Top AWS Jobs in Chennai

Build and deploy ML models on structured and unstructured data, design A/B tests, create visualizations, collaborate cross-functionally, operationalise pipelines with data engineering, develop domain expertise, and translate analyses into stakeholder recommendations.

Senior technology leader responsible for strategy, architecture, and delivery of enterprise-scale GenAI/AI agent platforms and Python-based data ecosystems. Leads ~15+ engineer agile teams, drives AI PDLC, regulatory-compliant data pipelines (PySpark/Databricks/Kafka), microservices and cloud-native deployments, and ensures model governance, explainability, and stakeholder alignment across Retail and Wealth Risk.

The Lead C# Web Developer will design and develop secure MVC applications, perform coding, testing, and debugging while enhancing web platforms and integrating with vendor systems.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Design and deploy production AI systems that integrate backend services, build reusable ML infrastructure, optimize AI systems, and mentor engineers on best practices.

Design, develop, and maintain scalable backend services; implement secure APIs; optimize system performance and reliability; collaborate with cross-functional teams.

As an Infrastructure Engineer, you will build and optimize storage and offloading infrastructure for multimodal robotics data, focusing on data movement, AWS optimization, and reliability across global operations.

The Partner AI Deployment Engineer will guide AWS engagements, shape technical strategy, build AI architectures, and mentor partners to drive successful AI deployments.

As a Forward Deployed Engineer, drive customer success through AI deployments, optimize systems for reliability, and collaborate with teams to enhance products.

Provide technical pre-sales support for servers, storage, backup, and cloud solutions, while engaging with clients to gather requirements and offer effective solutions.

Lead end-to-end customer deployments with frontier AI labs: gather requirements, design and build production-grade, scalable systems across stack, partner with cross-functional teams, mentor engineers, and create reusable tools and deployment patterns to improve model and customer outcomes.

Build and scale the Reinforcement Learning Environments platform: design backend services and data pipelines, create modular simulation domains, improve reliability and observability, partner with US research and product teams, and ship high-quality maintainable code to support model training and evaluation.

Lead design and scaling of Reinforcement Learning Environments (RLE) and data pipelines, partnering with research, product, and ops to build reliable, observable, production systems that generate high-quality training and evaluation data.

Build and maintain customer-facing production software across the full stack. Partner with senior engineers to design, deploy, and iterate scalable solutions using React, TypeScript, relational databases, and cloud platforms. Improve reliability, performance, and maintainability while collaborating with Research, Product, and Operations teams on customer deployments.

The Fullstack Developer will support a web portal project, primarily using Java and Angular for development and maintenance tasks.

The Automation Tester will design, maintain, and troubleshoot automated test scripts using Selenium and API testing tools. Responsibilities include developing automation frameworks, collaborating on CI/CD processes, and guiding team members while ensuring the incorporation of new technologies and best practices.

As a hands-on data engineer, you'll build and enhance scalable data platforms, develop data pipelines, and collaborate with various teams to improve data solutions and system performance.

Design, develop, and execute test plans and automated tests (including API and performance). Identify and track defects, collaborate with cross-functional teams, maintain CI/CD test automation, and use AI tools to support test strategy and automation.

Lead design, development, and deployment of enterprise Oracle APEX applications. Provide architecture, mentorship, security best practices, high-performance SQL/PLSQL development, API integrations (REST/SOAP/ORDS), CI/CD and DevOps collaboration, performance tuning, and documentation for long-term Washington-time contractor engagement.

Design and lead enterprise Oracle APEX applications and architecture. Develop high-performance SQL/PLSQL, integrate REST/SOAP services, implement APEX UI/customizations and security, optimize performance, mentor teams, manage CI/CD and cloud deployments, and produce technical documentation.

Lead application security efforts by governing vulnerability management, automating security workflows, embedding SSDLC practices, partnering with engineering/GRC to meet compliance, and serving as a security SME during incident response and customer escalations.

Lead IT audit and compliance activities, perform risk assessments, identify vulnerabilities across networks, applications, databases and cloud platforms, analyze audit data, recommend remediation, ensure IT governance alignment, and communicate findings to technical and non-technical stakeholders while collaborating with cross-functional teams.

Lead technical direction for data platform capabilities: design and maintain data pipelines, reporting models, and data governance to support trusted metrics and AI/LLM agentic workflows. Drive architectural improvements, mentor engineers, collaborate on roadmaps, and represent technical capabilities externally.

Maintain and optimize production LLM/VLM services and microservices (Flask/FastAPI), manage async queues, deploy and monitor Uvicorn/Gunicorn hosts, integrate LLM routing tools, design prompt strategies, build feedback/evaluation pipelines, expose secure REST APIs, and track token usage, latency, and errors to ensure SaaS-grade AI performance.

Own and mature the enterprise security program: manage identity/SSO, EDR, MDM, and SaaS security; secure cloud and developer stacks (GitHub, AWS, GCP); run vulnerability management, backup testing, and incident response; ensure endpoint lifecycle governance and maintain compliance with ISO 27001 and SOC 2.