps, Product, and Security teams to define quality gates and release criteria
• Track and report quality KPIs, including test coverage, defect leakage, and system reliability
• Drive root-cause analysis and continuous improvement across the AI testing lifecycle

Required Skills

Core Engineering

• Strong programming skills in Python; familiarity with Bash, TypeScript, or Go
• Experience with test automation frameworks such as PyTest, Playwright, Selenium, or Cypress
• Proficiency in CI/CD tools (GitHub Actions, Jenkins, GitLab CI)
• Experience with cloud platforms (AWS, Azure, GCP) and containers (Docker, Kubernetes)

AI / ML & Agentic Systems

• Hands-on experience with LLM ecosystems (OpenAI, Anthropic, Bedrock)
• Familiarity with:
• RAG architectures and vector databases (Pinecone, Weaviate)
• Agent frameworks (LangChain, LlamaIndex, AutoGen)

AI Testing Techniques

• Experience with non-deterministic testing approaches (statistical assertions, tolerance thresholds)
• Knowledge of evaluation methods:
• LLM-as-a-judge
• BLEU, ROUGE, semantic similarity scoring
• Experience with prompt and agent regression testing
• Understanding of AI safety testing, including adversarial testing, bias/fairness validation, and jailbreak detection

Tooling (Preferred)

• AI testing & observability tools: LangSmith, TruLens, Arize, Weights & Biases
• Evaluation tools: DeepEval, Ragas, PromptFoo, Giskard
• Monitoring: Prometheus, Grafana, OpenTelemetry

Soft Skills

• Strong analytical and problem-solving skills
• Excellent communication and cross-functional collaboration
• Data-driven mindset with focus on quality KPIs
• Detail-oriented with a strong bias toward automation and scalability

Experience Requirements

• 7+ years in QA, SDET, or test automation engineering
• Proven experience building and scaling automation frameworks
• Hands-on experience with AI/ML systems or LLM-based applications
• Experience testing RAG pipelines or agentic workflows
• Owned end-to-end AI test strategy and architecture
• Defined quality metrics and release gates
• Delivered scalable validation pipelines for production AI systems
• Supported audit and compliance readiness

Preferred

• Experience in enterprise or regulated environments (SOC2, ISO 27001, etc.)
• Exposure to:
• Shift-left testing practices
• Production observability and monitoring
• Chaos or resilience testing

Senior-Level Differentiators

Education

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field

Nice-to-have:

• ISTQB certification
• Cloud/ML certifications (AWS, Azure, GCP)
• AI testing certifications

What Success Looks Like

• AI systems that are accurate, reliable, and safe
• Fully automated test pipelines integrated into CI/CD
• Measurable improvements in defect leakage and model quality
• Strong observability and auditability across AI systems
• Scalable validation frameworks supporting rapid AI innovation

Solid product experience and an educational background from Tier‑1 universities are preferred.

As a Senior AI Engineer, you will play a key role in designing and delivering highly scalable, next generation AI products within our AI stack. You will work in a technically rich environment with talented peers, contributing to product planning, design, and execution while influencing the evolution of Teradata’s AI capabilities. 

In this role, you will: 

• Design, develop, and maintain high quality systems, services, and applications with an emphasis on scalability, reliability, and performance. 
• Collaborate with cross-functional engineers and product partners to shape design and consistently deliver end to end features. 
• Build and integrate robust RESTful APIs, ensuring security, data consistency, and maintainability. 
• Work with SQL and NoSQL databases to implement efficient data models and service access patterns. 
• Apply and experiment with AI/ML technologies, including agentic AI and large language models (LLMs). 
• Use AI powered engineering tools to improve development quality, speed, and productivity. 
• Mentor engineers, supporting them in technical planning, implementation, and best practices. 
• Identify and resolve system performance bottlenecks, optimizing code, design, and infrastructure. 
• Write unit and integration tests and participate in code reviews to uphold engineering excellence. 
• Investigate production issues, ensuring timely and effective solutions. 
• Stay current with emerging trends in engineering, AI/ML, and cloud-native technologies. 

Who You’ll Work With 

You will be part of a high-performing engineering team building core components of Teradata’s AI platform. You will collaborate closely with other engineers, AI/ML specialists, product managers, cloud architects, and partner teams across the company. The role offers opportunities to contribute directly to Teradata’s AI product roadmap and technological direction. 

What Makes You a Qualified Candidate 

(Nonnegotiable qualifications) 

• Bachelor’s degree in Computer Science or equivalent from a recognized institution. 
• 5+ years of experience in backend services, distributed systems, or data platform development. 
• Strong proficiency in Java, Go, or Python for service development. 
• Good understanding of design principles, distributed system patterns, and service framework. 
• Hands-on experience designing and developing RESTful APIs. 
• Experience with SQL and NoSQL databases and data modelling. 
• Strong debugging, problem solving, and troubleshooting skills. 
• Experience with modern containerization and orchestration tools such as Kubernetes. 
• Knowledge of public cloud platforms. 
• Experience with AI productivity tools (e.g., GitHub Copilot). 
• Ability to work independently, drive workstreams, and deliver high quality outcomes. 
• Strong communication and collaboration skills. 

What You’ll Bring 

(Preferred qualifications) 

• Familiarity with messaging systems such as Kafka. 
• Experience experimenting with or implementing AI/ML technologies, Agentic AI, or LLMs. 
• A track record of influencing design decisions and driving engineering best practices. 
• The ability to mentor engineers and guide them through design, planning, and execution. 
• A proactive mindset and comfort working in fast paced, dynamic environments. 
• Curiosity, adaptability, and a passion for building impactful AI-driven products. 

Job Summary: We are seeking a highly skilled Full-stack Developer to join our dynamic team as a Delivery Module Lead. The ideal candidate will possess strong expertise in Python and front-end technologies, enabling them to design, develop, and maintain robust web applications. This role requires a proactive individual who can collaborate effectively with cross-functional teams to deliver high-quality software solutions that meet business needs.

• Proficient in Python programming language.
• Strong knowledge of front-end technologies such as HTML, CSS, and JavaScript.
• Experience with front-end frameworks like React, Angular, or Vue.js.
• Familiarity with back-end frameworks such as Django or Flask.
• Understanding of RESTful APIs and web services.
• Experience with version control systems, preferably Git.

Responsibilities:

• Architect, develop, and maintain backend components for our Risk Decisioning Platform.
• Build and orchestrate scalable backend services that automate, optimize, and monitor high-value credit and risk decisions in real time.
• Integrate with ORM layers - such as SQLAlchemy - and multi-RDBMS solutions (Postgres, MySQL, Oracle, MSSQL, etc. ) to ensure data integrity, scalability, and compliance.
• Collaborate closely with Product Team, Data Scientists, QA Teams to create extensible APIs, workflow automation, and AI governance features.
• Architect workflows for privacy, auditability, versioned traceability, and role-based access control, ensuring adherence to regulatory frameworks.
• Take ownership from requirements to deployment, seeing your code deliver real impact in the lives of customers and end users.

Requirements:

• Proficiency in Python, SQLAlchemy (or similar ORM), and SQL databases.
• Experience developing and maintaining scalable backend services, including API, data orchestration, ML workflows, and workflow automation.
• Solid understanding of data modeling, distributed systems, and backend architecture for regulated environments.
• Curiosity and drive to work at the intersection of AI/ML, fintech, and regulatory technology.
• Experience mentoring and guiding junior developers.

Technical Skills:

• Languages: Python 3.9+, SQL, JavaScript/TypeScript, Angular.
• Frameworks: Flask, SQLAlchemy, Celery, Marshmallow, Apache Spark.
• Databases: PostgreSQL, Oracle, SQL Server, Redis.
• Tools: pytest, Docker, Git, Nx.
• Cloud: Experience with AWS, Azure, or GCP preferred.
• Monitoring: Familiarity with OpenTelemetry and logging frameworks.

IMMEDIATE JOINERS ONLY

Key Responsibilities:

1                   Data Flow Mapping & Lineage

2                   Design and produce end-to-end data flow maps for critical data items – from market source/core systems, through Data Lake staging, zone 2 and consumption zone 3, to downstream reporting, dashboards and analytics use cases.

3                   Document data lineage and transformations for critical data elements identified in the Master Data Requirements exercise, ensuring traceability that is audit-defensible and supports regulatory, governance and AI-readiness needs.

4                   Map data availability by country/Data Lake against the Product Hierarchy (to profit-centre level), building the consolidated Commercial Data Landscape view of what exists, where it sits (source only, staging, or consumption) and what is not captured at all.

5                   Document cross-system dependencies and cross-border data flows, flagging data residency, privacy and regulatory considerations to the appropriate governance forums.

6                   Data Inventory, Data Model Alignment & Gap Analysis

•                    Own and mature the data asset inventory, catalogue and data dictionary aligned to the consolidated Master Data Requirements Template – resolving “Not Specified”, “TBD” and “validation required” availability statuses through structured validation with Market IT and Data Engineering.

•                    Align business data requirements to the conceptual and logical data model of the target Data Lakehouse, ensuring the dependency between data model design and lineage tracking of critical data items is explicitly documented.

•                    Perform gap and hydration analysis by market and product, quantifying the scale of data that must be brought into the Data Lakes and providing sizing input to the Data Foundation Lead, DAE architects and Data Engineering delivery plans.

•                    Contribute to the Data Consolidation Plan towards a single source of truth, including recommended sequencing based on business priority (Top 200 fields, Horizon 1–3 priorities).

•                    Stakeholder Engagement & Workshops

•                    Work hand-in-hand with the Data Foundation Lead, Data & Analytics Programme Manager, Data Engineers, DAE/infrastructure architects, Local Market IT and Business stakeholders (Regional and Market) as the connective tissue between business data needs and technical implementation.

•                    Plan and facilitate structured interviews and cross-functional validation workshops with business, technology and data stakeholders to corroborate actual operating data flows against documented processes – establishing a fact-based, evidence-backed view rather than relying on documentation alone.

•                    Translate ambiguous business asks into clear data definitions, mapping rules and acceptance criteria that Data Engineering can build against, and play back findings to senior stakeholders in clear, visual, decision-oriented formats.

•                    Manage competing priorities across multiple markets with tact, keeping momentum in an environment of constrained capacity and differing local system landscapes.

•                    Governance, Ownership & Documentation

•                    Produce and maintain the Data Ownership & Accountability Matrix – mapping data owners, stewards and custodians per data asset and highlighting ownership gaps for remediation.

•                    Classify data assets by sensitivity and business function, aligning to Data Protection Policy, PDPA and applicable regulatory expectations (e.g. MAS guidelines) in partnership with Risk & Compliance.

•                    Ensure all data flow maps, lineage records and inventory artefacts are version-controlled, audit-ready and handed over cleanly into BAU data governance processes.

•                    Produce source to Datalake mapping document and data catalogue for missing data elements to complete Datalake hydration

Key Skills

•                    Data flow mapping and lineage documentation – proven ability to draw clear, accurate source-to-consumption data flow maps across complex multi-system, multi-market landscapes.

•                    Data architecture and modelling – strong grasp of conceptual/logical data models, data lake/lakehouse zone architectures (staging, conformed, consumption), data marts and MDM concepts.

•                    Data inventory, catalogue, dictionary and metadata management; familiarity with lineage/catalogue tooling (e.g. Purview, Collibra) and diagramming tools (e.g. Visio, ErWin, Lucidchart).

•                    Hands-on data profiling and validation skills (SQL essential) to verify what actually exists in source systems and lake zones.

•                    Strong stakeholder management – this is critical: able to build trust and drive outcomes across regional leadership, market business teams, Market IT and engineering, and to facilitate effective cross-functional workshops.

•                    Insurance domain knowledge – ideally commercial and specialty lines, with an understanding of policy, claims, reinsurance and underwriting data.

•                    Data quality, governance and privacy concepts, including cross-border data considerations.

•                    Clear written and visual communication – able to make complex data landscapes understandable to executives.

Experience & Qualification Requirements:

•                    8+ years’ experience in data architecture, data business analysis or information architecture roles, with at least:

•                    3+ years documenting data flows, lineage or data landscapes across multi-system / multi-market environments.

•                    Experience in Insurance or Financial Services, ideally within data foundation, data lake or data governance programmes.

•                    Demonstrated delivery of data inventory / data mapping / current-state data landscape assessments involving both business and IT stakeholders.

•                    Relevant certification (e.g. DAMA CDMP, TOGAF, cloud data platform certifications) preferred.

We are looking for a Data Science & Machine Learning Senior Associate with 3–5 years of relevant experience in data science, machine learning, and analytics. The candidate will be responsible for developing predictive models, analyzing complex datasets, building scalable ML solutions, and supporting production-grade data science applications on cloud platforms.

• Develop and implement machine learning and predictive analytics models.
• Perform data analysis, statistical modeling, and optimization to solve business problems.
• Build demand forecasting and predictive models using time-series and other advanced techniques.
• Work with large datasets using Python, SQL, PySpark, and cloud-based data platforms.
• Develop and maintain scalable data pipelines for ML model development and deployment.
• Implement MLOps practices including model deployment, monitoring, retraining, and data-drift detection.
• Collaborate with software engineers, product teams, and business stakeholders to convert business requirements into analytical solutions.
• Validate models for accuracy, robustness, bias, and production readiness.
• Create meaningful visualizations and communicate analytical insights to technical and non-technical stakeholders.

• Python
• SQL
• Data Science & Machine Learning
• Predictive Modeling
• Statistical Analysis
• Machine Learning Algorithms
• Optimization Techniques
• Google Cloud Platform (GCP)
• BigQuery
• Dataflow
• Dataproc
• Data Fusion
• Cloud SQL
• Airflow
• PySpark
• PostgreSQL
• Terraform
• Tekton
• APIs
• MLOps

• Java

• Demand Forecasting
• Time-Series Analysis
• Neural Networks
• Ensemble Methods
• Support Vector Machines (SVM)
• Regression and Cluster Analysis
• ML Model Testing
• Bias Detection and Data Drift Monitoring
• Production ML Deployment
• QlikSense
• Automotive or Supply Chain Analytics

Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a related technical field.Master's degree in a relevant quantitative or technical field is preferred.

Job Description – Senior GCP Data Engineer

Position: Senior GCP Data Engineer

Experience: 8+ Years

Budget: Up to 30 LPA

Location: Bangalore / Hyderabad

Relocation: Candidates from Chennai / Pune willing to relocate are also welcome.

Notice Period: Immediate to 15 Days

Interview Process:

• Round 1: Virtual Interview
• Round 2 / DM Round: Face-to-Face Interview

Required Skills

• Strong hands-on experience in GCP Data Engineering.
• Good programming experience in Python.
• Strong experience with PySpark / Apache Spark.
• Proficiency in SQL and database concepts.
• Experience in developing and maintaining data pipelines.
• Good understanding of data processing, transformation, and integration.
• Experience in handling large-scale data processing.
• Strong problem-solving and debugging skills.
• Good understanding of cloud-based data engineering concepts.
• Experience in optimizing data pipelines for performance and scalability.

Preferred Skills

• Previous experience in a Lead Data Engineer role.
• Experience in technical leadership, mentoring, and guiding team members.
• Ability to collaborate with cross-functional teams and deliver data engineering solutions.

Roles & Responsibilities

• Design, develop, and maintain scalable data pipelines using GCP.
• Develop data processing and transformation workflows using Python and PySpark.
• Write and optimize SQL queries for efficient data processing.
• Build and maintain reliable data engineering solutions.
• Troubleshoot data pipeline issues and optimize performance.
• Ensure data quality, reliability, and scalability.
• Collaborate with stakeholders and team members to deliver project requirements.
• Lead and guide team members where applicable.
• Important: Candidates must have strong Senior Data Engineer experience. Lead experience is preferred but not mandatory.

At Shipthis, we are building a better future for freight forwarders by evolving traditional operations into fully digital, efficient, and scalable systems. We’re a fast-growing product company where every individual has the opportunity to take ownership, move fast, and create real impact. If you enjoy solving complex problems, shaping products from the ground up, and influencing technical direction, Shipthis is the place for you.

Learn more at www.shipthis.co

Role Overview

We are looking for an associate-level SecOps Engineer to support security operations, compliance, endpoint management, cloud infrastructure, and DevOps engineering. The role will work closely with the CTO/CISO and engineering team. Security and compliance are core responsibilities; when those priorities are lighter, the engineer will focus on CI/CD, infrastructure automation, reliability, monitoring, performance, and cloud cost optimization.

What You’ll be Doing

Security Operations

• Monitor infrastructure, application, and security alerts and assist with incident investigation.
• Review access controls, privileged accounts, service accounts, permissions, and periodic access reviews.
• Support infrastructure hardening, logging, monitoring, backup, recovery, and other security controls.
• Track security issues and corrective actions through closure.

Vulnerability Management

• Run and review application and infrastructure vulnerability scans.
• Maintain a vulnerability register and coordinate remediation with engineering teams.
• Support VAPT and penetration-testing exercises and validate closure of findings.
• Monitor dependencies, containers, operating systems, and cloud infrastructure for known vulnerabilities and patching needs.

Compliance & Governance

• Support ongoing ISO/IEC 27001, SOC 2, GDPR, customer-security, and internal-policy requirements.
• Maintain audit evidence, control registers, security policies, procedures, risk items, and remediation records.
• Assist with internal/external audits, vendor assessments, customer security questionnaires, and asset inventories.
• Maintain evidence for access reviews, vulnerability management, incidents, onboarding/offboarding, backups, and infrastructure changes.

MDM & Endpoint Security

• Administer the company MDM platform and enroll/manage company laptops, desktops, and mobile devices.
• Maintain device inventory and monitor endpoint compliance.
• Enforce approved controls such as disk encryption, screen locks, password requirements, patching, and endpoint protection.
• Support employee device onboarding/offboarding, approved application deployment, lost/stolen-device procedures, and remote wipe where authorized.
• Maintain endpoint security and MDM evidence required for audits and troubleshoot enrollment or policy issues.

DevOps, CI/CD & Cloud

• Maintain and improve CI/CD pipelines, deployment workflows, build times, caching, and rollback processes.
• Support production and non-production cloud infrastructure, networking, DNS, TLS certificates, IAM, and secrets.
• Automate repetitive deployment, infrastructure, security, and compliance tasks.
• Improve monitoring, logging, alerting, reliability, resource utilization, and cloud costs.
• Troubleshoot pipeline, deployment, and infrastructure issues and participate in root-cause analysis.

Required Fundamentals

• Basic knowledge of Linux, networking, HTTP/HTTPS, DNS, TLS, Git, Docker, cloud computing, APIs, and web applications.
• Understanding of IAM, MFA, least privilege, vulnerabilities/CVEs, encryption, logging, patching, and secrets management.
• Strong troubleshooting, ownership, attention to detail, and willingness to learn.

Desired Qualifications

• 1–2 years of experience with strong fundamentals are welcome.
• Basic scripting knowledge in Python, Bash, or similar.
• Interest in cybersecurity, cloud infrastructure, automation, and troubleshooting.
• Exposure to AWS/GCP/Azure, Terraform, GitHub Actions, Cloudflare, OWASP, vulnerability scanners, MDM, ISO 27001, or SOC 2 is a plus, not mandatory.

We Welcome Candidates:

• Who can join immediately
• Female candidates returning to work after a career break are strongly encouraged.

We are an equal opportunity employer and are committed to fostering diversity and inclusivity. We do not discriminate based on race, religion, color, gender, sexual orientation, age, marital status, or disability status.

Job Synopsys

Location: Bangalore

Job Type: Full-time, Permanent

Experience: 1-2 years

Industry: Software Product

Senior Data Engineer – PySpark & Oracle

Experience: 7+ Years

Location: Bangalore

Notice Period: Immediate to 10 Days

Key Skills:

• Strong expertise in Data Modeling, Data Design & Modernization
• Primary skills: PySpark, Oracle SQL/PLSQL
• Secondary skills: Python, ETL & Data Pipelines
• Experience with Kafka and Hadoop
• Exposure to AWS / Azure / GCP
• Good knowledge of Git and JIRA

Roles & Responsibilities:

• Design, develop, and modernize scalable data models and data architecture.
• Develop and optimize data processing solutions using PySpark and Oracle SQL/PLSQL.
• Build and maintain robust ETL workflows and data pipelines.
• Work with Kafka, Hadoop, and cloud platforms for data processing and integration.
• Perform data transformation, optimization, and performance tuning.
• Collaborate with technical teams on data design, development, testing, and deployment.

Role: Full Stack Engineer

Location: Hyderabad/Mumbai/Bangalore/Gurgaon

Required Experience: 4-7 years

Role Summary:

We are looking for Software Engineers with deep experience in building highly scalable and reliable enterprise applications. We are looking for engineers who have experience building cloud based/cloud native solutions from scratch. This includes demonstrable expertise in an enterprise friendly backend framework. We expect the engineer to work in a team consisting of Project Managers, Designers, Data Scientists and Software Architects. This is an exciting opportunity to work in a fast paced and innovative environment along with a group of world class and entrepreneurial professionals.

Responsibilities:

• Design and develop user-friendly web interfaces using HTML, CSS, and JavaScript.

• Utilize modern frontend frameworks and libraries such as React, Angular, or Vue.js to build dynamic and responsive web applications.

• Develop and maintain server-side logic using programming languages such as Java, Python, Ruby, Node.js, or PHP.

• Build and manage APIs for seamless communication between the frontend and backend systems.

• Integrate third-party services and APIs to enhance application functionality.

• Implement CI/CD pipelines to automate testing, integration, and deployment processes.

• Monitor and optimize the performance of web applications to ensure a high-quality user experience.

• Stay up-to-date with emerging technologies and industry trends to continuously improve development processes and application performance.

Qualifications:

• Bachelors/Masters in Computer Science or related subjects or hands-on experience demonstrating working understanding of software applications.

• Knowledge of building applications that can be deployed in a cloud environment or are cloud native applications.

• Strong expertise in building backend applications using Java/C#/Python with demonstrable experience in using frameworks such as Spring/Vertx/.Net/FastAPI.

 • Deep understanding of enterprise design patterns, API development and integration and Test-Driven Development (TDD)

• Working knowledge in building applications that leverage databases such as PostgreSQL, MySQL, MongoDB, Neo4J or storage technologies such as AWS S3, Azure Blob Storage.

• Hands-on experience in building enterprise applications adhering to their needs of security and reliability.

• Hands-on experience building applications using one of the major cloud providers, preferably GCP.

• Working knowledge of CI/CD tools for application integration and deployment.

• Working knowledge of using reliability tools to monitor the performance of the application.

 The Role 

As a **DevOps Engineer** you'll own the infrastructure and delivery backbone that 

keeps our platform running as we grow. You'll build the CI/CD, cloud infrastructure, and 

observability that let a small, fast-moving team ship confidently — and you'll keep our AI and 

data workloads reliable and affordable at scale. 

This is a hands-on role with real ownership: you won't be maintaining someone else's setup, 

you'll be shaping ours. You'll work closely with the backend, AI/ML, and data teams to make 

deployment boring, incidents rare, and scaling a non-event. --- 

What You'll Own 

**CI/CD & developer experience** 

- Build and maintain fast, reliable CI/CD pipelines so engineers ship multiple times a day with 

confidence. - Make the path from commit to production simple, safe, and repeatable, with sensible 

automated testing, rollbacks, and release controls. 

**Cloud infrastructure & IaC** - Own our cloud infrastructure (AWS/GCP) end to end, managed as code (Terraform or 

similar) — no click-ops. - Design for scale and cost-efficiency as store and conversation volumes grow. 

**Containers & orchestration** - Run our services on containers/Kubernetes: deployments, autoscaling, networking, and 

resource management. - Support the specific needs of AI/ML workloads, including GPU-backed inference and batch 

processing for the speech pipeline. 

**Reliability & observability (SRE)** - Own uptime, performance, and incident response — monitoring, logging, tracing, alerting, 

on-call, and blameless postmortems. - Define and defend SLOs; keep the platform dependable as it scales across clients. 

**Data & pipeline infrastructure** - Support the infrastructure behind large-scale, edge-to-cloud data movement and 

processing (audio ingestion, ASR/AI pipelines, analytics). - Keep data workloads reliable, performant, and cost-aware. 

**Security & compliance** - Bake security into the platform: secrets management, IAM/least-privilege, encryption in 

transit and at rest, network hardening, and vulnerability management. - Support compliance readiness (including India's DPDP Act and enterprise-client security 

requirements) for a product that handles sensitive customer conversations. 

**Cost & scale** - Own cloud cost visibility and optimization; make scaling decisions that balance reliability 

and spend. --- 

What You'll Bring - 6+ years in DevOps, SRE, platform, or infrastructure engineering, running production 

systems at meaningful scale. - Strong hands-on experience with a major cloud provider (**AWS or Azure or GCP**) and 

Infrastructure-as-Code (**Terraform** or equivalent). - Solid experience with **containers and Kubernetes** in production. - Experience building and owning **CI/CD** pipelines (e.g. GitHub Actions, GitLab CI, 

Jenkins, Argo, or similar). 

- Comfort with a scripting/automation language (Python, Go, or Bash) and a strong 

automation-first mindset. - Real experience with **observability** (Prometheus/Grafana, ELK, Datadog, 

OpenTelemetry, or similar) and running incident response / on-call. - A security-conscious approach — secrets, IAM, encryption, and least-privilege as defaults. - Startup temperament: ownership, pragmatism, and a bias to automate and ship. - Based in or willing to relocate to Bangalore, and up for an onsite/hybrid, in-person team. 

Bonus Points - Experience running **ML/AI or GPU workloads** in production (inference serving, batch 

pipelines, model deployment). - Experience with data-intensive infrastructure — streaming/queues (Kafka, SQS), data 

pipelines, or large object/audio storage. - Exposure to **edge devices / IoT fleets**, OTA updates, or high-volume device-to-cloud 

ingestion. - Experience with compliance/security frameworks (SOC 2, ISO 27001, DPDP). - FinOps / cloud cost-optimization experience. - Early-stage startup experience. --- 

Why Join - Own infrastructure that's already live with leading retail brands and growing fast — real 

scale, real impact. - Work across genuinely interesting workloads: speech AI, GPU inference, large-scale data, 

and edge-to-cloud ingestion. - Small team, high ownership, direct line to engineering leadership — your decisions ship. - Build the platform foundation of a category-defining product from an

GCP Data Engineering Lead

Experience: 9+ Years

Lead Experience: 2+ Years

Location: Bangalore / Hyderabad

Key Skills:

• Strong experience in GCP Data Engineering and BigQuery
• Hands-on experience with Oracle Exadata / PL-SQL
• Strong knowledge of PySpark / Scala and Python
• Experience with GoldenGate, Kafka and CDC
• Hands-on experience with Apache Airflow
• Good experience in CI/CD and DevOps practices
• Experience with Terraform / Infrastructure as Code
• Exposure to AI/LLM technologies and GenAI solutions
• Strong understanding of data architecture, ETL/ELT and data pipelines

Roles & Responsibilities:

• Lead the design and development of scalable GCP data engineering solutions.
• Design and implement batch and real-time data pipelines using BigQuery, PySpark, Kafka/CDC and Airflow.
• Work with Oracle Exadata/PL-SQL and GoldenGate for data integration and migration.
• Implement CI/CD pipelines and infrastructure automation using Terraform.
• Explore and integrate AI/LLM capabilities into data engineering solutions.
• Lead technical discussions, code reviews, solution design and mentor team members.
• Collaborate with business and technical teams to deliver high-quality data solutions.

About the Role

Currently, we are evolving our testing approach from a Selenium-based framework towards a comprehensive, multi-layered Test Pyramid model to continuously deliver reliable, high-quality software to the market.

We are looking for a passionate QA Automation Engineer who can contribute to building and enhancing our automation frameworks across web, API, and mobile applications.

Our goal is to move away from the traditional Ice Cream Cone testing approach and adopt a scalable Test Pyramid model that emphasizes efficient, maintainable, and reliable automated testing.

You will work closely with developers, product managers, and QA engineers to ensure product quality through effective test planning, automation, continuous testing, and systematic defect management.

Interview Process

This position will have an offline/in-person interview only at our Learnyst office. Remote/online interviews will not be conducted.

About Learnyst

We are a Nasscom 10K startup with many paying customers and great traction. We help educators teach online and sell courses through their own websites and mobile learning apps.

We are building Shopify for education. Our mission is to make quality education affordable, easily accessible, and engaging.

Nice, but What Do We Do?

We provide a complete technology solution that enables educators to sell courses through their online academies.

Our platform includes a website builder, course builder, virtual classroom interface for students, video encryption and streaming services, and almost everything required to launch an online learning academy.

Tech @ Learnyst

Learnyst is hosted on Google Cloud Platform (GCP) with an auto-scaling infrastructure. More than 10 lakh learners use Learnyst for streaming course videos and taking mock tests.

Our core backend server uses Ruby on Rails with MySQL as the database. We have architected Learnyst to be a fault-tolerant, loosely coupled, and scalable system.

Our QA team works across backend APIs, web applications, and mobile applications, focusing on test automation, continuous quality improvement, and reliable product releases.

Our QA Automation Tech Stack

• Programming Language: Java
• Web Automation: Selenium WebDriver, Playwright
• Mobile Automation: Appium
• BDD Framework: Cucumber
• Testing Framework: TestNG
• API Testing: REST Assured, Postman
• Build & Dependency Management: Maven
• Defect Management: Jira, HubSpot
• Version Control: Git
• Cloud Infrastructure: Google Cloud Platform (GCP)
• CI/CD & Reporting: Automated test execution, pipeline integration, and test reporting

Why Join Learnyst?

• Consistent performers will get stock options.
• Exposure to understanding market opportunities and contributing directly to company growth.
• Opportunity to work with a fast-growing EdTech startup.
• Gain hands-on experience in serving direct customers.
• Learn and grow through challenging technical opportunities.
• Work in an environment that encourages ownership, innovation, and continuous improvement.
• Food & Snacks: You’ll never have to worry about your hunger pangs. We provide food and snacks throughout the day.
• Every Wednesday, we have game nights and quarterly team outings.

Must-Haves

You will be a core member of the QA team, working on important features and helping us improve the reliability, scalability, and quality of our products.

The following skill sets are essential:

Technical Skills

• Strong programming and problem-solving skills, specifically in Java.
• Hands-on experience with Selenium WebDriver and web automation.
• Knowledge of Playwright for modern web application automation.
• Working knowledge of Appium for Android/iOS mobile application testing.
• Understanding of BDD using Cucumber, including feature files, scenarios, step definitions, and reusable automation components.
• Knowledge of TestNG and Maven.
• Understanding of API testing and RESTful services.
• Ability to design, develop, and enhance scalable, maintainable, and reusable test automation frameworks.
• Good understanding of algorithms, data structures, and object-oriented programming concepts.
• Familiarity with Git and CI/CD concepts.

Quality Engineering & Defect Management

• Effective test planning by understanding product requirements, user stories, and acceptance criteria.
• Ability to design and execute test cases covering positive, negative, edge, integration, and regression scenarios.
• Experience in testing backend APIs, web applications, and mobile applications.
• Ability to identify, reproduce, document, and track defects with clear steps, test evidence, and expected versus actual results.
• Understanding of defect severity, priority, impact analysis, and defect lifecycle management.
• Ability to collaborate with developers and product teams to investigate root causes and drive defects towards resolution.
• Experience in defect verification, regression testing, and validating fixes before release.
• Understanding of test reporting, release readiness, and quality gates.
• Interest in adopting the Test Pyramid approach by balancing unit, API/integration, UI, and end-to-end automation.

Mindset & Ownership

• Eager to learn, with a strong passion for quality engineering and technology.
• Ability to listen carefully, understand problems, and communicate effectively.
• Strong sense of ownership and accountability for deliverables.
• Ability to make informed decisions and discover practical solutions to challenging problems.
• Honest, dependable, and committed to consistently strong performance.
• Ability to work with tight yet realistic deadlines while understanding product strategy, market needs, and customer expectations.
• Willingness to collaborate with cross-functional teams and contribute to continuous process improvement.

Education & Experience

• Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
• Prior work experience is not a necessity.
• Personal projects, GitHub repositories, internships, or practical automation experience that demonstrate coding and testing skills are highly valued.

Interested in Joining Learnyst?

You can visit www.learnyst.com to learn more about our platform. Don’t forget to check out our customer testimonials.

If you are passionate about Java, test automation, and building reliable software, we would love to hear from you.

Talk to us and take the next step in your QA career with Learnyst!

Job Title: Senior AI/ML Engineer

Company: Timble Technologies Pvt. Ltd

Location: Gurugram (Hybrid)

Experience: 2 TO 5 Years

About Us

Timble Glance is a high-growth AI RegTech and B2B SaaS company catering to top-tier BFSI and enterprise clients. We build cutting-edge systems powering 30+ high-scale APIs for digital identity verification, fraud detection, document intelligence, and compliance automation.

Role Overview

We are looking for a hands-on Senior AI/ML Engineer to design, develop, and productionize high-throughput AI/ML and Generative AI systems. You will own the full lifecycle—from problem formulation and data pipelines to deep learning architectures, RAG systems, LLMOps, and model governance—delivering sub-second latency and high reliability across our enterprise products.

Key Responsibilities

·       Model Architecture & Deployment: Design, train, and deploy production-scale ML/Deep Learning and GenAI systems (computer vision, document intelligence, OCR, NLP, fraud risk classification, and LLM applications).

·       GenAI & LLM Solutions: Develop robust LLM workflows including prompt engineering, fine-tuning, RAG pipelines, semantic search, vector indexing (Pinecone/Milvus/Chroma), and safety guardrails.

·       Pipelines & Engineering: Build performant feature extraction and data pipelines; write modular, vectorized, production-grade Python (NumPy, Pandas) and advanced SQL.

·       MLOps & Monitoring: Establish end-to-end MLOps/LLMOps standards—model registries, CI/CD, experiment tracking, drift detection, A/B testing, latency optimization, and cost governance.

·       Responsible AI & Security: Ensure model decisions comply with enterprise data security, privacy standards, and auditability required by the BFSI sector.

·       Collaboration & Ownership: Translate complex business requirements into technical roadmaps, conduct rigorous code reviews, and mentor junior engineers.

Required Qualifications & Skills

·       Education: B.Tech / M.Tech in Computer Science, AI/ML, Mathematics, or a related field—Tier-1 institutes (IIT, IIIT, NIT) strongly preferred.

·       Experience: 2+ years of hands-on experience developing, deploying, and maintaining ML/Deep Learning or GenAI models in production environments.

·       GenAI & NLP Stack: Hands-on experience with LLMs, embeddings, RAG architectures, and frameworks such as LangChain, LlamaIndex, or Hugging Face.

·       Deep Learning Frameworks: Strong proficiency in PyTorch or TensorFlow, with deep knowledge of transformer architectures and modern NLP/CV models.

·       Software & Data Engineering: Expert-level Python skills (pytest, Git, OOP, asynchronous programming), solid SQL proficiency, and familiarity with data workflows.

·       Deployment & Cloud: Practical exposure to cloud platforms (AWS/GCP), containerization (Docker), API frameworks (FastAPI/Flask), and basic orchestration (Kubernetes).

Preferred Qualifications

·       Prior domain experience in Fintech, RegTech, Identity Verification (KYC/AML), Fraud Intelligence, or B2B SaaS.

·       Experience optimizing models for low latency and inference cost (e.g., ONNX, TensorRT, model quantization).

·       Familiarity with workflow orchestrators such as Airflow, Prefect, or Kubeflow.

GCP Data Engineer

Job Description

Experience: 4-10 Years Location: Bangalore, India Employment:

Role Overview

We are seeking a GCP Data Engineer to design, build and maintain data systems on Google Cloud Platform. The role focuses on building pipelines with BigQuery, Dataflow and Pub/Sub, managing cloud storage, and enabling real-time data processing for fast, reliable analytics.

Key Responsibilities

• Design, develop and maintain scalable batch and real-time data pipelines on GCP.

• Build ETL/ELT pipelines with rollback strategies, bad-record handling and performance optimization.

• Design end-to-end data integration flows across systems.

• Design scalable fact/dimension schemas in cloud data warehouses.

• Handle structured, semi-structured and unstructured data at scale.

• Implement data quality checks, security and compliance policies; protect sensitive information.

• Optimize data systems by identifying bottlenecks, tuning queries and adopting new technologies.

• Collaborate with data scientists, analysts and business stakeholders to deliver tailored data solutions.

Technical Skills

• GCP Services: Cloud Run functions, Cloud Scheduler, Workflows, Pub/Sub, GCS, Dataflow, BigQuery, Cloud Build.

• Programming: Strong SQL / PL-SQL, Python and object-oriented languages (Java, Python); API development.

• CI/CD: Deployment using GitHub Actions and Jenkins.

• Data Modelling: Top-down and bottom-up database design, data masking, normalization, denormalization, dimensional modeling.

• Big Data & Streaming: Streaming architectures, NoSQL stores and key-value databases under high concurrency and volume.

Qualifications

• Bachelor's degree in Computer Science, IT, Engineering or a related field.

• 4-10 years of data engineering experience with hands-on GCP delivery.

• Strong problem-solving, communication and stakeholder management skills.

• GCP Professional Data Engineer certification preferred.

Sourcing Preference

• Priority 1: Internal profiles (TCSers).

• Priority 2: If no suitable internal profile is identified, external candidates available for immediate joining.

Desirable Skills:

Keyword:

Skills: Digital : Python~Digital : NOSQL~Digital : Google Cloud

Experience Required: 6-8

Senior Software Engineer – Backend

Company: House of EdTech (Goenka Kachave LLP)

Location: Bangalore, Hybrid

Job Type: Full-Time

Experience: 5+ Years

About the Role

House of EdTech is looking for a Senior Software Engineer – Backend to design, develop, and scale high-performance backend services and APIs supporting products used by millions of learners.

You’ll work closely with Product, Frontend, Data, and Engineering teams while taking end-to-end ownership of backend features and contributing to system architecture and technical decisions.

What You'll Do

• Design and develop scalable backend services and REST APIs.
• Build reliable systems capable of handling high traffic and large data volumes.
• Own backend features from design and development through deployment and monitoring.
• Work with microservices, databases, and distributed systems.
• Identify and solve performance, scalability, reliability, and security challenges.
• Participate in system design and architecture discussions.
• Conduct code reviews and contribute to engineering best practices.
• Mentor junior and mid-level engineers.
• Monitor production systems and troubleshoot incidents.

What We're Looking For

• 5+ years of professional backend development experience.
• Strong hands-on experience with Java, Python, Scala, C++, or a similar language.
• Experience building and operating large-scale distributed systems.
• Strong understanding of REST APIs, microservices, and databases.
• Experience with cloud/infrastructure technologies such as GCP, Docker, or Kubernetes.
• Strong software engineering fundamentals, including security, reliability, testing, and code quality.
• Experience with system design, architecture, and technical decision-making.
• Strong communication and cross-functional collaboration skills.
• Experience mentoring engineers is a plus.

Why Join House of EdTech?

• Work on products impacting millions of learners.
• Solve challenging backend and scalability problems.
• Take significant ownership of architecture and engineering decisions.
• Opportunity to grow into technical leadership and architectural ownership.
• Work in a fast-growing technology environment.

Presales Engineer – Cloud & AI — Comprinno, Bangalore (3–5 yrs experience)

Role: Bridges Sales, Solution Architects, Data & AI, and Delivery teams — shaping technical solutions, driving discovery conversations, and translating customer needs into cloud/AI architectures.

Core responsibilities:

• Customer discovery workshops, cloud assessments, and migration readiness evaluations
• Cloud transformation consulting (migration, modernization, DevOps, security, DR) using AWS frameworks (MAP, WAFR, FTR)
• AI/GenAI solution consulting — identifying use cases for GenAI, AI Assistants, Agentic AI, conversational AI
• Building technical proposals, architecture diagrams, SOWs, RFP/RFI responses
• Supporting PoCs, demos, and technical validations
• Customer-facing engagement, thought leadership (blogs, webinars, case studies)
• Maintaining reusable presales assets and knowledge repositories
• Travel for customer meetings/workshops as needed

Must-have qualifications:

• Bachelor's in CS/IT/Engineering or related
• Strong AWS knowledge (compute, networking, storage, security, databases)
• Kubernetes, containerization, cloud-native architecture, DevOps, IaC (Terraform/CloudFormation)
• GenAI concepts: LLMs, prompt engineering, RAG, AI assistants, Agentic AI
• Familiarity with Bedrock, SageMaker, Amazon Q; LangChain, LangGraph, CrewAI, OpenAI/Anthropic APIs
• AWS Solutions Architect – Associate Certification (mandatory)
• Strong communication/stakeholder management

Nice-to-have: AWS specialty certs (Security, ML, Networking, DevOps Pro), compliance knowledge (ISO 27001, SOC 2, HIPAA), MBA, published thought leadership.

Are you looking to work in the cutting edge area of applying data-science to help global customers get a better insight into their health? If so, read on and apply.

Role Name: Senior Data Scientist

Science Team | Full-Time | In-Office | Bangalore

The Role

The Ultrahuman Science Team builds the algorithms behind the Ring, M1 CGM, blood and urine biomarkers, and Performance Lab assessments. We are hiring a Senior Data Scientist to own those algorithms end to end: from the raw sensor signal to a model that is shipped, monitored, and trusted in users' hands.

This is a build role with real scope. In a typical month you will improve a production algorithm, root-cause a metric users are complaining about, and stand up the data pipeline the next model needs. The common thread is ownership: you take a vague question and return a working answer, without waiting to be handed scope.

What You'll Do

·      Own algorithms end to end: sleep staging, activity detection, sensor-derived metrics, and health scores. You frame the problem, build the features, train and evaluate the model, and see it live

·      Ship models, not notebooks: you prove a change on our own cohort before it reaches users, and a model is done only when it runs in production and you can tell how it is behaving

·      Validate against reference standards: design evaluations against gold standards, reference devices, and study ground truth, and know when a result is real and when it is an artifact

·      Own the data layer: cohort extraction, feature pipelines, study data, and raw sensor data, so the next model starts from clean inputs

What This Looks Like in Practice

1. Improving production algorithms - Take an existing production model like sleep staging, root-cause the failure modes against reference data, and ship a fix you can defend with numbers.

2. Building new models - Train an activity classifier on raw sensor data, design the labeled data collection that expands it, and pick the operating point so false positives never erode trust.

3. Proving it before it ships - Run a new steps algorithm against reference-device cohorts, decide with data when it is ready, and monitor how it behaves after rollout.

Who You Are

The two things we can't coach

·      High ownership, end to end: you take a problem from a vague question to a shipped model without waiting to be handed scope, and you can point to something you owned from raw data all the way to production

·      Hungry for more scope: you have outgrown your current role and want problems biggerthan your title, with the technical depth to be trusted with them

Also important

·      You've worked with human health data: wearables, physiological signals, or clinical data.

If your experience is close but not exact, show us why you will ramp fast

·      You've built at a startup: or somewhere small enough that nobody handed you clean data, clear specs, or a mature ML platform

·      You work like it's 2026: coding agents and AI tooling are part of how you build every day, and you can tell which new capabilities are worth adopting

·      You communicate: you can explain a model and its limits to a product manager, an engineer, or a founder, and hold your own with our scientists Core Technical Skills

·      Languages and data: Python and SQL daily, comfortable working in a real codebase

·      Machine learning: PyTorch or TensorFlow, scikit-learn, and gradient boosting, with the judgment to know which the problem needs

·      Advanced machine learning: time series and sequence models, deep learning on continuous physiological signals, and ensembles

·      Statistics and evaluation: hypothesis testing, experiment and A/B design, model evaluation, and error analysis against a reference standard

·      Scale and cloud: Spark or equivalent on large datasets, and AWS, GCP, or Azure

·      Production ML and MLOps: training pipelines, model versioning, deployment, monitoring, and drift detection

·      LLMs and agentic systems: fine-tuning and serving models, building agentic pipelines, and using coding agents to move faster

Experience:

- 4 to 5 years building and shipping machine learning systems. We index on what you have shipped and on trajectory, not the exact number of years; if you are a little earlier but have clearly outgrown your current scope, we want to hear from you.

- Bachelor's or higher in engineering, computer science, statistics, or a related field.

How We Work and Who Thrives Here

- The Science team is small and moves fast, and much of the work has no precedent to copy.

- People do their best work here when they are energized by ambiguity, low on ego, quick to adopt a better idea no matter where it comes from, and comfortable owning something before anyone has told them how. If you need a mature data org, clean labelled datasets, and clear guardrails to thrive, this particular role will not be the right fit, and that is worth knowing up front.

What You'll Gain

·      Ownership of algorithms that hundreds of thousands of people see every morning

·      A dataset most scientists never get to touch: 100M+ nights of sleep and continuous physiological signals at scale

·      Direct collaboration with the engineering, product, and design teams building Ultrahuman

Senior Data Engineer – Ab Initio | GCP | Spark | Agentic AI

Location: Bangalore

Experience: 5+ Years

Role: Senior Data Engineer

Work Mode: Bangalore

Job Summary

We are looking for an experienced Senior Data Engineer with strong expertise in Ab Initio, GCP, Apache Spark, and Agentic AI. The ideal candidate will have hands-on experience designing and developing scalable data engineering solutions, building data pipelines, and working with modern cloud and AI technologies.

The candidate should be comfortable working across traditional enterprise data platforms and emerging Generative AI / Agentic AI solutions.

Key Responsibilities

• Design, develop, and maintain scalable and high-performance data pipelines using Ab Initio, Spark, and GCP services.
• Develop and optimize complex ETL/ELT workflows using Ab Initio.
• Build and maintain data processing solutions using Apache Spark / PySpark.
• Develop cloud-based data solutions on Google Cloud Platform (GCP).
• Work with GCP data services such as BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, or equivalent services.
• Perform data integration, transformation, cleansing, and validation.
• Optimize data pipelines for performance, scalability, reliability, and cost.
• Collaborate with data architects,
• 
  

Job Title: Automation Engineer – Watermelon Tool 

Experience: 6–7 Years

Location: Bangalore

Work Mode: Hybrid

Notice Period: Immediate Joiners (Apply only if you can join within 15 Days)

Key Responsibilities:

Design, develop, and maintain automated test scripts using the Watermelon automation tool.

Build and enhance automation frameworks for web, API, and enterprise applications.

Analyze business and functional requirements to identify automation opportunities.

Execute automated regression, smoke, sanity, and functional test suites.

Maintain reusable automation components and improve test coverage.

Integrate automation scripts with CI/CD pipelines.

Perform root cause analysis for failed test cases and provide detailed defect reports.

Work closely with developers, business analysts, and QA teams to resolve issues.

Ensure automation standards, coding best practices, and documentation are followed.

Participate in Agile ceremonies including sprint planning, stand-ups, reviews, and retrospectives.

Required Skills:

5–10 years of experience in Automation Testing.

Strong hands-on experience with the Watermelon automation tool (mandatory).

Experience in test automation framework development and maintenance.

Knowledge of API testing and automation.

Experience with SQL for database validation.

Familiarity with Git or other version control systems.

Experience with CI/CD tools such as Jenkins, Azure DevOps, or GitLab CI.

Strong understanding of SDLC, STLC, and Agile methodologies.

Excellent debugging, analytical, and problem-solving skills.

Good verbal and written communication skills.

Preferred Skills:

Experience with Selenium, Playwright, Cypress, or similar automation tools.

Knowledge of Java, Python, or JavaScript for automation scripting.

Exposure to cloud platforms such as AWS, Azure, or GCP.

Experience working in enterprise-scale automation projects.

ISTQB or equivalent testing certification is an added advantage.

Roles & Responsibilities:

Develop scalable and maintainable automation solutions.

Improve automation coverage and reduce manual testing effort.

Collaborate with stakeholders to deliver quality software releases.

Identify automation improvements and implement best practices.

Support production validation and release testing activities.

Mandatory Skills:

Watermelon Automation Tool

Test Automation

Automation Framework Development

API Testing

SQL

Git

CI/CD

Agile Methodology

Job Title : MLOps Engineer

Mode: Hybrid

Experience : 4 to 7 Years

Location : Hyderabad (Priority)/Bengaluru locations only

Notice Period : Immediate Joiner

Job Summary:

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

Key Responsibilities:

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

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

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

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

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

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

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

Experience:

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

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

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

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

• Experience with containerization technologies such as Docker and Kubernetes

• Strong understanding of DevOps principles and practices

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

Skills Referential (Required knowledge, skills and abilities)

Technical Skills:

Python

Pyspark

SQL

ETL Aws, Azure, gcp

Strong Senior Solution Architect – Google Cloud (AI / Enterprise Architecture) Profile

2

Mandatory (Experience 1) – Must have minimum 8+ years of experience in Enterprise Solution Architecture, Cloud Architecture, or Solution Consulting, with experience designing enterprise-scale cloud transformation initiatives.

3

Mandatory (Experience 2) – Must have 5+ years hands-on experience designing and delivering Google Cloud-based enterprise solutions, with strong expertise across the Google Cloud ecosystem.

4

Mandatory (Experience 3) – Must have hands-on experience architecting AI/Generative AI solutions using Vertex AI and Gemini Enterprise, including enterprise AI adoption, AI platform design, or AI application architecture.

5

Mandatory (Experience 4) – Strong expertise in BigQuery for enterprise data platforms, analytics architecture, and modern data engineering solutions.

6

Mandatory (Experience 5) – Must have experience designing cloud-native architectures using GKE (Google Kubernetes Engine), Cloud Run, and AlloyDB, with strong understanding of scalability, security, and production deployments.

7

Mandatory (Experience 6) – Must have experience leading enterprise architecture engagements, customer discovery workshops, AI strategy sessions, and translating business requirements into scalable technical solutions.

8

Mandatory (Experience 7) – Proven experience collaborating with Sales, Delivery, Customer Success, and Business Stakeholders, providing technical leadership throughout pre-sales, solution design, and implementation.

9

Mandatory (Certification) – Must hold a valid Google Professional Cloud Architect Certification.

10

Mandatory (Notice Period) – Immediate joiners or candidates who can join within 2 weeks.

Greetings from NAM Info Pvt Ltd,

Job Title: GCP DevOps Engineer

Location: Bangalore

Experience: 6+ Years

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

Job Description:

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

Required Skills:

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

Role Summary 

The GCP Delivery Lead is responsible for driving the technical vision, architecture, and delivery of enterprise-scale solutions on Google Cloud Platform (GCP). This role combines deep technical expertise with strong delivery leadership and customer engagement capabilities, working closely with clients, Google teams, and internal stakeholders. 

Key Responsibilities 

Technical Leadership 

• Define and own GCP solution architecture and technical strategy for client engagements 
• Design scalable, secure, and resilient cloud-native architectures 
• Establish architecture standards, best practices, and reusable frameworks 
• Provide governance and oversight across multiple programs 

Delivery Leadership 

• Ensure successful delivery of cloud transformation and modernization initiatives 
• Conduct architecture reviews, risk assessments, and quality assurance 
• Guide engineering teams through complex implementations 
• Ensure solutions meet performance, security, and scalability standards 

Google Partnership & Pre-Sales 

• Act as primary technical interface with Google Cloud teams 
• Support joint solutioning, co-selling, and client workshops 
• Contribute to proposals, solution design, and executive presentations 

AI & Data Solutions 

• Lead enterprise AI, GenAI, and data platform architecture on GCP 
• Drive adoption of Vertex AI, BigQuery, and modern AI/ML platforms 
• Advise clients on AI strategy, transformation, and innovation 

Practice Development 

• Build and mentor high-performing architecture and engineering teams 
• Drive certifications, capability building, and hiring initiatives 
• Create accelerators, reusable assets, and reference architectures 
• Contribute to practice growth and go-to-market strategies 

Required Qualifications 

Experience 

• 12+ years in cloud architecture, software engineering, or consulting 
• 5+ years of hands-on GCP architecture and delivery experience 
• Proven track record in large-scale cloud transformation programs 
• Experience managing multi-client and multi-program delivery 

Job Title

Channel Sales (Cloud Products)

Location

• Bangalore
• Chennai
• Vishakhapatnam
• Kochi
• Trivandrum

Company Name

Savex Technologies Pvt. Ltd.

It is a seasoned company operating for the last 35 years.

Mode of Working: Work From Office

Days of Working : 6 days a week (1st and 2nd Saturday off; remaining Saturdays are half-day working)

Responsibilities

Objective: Role Overview

We are looking for a highly motivated Sales Specialist – Cloud Software Portfolio to expand the adoption of modern cloud solutions across enterprise and mid-market customers through Savex’s channel ecosystem. 

The role requires experience in handling Cloud Software, SAAS softwares, software related to data platforms, analytics solutions, AI/ML, or database technologies with enterprise sales, partner engagement and channel development experience.

Key Responsibilities

• Drive revenue growth for the Cloud Software portfolio through enterprise sales and enabling and empowering resellers and partners.
• Identify, onboard, and develop partners with Cloud Software practice capabilities.
• Build and execute joint business development plans with partners to drive pipeline.
• Position solutions around cloud softwares.
• Work with OEM and Savex internal teams to support deal structuring and closure via partners.
• Conduct partner trainings, workshops, and joint sales motions to strengthen adoption.
• Participate in channel marketing activities, demand generation campaigns, and partner events.
• Track and report on partner pipeline, forecast, and target achievement.

Proven record of achieving sales growth through Enterprise and Channels.

Qualification: 

• Bachelor’s degree in engineering / computer science / IT / Business Administration.

• MBA (preferred, not mandatory).

Key Skills & Experience

• 3–8 years of experience in Enterprise sales/ channel sales/partner management within the IT industry.

Strong knowledge of the channel ecosystem – VARs, resellers, regional SIs.

• Ability to drive partner enablement, solution positioning, and joint GTM execution.

• Excellent communication, presentation, and relationship management skills.

Interview Process

Face to Face

Key Responsibilities

• Performance Testing: Design and execute large-scale strategies using Apache JMeter.
• CI/CD Integration: Embed performance testing into pipelines and automate workflows.
• Observability: Lead monitoring initiatives with Dynatrace.
• AI Insights: Leverage Davis AI for anomaly detection, insights, and root cause analysis.
• Automation Frameworks: Build frameworks for testing, reporting, and quality gates.
• Bottleneck Resolution: Diagnose and resolve issues across applications, APIs, databases, middleware, and infrastructure.
• ML Applications: Apply ML for workload modelling, traffic forecasting, and optimization.
• Collaboration: Partner with Dev, DevOps, Cloud, and Architecture teams.
• Governance: Define standards, best practices, and governance.
• Leadership: Mentor engineers and provide technical leadership.
• Executive Reporting: Present findings and recommendations to stakeholders.

Observability & Monitoring

• Strong hands-on experience with Dynatrace.
• Proven use of Davis AI in production.
• Expertise in APM, Observability, Root Cause Analysis, and Performance Diagnostics.

Automation & AI

• Experience developing Performance Automation frameworks.
• Proficiency in Python scripting.
• Applying AI/ML for traffic prediction, load simulation, workload modelling, and performance optimization.

Cloud & Infrastructure

• Strong experience with AWS, Azure, or GCP.
• Expertise in JVM tuning, database optimization, API performance analysis, and infrastructure monitoring.

Good-to-Have

• Experience with Gatling, k6, or LoadRunner.
• Exposure to Grafana and OpenTelemetry.
• Experience with Kubernetes Performance Tuning.
• Dynatrace certifications.
• Client-facing consulting or professional services background.

Role: GCP Data Engineer

Location: Bangalore. Chennai, Noida, Pune, Hyderabad

Experience: 5 years

Primary skills: Python, NOSQL, GCP concepts like Airflow, Big Query & Spanner, DAG, Composer for large dataset, Tidal tool

Role Descriptions:

Design| build| and maintain scalable data pipelines to support analytics| ML| and operational reporting.

Develop robust data ingestion| transformation| and integration workflows using Python| SQL| and modern data engineering frameworks.

Work with Google Cloud Platform (GCP) services| including Cloud Storage| Dataflow| PubSub| BigQuery| Cloud Spanner and Cloud Functions

Experience building data pipelines or backend data workflows using Python or similar languages

Principal Architect.

Architecture: Microservices, Event-Driven, Serverless, Service Mesh, Multi-tenancy, API Gateway.

DevOps/IaC: Terraform, Kubernetes (EKS/AKS/GKE), Helm, Jenkins/GitHub Actions, ArgoCD, MLOps.

Monitoring/Performance: OpenTelemetry, Datadog/New Relic, Chaos Engineering, Load Testing (k6/JMeter).

Networking/Security: VPC, Zero Trust, IAM, WAF, OAuth2/OIDC, DevSecOps.

Location: Bangalore (Hybrid/Onsite)

Experience: 5–8 Years

Work location -Manyata Tech park

Job Description

We are seeking a skilled GCP Data Engineer with 5–8 years of experience in designing, developing, and maintaining scalable data pipelines and cloud-based data solutions. The ideal candidate should have strong expertise in Google Cloud Platform (GCP), Python, PySpark, SQL, and Data Engineering concepts.

Key Responsibilities

• Design, build, and optimize scalable ETL/ELT data pipelines.
• Develop and maintain data processing solutions using Python and PySpark.
• Work with large-scale structured and unstructured datasets.
• Implement data ingestion, transformation, and data quality frameworks.
• Build and manage data solutions on Google Cloud Platform (GCP).
• Develop and optimize complex SQL queries, stored procedures, and data models.
• Collaborate with business stakeholders, data analysts, and cross-functional teams to understand data requirements.
• Monitor, troubleshoot, and improve data pipeline performance and reliability.
• Ensure data governance, security, and compliance standards are followed.
• Support data warehousing and analytics initiatives.

Required Skills

• 5–8 years of experience in Data Engineering.
• Strong programming experience in Python.
• Hands-on experience with PySpark and distributed data processing.
• Strong expertise in SQL and database performance tuning.
• Experience with Google Cloud Platform (GCP) services such as:
• BigQuery
• Cloud Storage
• Dataflow
• Dataproc
• Cloud Composer
• Pub/Sub
• Experience in designing ETL/ELT workflows.
• Knowledge of data warehousing concepts and dimensional modeling.
• Experience with version control tools such as Git.
• Strong problem-solving and analytical skills.

Preferred Skills

• Experience with CI/CD pipelines and DevOps practices.
• Exposure to orchestration tools like Airflow/Cloud Composer.
• Experience working in Agile/Scrum environments.
• Knowledge of streaming data processing and real-time data pipelines.

Educational Qualification

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.

Hiring: GCP Data Engineer (FTE)

📍 Location: Bangalore | Chennai | Pune | Gurgaon | Kolkata

💼 Employment Type: Full-Time

Notice Period - Immediate Joiner ( Serving Notice Period )

Work Mode - Hybrid

We are looking for experienced GCP Data Engineers with strong expertise in building scalable cloud data solutions.

Required Skills:

✔ GCP Data Engineering Experience

✔ BigQuery

✔ SQL & Python

✔ PySpark / Apache Spark

✔ Apache Beam / Dataflow

✔ ETL / ELT Pipeline Development

✔ Airflow / Cloud Composer

Responsibilities:

• Design and develop scalable ETL/ELT pipelines on GCP
• Build and optimize BigQuery solutions
• Process large-scale structured/unstructured data using Spark
• Develop automated workflows and cloud-native data pipelines
• Work with GCP services like Dataflow, Dataproc, Cloud Storage, etc.
• 
  

Good to Have:

• Google Cloud Certifications (Professional Data Engineer / Solution Architect)
• Experience with BigTable, Cloud SQL, Spanner, NoSQL databases

🎓 Qualification: Bachelor’s / Master’s in CS, Engineering, or related field

Key Responsibilities 

• Design, develop, and maintain scalable web applications using Node.js, React.js, and Next.js 
• Build robust RESTful APIs and backend services 
• Develop responsive and high-performance user interfaces 
• Work with cloud services on AWS and/or GCP for deployment and infrastructure 
• Collaborate with cross-functional teams including product, design, and QA 
• Optimize applications for maximum speed and scalability 
• Ensure code quality through best practices, code reviews, and testing 
• Troubleshoot and debug applications 

Required Skills 

• Strong experience in Node.js (backend development) 
• Proficiency in React.js and Next.js with product development experience
• Experience in building REST APIs and microservices architecture 
• Hands-on experience with cloud platforms: 
• Amazon Web Services (AWS) 
• Google Cloud Platform (GCP) 
• Strong knowledge of JavaScript (ES6+), HTML5, and CSS3 
• Experience with databases (SQL/NoSQL such as MongoDB, PostgreSQL) 
• Familiarity with version control tools like Git 
• Understanding of CI/CD pipelines and DevOps practices  

Role: Data Engineer

 Experience: 5+ Yrs

Type: Hybrid (3 Days a week)

Location: Chennai, Bangalore, Hyderabad, Pune, Kolkatta

End Client: Cognizant

Contract Duration: 6 Months

Shift:- 10 AM - 7 PM IST

Must Have: 

* Strong experience in Python

* Expertise in Data Engineering Frameworks

* Hands-on experience with ETL processes

* CI/CD

* Experience working on GCP (Google Cloud Platform)

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

Mandatory Skills: ETL, Data Warehousing, Python, GCP Services

Required Skills:

● Bachelor’s degree in Computer Science or similar field or equivalent work experience.

● 4+ years of experience on Data Warehousing, Data Engineering or Data Integration projects.

● Expert with data warehousing concepts, strategies, and tools.

● Strong SQL background.

● Strong knowledge of relational databases like SQL Server, PostgreSQL, MySQL.

● Strong experience in GCP & Google BigQuery, Cloud SQL, Composer (Airflow), Dataflow, Dataproc, Cloud Function and GCS

● Good to have knowledge on SQL Server Reporting Services (SSRS), and SQL Server Integration Services (SSIS).

● Knowledge of AWS and Azure Cloud is a plus.

● Experience in Informatica Power exchange for Mainframe, Salesforce, and other new-age data sources.

● Experience in integration using APIs, XML, JSONs etc.

● In-depth understanding of database management systems, online analytical processing (OLAP) and ETL (Extract, transform, load) framework, data-warehousing and Data Lakes

● Good understanding of SDLC, Agile and Scrum processes.

● Strong problem-solving, multi-tasking, and organizational skills.

● Highly proficient in working with large volumes of business data and strong understanding of database design and implementation.

● Good written and verbal communication skills.

● Demonstrated experience of leading a team spread across multiple locations.

Role & Responsibilities:

● Work with business users and other stakeholders to understand business processes.

● Ability to design and implement Dimensional and Fact tables

● Identify and implement data transformation/cleansing requirements

● Develop a highly scalable, reliable, and high-performance data processing pipeline to extract, transform and load data from various systems to the Enterprise Data Warehouse

● Develop conceptual, logical, and physical data models with associated metadata including data lineage and technical data definitions

● Design, develop and maintain ETL workflows and mappings using the appropriate data load technique

● Provide research, high-level design, and estimates for data transformation and data integration from source applications to end-user BI solutions.

● Provide production support of ETL processes to ensure timely completion and availability of data in the data warehouse for reporting use.

● Analyze and resolve problems and provide technical assistance as necessary. Partner with the BI team to evaluate, design, develop BI reports and dashboards according to functional specifications while maintaining data integrity and data quality.

● Work collaboratively with key stakeholders to translate business information needs into well-defined data requirements to implement the BI solutions.

● Leverage transactional information, data from ERP, CRM, HRIS applications to model, extract and transform into reporting & analytics.

● Define and document the use of BI through user experience/use cases, prototypes, test, and deploy BI solutions.

● Develop and support data governance processes, analyze data to identify and articulate trends, patterns, outliers, quality issues, and continuously validate reports, dashboards and suggest improvements.

● Train business end-users, IT analysts, and developers.

Immediate Hiring: GCP DevOps Engineer | Mumbai & Bengaluru (On-site)

OpsTree Global is urgently hiring a GCP DevOps Engineer with 4–9 years of experience for immediate requirements in Mumbai and Bengaluru.

Key Skills

• Google Cloud Platform (GCP)
• Terraform / Infrastructure as Code (IaC)
• Kubernetes & Helm Charts
• CI/CD – Jenkins, GitLab CI, GitHub Actions
• Linux Administration
• Scripting – Python / Go / Java
• 
  

Role Responsibilities

• Build and manage scalable cloud infrastructure on GCP
• Automate deployments and infrastructure provisioning
• Ensure system reliability, monitoring, and performance optimization
• Collaborate with development and operations teams for seamless delivery

📍 Locations: Mumbai & Bengaluru (On-site)

⚡ Immediate Joiners Preferred

💼 Experience: 4–9 Years

Designation: Cloud Sales Specialist (AWS/GCP/AZURE) (Field Sales)

Location: Mumbai (Andheri West) / Bengaluru

Experience: 5 to 10 Years relevant experience

Industry: Cloud Solutions/IT Services

About the Role

We are looking for a high-performing Sales Specialist (Field Sales) with strong industry connect & solution selling and a proven ability to close high-value deals.

This role is ideal for someone who is a true sales hunter, with strong CXO-level connect, ability to independently drive revenue through field engagement, principal vendors’ connections and strategic selling.

Important Note 

This role strictly requires hands-on Cloud Sales experience and existing CXO connections. Profiles from non-cloud or purely generic IT sales backgrounds will not be considered.

Key Responsibilities

• Own and drive end-to-end field sales for Cloud Services (AWS/Azure/GCP)
• Manage the region by Identifying, acquiring, and growing new business opportunities
• Build and leverage CXO-level relationships to drive business
• in-person client meetings, presentations, and solution positioning
• Collaborate with pre-sales & technical teams for solution-based selling
• Manage complete sales cycle: prospecting → negotiation → closure
• Consistently achieve and exceed sales targets
• Maintain strong pipeline management and forecasting discipline

Must-Have Experience

• 5-10 years in core Cloud Sales (AWS / Azure / GCP / Cloud Solutions)
• Proven track record in closing high-value deals
• Strong existing CXO / decision-maker connects (mandatory)
• Hands-on experience in field sales & direct client engagement
• Strong understanding of cloud ecosystem & solution selling

What Makes You a Great Fit

• A go-getter sales professional with strong hunting ability
• Ability to open doors, build trust, and close deals independently
• Strong network across decision-makers and business stakeholders
• High ownership mindset with a target-driven approach

What’s in It for You

• Opportunity to work directly with CXOs and key decision-makers
• Fast-track growth into leadership roles
• Exposure to leading cloud ecosystems (AWS / Azure / GCP)

Your Mission: The Role

solving for better.

You are a reliability-owning, hands-on solver. Not just a "break-fix engineer."

As a DRI (directly responsible individual) for our clients' most critical systems, you’ll be the go-to expert within the squad that ensures their environments are secure, reliable, and optimized 24/7. You will deliver measurable impact – improved uptime, faster response times, and real cost savings. Not just closed tickets. Not just alerts. Real outcomes you engineer yourself.

You will lead the charge on technical execution, from complex troubleshooting and root cause analysis to engineering proactive, automated solutions. This role is about building the future of reliable cloud operations and shipping it into today's production environments.

Your Responsibilities

what you will wake up to solve.

This isn’t a “manage tickets” role. You are the architect, the executioner and the DRI for our Cloud Managed Services GTM, deploying solutions that turn operational noise into hardened outcomes. Here’s how you’ll make your mark:

• Own Service Reliability: You will be the go-to technical expert for 24/7 cloud operations and incident management. You'll ensure strict adherence to SLOs by getting your hands dirty, leading high-stakes troubleshooting to deliver a superior client experience.
• Engineer the Blueprint: You'll translate client needs into scalable, automated, and secure cloud architectures. You will write and maintain the operational playbooks and Infrastructure as Code (IaC) that your squad uses every day.
• Automate with Intelligence: You'll lead the charge from the keyboard to futurify our operations. You'll embed AI-driven automation, predictive monitoring, and AIOps into core processes to eliminate toil and preempt incidents.
• Drive FinOps & Impact: You'll own the technical execution of the FinOps framework. You will continuously analyze, configure, and optimize cloud spend for clients through hands-on engineering.
• Be the Expert in the Room: You'll share your knowledge through internal demos, documentation, and technical deep dives, representing the deep expertise that turns operational complexity into business resilience.
• Mentor & Elevate: You will be a technical mentor for your peers. Through code reviews and collaborative problem-solving, you'll help build a high-performing squad that lives the “Always Hardened” mindset.

Experience & Relevance

We are looking for future technology leaders, not just coders. We value raw intelligence, analytical rigor, and an obsessive passion for technology over any prior experience.

• Cloud Operations Pedigree: 3+ years of experience in GCP cloud infrastructure, with a significant portion in a cloud managed services.
• Commercial Acumen: Proven track record of building and scaling a net-new managed services business.
• Client-Facing Tech Acumen: 2+ years of experience in a client-facing technical role, acting as the trusted advisor for cloud operations, security, and reliability.

Functional Skills:

• Service Delivery Mindset: A deep understanding of MSP business models, SLAs, and the importance of client satisfaction in an operational context.
• Client Engagement: Ability to ask appropriate questions to get to the heart of an operational issue and win trust with stakeholders.
• Cross-Functional Catalyst: Thrive in multi-disciplinary teams, bringing together operations, security, and development teams.
• Repository builder: Creates reusable frameworks, IaC modules, and operational playbooks for scale.

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.

Your Mission: The Role

solving for better.

You are a reliability-owning, hands-on solver. Not just a "break-fix engineer."

As a DRI (directly responsible individual) for our clients' most critical systems, you’ll be the go-to expert within the squad that ensures their environments are secure, reliable, and optimized 24/7. You will deliver measurable impact – improved uptime, faster response times, and real cost savings. Not just closed tickets. Not just alerts. Real outcomes you engineer yourself.

You will lead the charge on technical execution, from complex troubleshooting and root cause analysis to engineering proactive, automated solutions. This role is about building the future of reliable cloud operations and shipping it into today's production environments.

Your Responsibilities

what you will wake up to solve.

This isn’t a “manage tickets” role. You are the architect, the executioner and the DRI for our Cloud Managed Services GTM, deploying solutions that turn operational noise into hardened outcomes. Here’s how you’ll make your mark:

• Own Service Reliability: You will be the go-to technical expert for 24/7 cloud operations and incident management. You'll ensure strict adherence to SLOs by getting your hands dirty, leading high-stakes troubleshooting to deliver a superior client experience.
• Engineer the Blueprint: You'll translate client needs into scalable, automated, and secure cloud architectures. You will write and maintain the operational playbooks and Infrastructure as Code (IaC) that your squad uses every day.
• Automate with Intelligence: You'll lead the charge from the keyboard to futurify our operations. You'll embed AI-driven automation, predictive monitoring, and AIOps into core processes to eliminate toil and preempt incidents.
• Drive FinOps & Impact: You'll own the technical execution of the FinOps framework. You will continuously analyze, configure, and optimize cloud spend for clients through hands-on engineering.
• Be the Expert in the Room: You'll share your knowledge through internal demos, documentation, and technical deep dives, representing the deep expertise that turns operational complexity into business resilience.
• Mentor & Elevate: You will be a technical mentor for your peers. Through code reviews and collaborative problem-solving, you'll help build a high-performing squad that lives the “Always Hardened” mindset.

Experience & Relevance

We are looking for future technology leaders, not just coders. We value raw intelligence, analytical rigor, and an obsessive passion for technology over any prior experience.

• Cloud Operations Pedigree: 3+ years of experience in GCP cloud infrastructure, with a significant portion in a cloud managed services.
• Commercial Acumen: Proven track record of building and scaling a net-new managed services business.
• Client-Facing Tech Acumen: 2+ years of experience in a client-facing technical role, acting as the trusted advisor for cloud operations, security, and reliability.

Functional Skills:

• Service Delivery Mindset: A deep understanding of MSP business models, SLAs, and the importance of client satisfaction in an operational context.
• Client Engagement: Ability to ask appropriate questions to get to the heart of an operational issue and win trust with stakeholders.
• Cross-Functional Catalyst: Thrive in multi-disciplinary teams, bringing together operations, security, and development teams.
• Repository builder: Creates reusable frameworks, IaC modules, and operational playbooks for scale.

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.

Location: Bangalore

Experience: 2–5 years

Type: Full-time | On-site

Start: Immediate

Why this role exists

Most systems don’t fail because of one big outage.

They fail because reliability is treated as an afterthought.

Right now, uptime depends too much on individual heroics.

That doesn’t scale.

This role exists to build a reliability system where:

• Uptime is predictable
• Failures are contained
• Escalations don’t depend on leadership

What you’ll do

You will not just monitor systems.

You will own reliability as a product.

1. Drive uptime to production-grade reliability

• Improve system uptime to 99.9% customer-facing SLA within 4 months
• Define and track:
• SLAs / SLOs / error budgets
• Ensure reliability is measured from the customer’s perspective, not internal metrics

2. Build incident response as a system

• Set up a 24/7 incident response rotation across 3 engineers
• Eliminate dependency on leadership (no single escalation point)
• Define:
• Incident severity levels
• Response playbooks
• Escalation protocols
• Ensure fast detection → containment → resolution

3. Contain and fix erratic system behavior

• Identify and resolve:
• Latency spikes
• Downtime incidents
• Integration failures
• Build guardrails to prevent recurrence
• Focus on root cause elimination, not temporary fixes

4. Create continuous reliability feedback loops

• Work closely with engineering teams to:
• Surface recurring failure patterns
• Improve build quality
• Reduce production bugs
• Ensure learnings from incidents directly improve future releases

5. Improve observability and monitoring

• Build dashboards and alerts for:
• System health
• Performance metrics
• Failure signals
• Ensure issues are detected before customers report them

6. Reduce operational fragility

• Remove single points of failure (people, systems, workflows)
• Improve system resilience across:
• Deployments
• Integrations
• Runtime environments

What success looks like

• Uptime reaches 99.9%+ reliably
• Incidents are:
• Detected early
• Contained quickly
• Resolved permanently
• No dependency on a single individual for escalation
• System behavior becomes predictable and stable
• Engineering teams ship with higher reliability confidence

Who you are

• You have 2-5 years of experience in SRE / DevOps / backend systems
• You have worked on production systems with real uptime expectations
• You think in:
• Systems
• Failure modes
• Trade-offs
• You are comfortable debugging live, high-pressure environments

What will make you stand out

• Experience with:
• Distributed systems
• Cloud infrastructure (AWS / Azure / GCP)
• Monitoring & alerting tools
• Have built or improved:
• Incident response systems
• Reliability frameworks
• Strong debugging skills across:
• Infra
• Application
• Integrations

Compensation

₹60,000/month (fixed)

(Aligned with role scope and impact expectations)

Why join

• You will define reliability standards for a production AI platform
• Your work directly impacts:
• Customer trust
• Product performance
• Enterprise readiness
• You will move the system from reactive → predictable

What this role is not

• Not just monitoring dashboards
• Not limited to handling tickets
• Not dependent on escalation to leadership

What this role is

• A builder of reliability systems
• A guardian of uptime and performance
• A multiplier of engineering quality

One question to self-evaluate

Can you build a system where downtime is rare, predictable, and never dependent on a single person?

Job Title : DevOps Engineer

Experience : 3+ Years

Location : Indiranagar, Bengaluru (Work From Office – 5 Days)

Employment Type : Full-Time

Work Timings : 11:00 AM to 7:00 PM IST

Notice Period : Immediate Joiners Preferred

Role Overview :

We are seeking a skilled DevOps Engineer with 3+ years of experience in building and managing scalable cloud-native infrastructure.

The ideal candidate will have strong expertise in Kubernetes and Helm, along with hands-on experience in deploying and maintaining production-grade systems on cloud platforms.

This role offers an opportunity to work in a high-growth startup environment, contributing to both existing systems and new infrastructure development.

Key Responsibilities :

• Design, deploy, and manage scalable infrastructure using Kubernetes.
• Build and maintain CI/CD pipelines for efficient and automated deployments.
• Manage and optimize cloud environments (preferably GCP).
• Implement Infrastructure as Code using Helm/Terraform.
• Monitor system performance and ensure high availability and reliability.
• Handle bug fixes, system improvements, and performance optimization.
• Collaborate with engineering teams to design scalable microservices architecture.
• Implement logging, monitoring, and alerting solutions.
• Ensure security best practices including IAM, secrets management, and network policies.

Mandatory Skills :

• Strong hands-on experience with Kubernetes.
• Expertise in Helm Charts.
• Experience with Google Cloud Platform (GCP).
• Hands-on experience with ArgoCD or similar CI/CD tools.
• Knowledge of CI/CD tools like Jenkins, GitHub Actions, GitLab CI.
• Experience in database hosting and scaling.

Nice to Have :

• Exposure to other cloud platforms (AWS/Azure).
• Experience with modern DevOps and automation tools.
• Ability to quickly learn and adapt to new technologies.

Team & Work Scope :

• No dedicated DevOps team currently – high ownership role.
• Work on both existing systems (maintenance & improvements) and new system builds (greenfield projects).
• Opportunity to shape DevOps practices and infrastructure from scratch.

Preferred Candidate Profile :

• 3+ years of relevant DevOps experience.
• Strong problem-solving and debugging skills.
• Experience working in fast-paced startup environments.
• Understanding of scalability, security, and performance optimization.
• Good communication and collaboration skills.

Hiring Process :

1. Profile Screening
2. GT Assessment
3. Technical Interview – Round 1
4. Technical Interview – Round 2
5. Final Round (if required with US team)

Lead Cloud Reliability Engineer

Job Responsibilities

● Lead and manage the Cloud Reliability teams to provide strong Managed Services support to end-customers.

● Isolate, troubleshoot and resolve issues reported by CMS clients in their cloud environment

● Drive the communication with the customer providing details about the issue, current steps, next plan of action, ETA

● Gather client's requirements related to use of specic cloud services and provide assistance in seing them up and resolving issues

● Create SOPs and knowledge articles for use by the L1 teams to resolve common issues

● Identify recurring issues, perform root cause analysis and propose/implement preventive actions

● Follow change management procedure to identify, record and implement changes

● Plan and deploy OS, security patches in Windows/Linux environment and upgrade k8s clusters

● Identify the recurring manual activities and contribute to automation

● Provide technical guidance and educate team members on development and operations. Monitor metrics and develop ways to improve.

● System troubleshooting and problem-solving across plaorm and application domains. Ability to use a wide variety of open-source technologies and cloud services.

● Build, maintain, and monitor conguration standards.

● Ensuring critical system security through using best-in-class cloud security solutions.

Qualifications

● 4-7 years experience in Cloud Infrastructure and Operations domains and IT operational experience preferably in a global enterprise environment.

● Specialize in one or two cloud deployment platforms: AWS, GCP

● Hands on experience with AWS/GCP services (EKS, ECS, EC2, VPC, RDS, Lambda, GKE, Compute Engine)

● Understanding of one or more programming languages (Python, JavaScript, Ruby, Java, .Net)

● Logging and Monitoring tools (ELK, Stackdriver, CloudWatch)

● Knowledge on Conguration Management tools such as Ansible, Terraform, Puppet, Chef

● Experience working with deployment and orchestration technologies (such as Docker, Kubernetes, Mesos)

● Good analytical, communication, problem solving, and learning skills.

● Knowledge on programming against cloud plaorms such as Google Cloud Platform and lean development methodologies.

● Strong service aitude and a commitment to quality.

● Willingness to work in shifts.