Top AWS Jobs in Chennai

Lead and manage global IT infrastructure as a product: plan roadmaps, run BAU services, deliver cloud migrations, manage networks/servers/security, lead Wintel/Desktop/DevOps teams, oversee budgets, KPIs, and on-call support to ensure stability, scalability and compliance.

Designs, builds, and maintains Snowflake and dbt data pipelines, transformations, models, and analytical solutions supporting global sales and marketing teams. Collaborates with product owners, database architects, and analysts to translate requirements into scalable technical solutions. Responsibilities include code reviews, performance optimization, data quality and reliability improvements, and evaluating emerging AI and LLM technologies.

Designs, builds, and maintains scalable data pipelines, transformations, warehouses, and analytical solutions using Snowflake and dbt. Collaborates with product owners, database architects, and analysts to translate requirements into technical solutions. Responsibilities include data modeling, code reviews, performance optimization, data quality, reliability improvements, and evaluating emerging AI and LLM technologies.

Designs, builds, and maintains scalable data pipelines, transformations, data models, and analytical solutions using Snowflake and dbt. Collaborates with product owners, database architects, and analysts to translate requirements into technical solutions. Responsibilities include code reviews, performance optimization, data quality and reliability improvements, and evaluating emerging technologies such as AI and LLMs. The role also applies SQL, CI/CD, cloud services, orchestration, infrastructure-as-code, and programming skills across sales and marketing data platforms.

Designs, builds, and maintains scalable data pipelines, transformations, data models, and analytical solutions in Snowflake and dbt for global sales and marketing analytics. Collaborates with product owners, architects, and analysts; performs code reviews; resolves performance, quality, and reliability issues; and evaluates emerging AI and LLM technologies.

Provide production application support across centralized enterprise applications and infrastructure. Responsibilities include incident, problem, and major incident management; monitoring and troubleshooting; log analysis; change, release, and deployment support; disaster recovery testing; runbook maintenance; operational improvements and automation; and coordination with development, infrastructure, operations, business, and global teams.

Designs and maintains automated test scripts and scalable frameworks for web, mobile, and API applications. Performs functional, regression, integration, system, smoke, and manual testing; validates RESTful APIs and databases; tracks defects; analyzes test results; and prepares reports. Collaborates with development, business, and product teams, integrates tests into CI/CD pipelines, participates in Agile ceremonies and code reviews, and supports quality assurance across software applications.

Design, build, and maintain secure, scalable platform infrastructure and CI/CD pipelines. Deploy and manage cloud and container platforms, implement observability and DevSecOps practices, provide L2/L3 operational support, perform RCA, and mentor engineers to drive platform reliability, automation, and modernization initiatives.

Design, build, and maintain scalable data pipelines, AI agents, and microservice integrations using Python, PySpark, Databricks, and agentic AI tools. Deploy and automate cloud-native, CI/CD workflows, ensure data quality and security, and drive adoption of Data Mesh/federation and AI use cases across retail and wealth risk platforms.

The Senior Full Stack Engineer will design and develop scalable APIs, manage databases, implement CI/CD pipelines, and mentor junior staff.

Design, build, and maintain scalable data pipelines and AI agents using Python, PySpark, Databricks, Kafka and microservices. Deploy and integrate agentic AI (Google ADK, Devin.AI, MCP), implement Data Mesh/federation, automate microservice integrations with cloud-native infrastructure (OpenShift/Kubernetes) and CI/CD, ensure data quality/security, and drive compliance and best practices within Retail and Wealth Risk Engineering.

Lead backend developer responsible for designing and building microservices, writing test automation, integrating LLM APIs and AI features, collaborating across product and QA, guiding team members, and assisting deployments to replace a legacy application.

Provide L3 production support for NICE CXone contact center environments. Monitor platform health, resolve incidents and outages, perform RCAs, support ACD/IVR/routing/agent desktop/digital channels, troubleshoot APIs/telephony/CRM/cloud integrations, support deployments, create operational documentation, and drive automation and improvements.

Design, build, and maintain production-grade Generative AI applications and agentic workflows using LLMs, RAG, embeddings, and vector search. Architect cloud-native, scalable solutions (.NET backend, modern front-end), implement security, monitoring, cost optimization, CI/CD, and mentor junior engineers while collaborating with product and domain teams.

Develop, test, review, and document Java-based enterprise services and RESTful APIs. Troubleshoot and profile performance, collaborate across teams, follow agile sprints, and support product operations and technical communication.

Design and build automated integrations and continuous control monitoring to improve visibility and reporting of cybersecurity controls. Leverage APIs, IaC, cloud platforms, scripting, AI, and workflow automation to reduce manual compliance work, support dashboards and metrics, and validate controls across critical environments.

Work with enterprise customers to design, build, and deploy production-grade AI solutions on the Cogentiq platform. Implement integrations with enterprise systems, develop connectors, backend services, and microservices, ensure scalability, security and observability, troubleshoot deployments, and turn deployment learnings into reusable platform capabilities.

Lead and grow the India engineering team (initially 5 engineers) across product, SRE, and InfoSec; own technical roadmap, drive scalable secure systems, mentor and hire, partner with US product and data teams, and implement engineering best practices for reliability and incident response.

Designs and operates enterprise data governance infrastructure across Snowflake and AWS. Responsibilities include RBAC, authentication, masking, row-level security, compliance automation, Terraform provisioning, access workflows, monitoring, SOX evidence, data sharing, Iceberg governance, orchestration, cost optimization, and Snowflake AI/ML governance. The role also supports platform reliability, self-service data access, and scalable identity integration using Okta and SCIM.

Design, modernize, and operate enterprise cloud platforms across AWS and Azure. Lead cloud architecture, platform engineering, infrastructure automation (IaC), observability, security, networking, database and reliability engineering for large-scale modernization initiatives.

Defines and governs enterprise data architecture, models, standards, metadata, data quality, governance, and scalable architectures for operational, analytical, and AI/ML workloads. Partners with business and technology stakeholders to translate requirements into data solutions, support modernization initiatives, establish semantic layers and trusted datasets, and ensure regulatory, security, and enterprise architecture compliance.

Designs and deploys AI-enabled platform capabilities, integrating LLMs, prompt engineering, RAG, embeddings, and intelligent workflows. Builds AI evaluation and validation frameworks alongside scalable QA automation for APIs, microservices, distributed systems, and platform services. Integrates automated testing into CI/CD pipelines, validates reliability and performance, and collaborates with engineering, product, data, and platform teams. Provides technical leadership on AI engineering, automation, and quality standards.

Design and optimize finance data products on Databricks (bronze-to-gold) by translating business needs into data pipelines and models, improving data quality, cataloging products, supporting incidents, and guiding engineering and stakeholders on architecture and consumption.

Design, develop, deploy, and support enterprise-scale applications using Java, Spring Boot, microservices, Angular or React, REST APIs, messaging, caching, and cloud technologies. Drive modernization, automation, observability, performance, security, and engineering best practices. Collaborate with cross-functional Agile teams, own end-to-end application delivery, mentor junior developers, and influence technical direction. AI-assisted development and AI-enabled application experience are preferred, as is banking or financial services experience.

Develop and maintain full-stack Java applications and customer-facing systems using Java, Spring Boot, Angular, APIs, and cloud technologies. Responsibilities include software design, coding, testing, deployment, application support, system analysis, documentation, and participation in Agile planning. The role also involves automated testing, CI/CD, DevOps, cloud deployment, AI product development, risk management, and collaboration with users, product owners, and technology teams.