Top AWS Jobs in Chennai

Provide in-person IT support for the Bengaluru office while managing enterprise infrastructure, endpoints, identity, networking, Microsoft 365, and hybrid services. Administer Intune and device lifecycle operations, troubleshoot complex technical issues, coordinate vendors, support ITSM processes, improve monitoring and reliability, develop automation, and assist with SOC 2 and ISO 27001 controls. Collaborate with global IT, Cloud, Security, HR, Facilities, and business teams.

Designs, automates, and supports AWS cloud infrastructure and delivery pipelines for cloud-native digital products. Responsibilities include Terraform and Ansible automation, CI/CD support, AWS account and networking configuration, containerized workloads on Amazon ECS, security and monitoring alignment, troubleshooting, documentation, and collaboration with application and central cloud teams.

Designs, develops, and supports scalable AWS-based file ingestion and data processing solutions using Python, AWS Glue, and PySpark. Responsibilities include building ETL workflows, integrating databases and APIs, implementing validation and error handling, configuring serverless AWS services, optimizing performance and cost, supporting production operations, and collaborating on CI/CD. The role also requires monitoring, security configuration, documentation, reconciliation, and audit processes.

Develop and maintain end-to-end web applications using modern JavaScript and TypeScript frameworks, Node.js, APIs, databases, and cloud platforms. Design responsive interfaces, implement secure authentication, write documentation and automated tests, debug performance and reliability issues, and follow Agile development practices. Collaborate with designers, product managers, testers, and other stakeholders to translate requirements into technical solutions. Mentor junior developers, recommend innovative improvements, and continuously optimize application code.

Build and operate production Kubernetes and AWS infrastructure across environments and customer deployments. Own CI/CD pipelines, automated provisioning, deployments, rollbacks, observability, reliability, scalability, and security. Debug issues involving Kubernetes, networking, databases, and applications, while developing internal tooling to improve engineering productivity. Partner with engineering, customer infrastructure, and security teams on enterprise deployments.

Build and deploy production AI systems across LLM orchestration, retrieval, agents, evaluations, voice, APIs, backend services, and infrastructure. Design reliable LLM pipelines, evaluation suites, data flows, and real-time multimodal experiences. Experiment with emerging models, debug issues across the stack, and communicate technical decisions clearly while owning projects from exploration through production iteration.

Design, build, and operate Supabase’s global edge and networking infrastructure, including routing, load balancing, DNS, WAF, TLS termination, CDN integrations, and observability. Improve latency, reliability, security, and cost efficiency across cloud regions. The role includes developing automated routing systems and CI/CD, troubleshooting distributed systems, participating in on-call and incident response, and collaborating with infrastructure and product teams.

Design, develop, and maintain Python-based automation frameworks using Selenium, Playwright, and PyTest. Create automated UI and API tests, integrate testing with CI/CD pipelines, validate databases with SQL, analyze results, resolve defects, and ensure coverage across web applications. Collaborate in Agile teams and continuously improve testing processes. Preferred experience includes Docker, performance testing, cloud platforms, BDD frameworks, accessibility, and cross-browser testing.

Leads delivery and support of enterprise Java backend platforms, setting technical priorities, designing scalable architectures, and guiding distributed engineering teams. Oversees timelines, resources, code quality, testing, CI/CD, production readiness, and technical escalations. Partners with Product, UX, QA, DevOps, architecture, and business stakeholders to deliver reliable high-volume solutions using Java, Spring Boot, microservices, APIs, event-driven systems, messaging, cloud platforms, and SQL/NoSQL databases.

Technically lead a sustenance engineering team maintaining and enhancing network automation and orchestration products. Own defect resolution, product enhancements, releases, design, coding, testing, debugging, root-cause analysis, and production issue resolution. Collaborate across product, development, QA, support, and engineering teams while mentoring engineers and improving automation, code quality, and testing practices. Build and support cloud-native microservices using Java or Golang, containers, Kubernetes, databases, messaging systems, and network protocols.

Leads and mentors data engineering teams while remaining hands-on in architecture, coding, and delivery. Designs scalable ingestion, transformation, ETL/ELT, data modeling, reporting, and analytics pipelines using Python, SQL, Azure Databricks, Snowflake, and PySpark. Oversees CI/CD, automated testing, code reviews, workload allocation, documentation, stakeholder communication, and technical decision-making for enterprise data initiatives.

Lead the architecture and development of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic AI systems for intelligent networking. Drive the full software lifecycle from design through production operations, establish technical direction, mentor engineers, and improve system reliability, security, observability, performance, and scalability.

Lead the technical vision, architecture, development, testing, deployment, and operations of scalable AI infrastructure, distributed microservices, real-time data platforms, and agentic AI systems. Build secure, resilient, observable services processing high-volume network data; guide technical strategy, improve engineering practices, and mentor engineers. Translate complex technical challenges into production-ready solutions across intelligent networking, cloud platforms, analytics, and automation.

Leads the architecture, development, deployment, and operation of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic systems for intelligent networking. Drives technical vision, builds secure and observable production services, mentors engineers, leads technical discussions, and improves system reliability and performance. Requires extensive software engineering and distributed systems experience, proficiency in a general-purpose programming language, cloud expertise, and familiarity with AI, stream processing, network telemetry, or large-scale analytics.

Leads the architecture, development, deployment, and operation of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic AI systems. Defines technical strategy, builds secure and observable production services, processes high-volume network data, and mentors engineers. The role requires hands-on software engineering leadership across the full lifecycle, including design, coding, testing, cloud deployment, operations, and technical reviews.

Lead the architecture, development, testing, deployment, and operation of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic AI systems. Define technical vision, build secure and observable production services, process high-volume network data, mentor engineers, and guide technical strategy across intelligent networking and cloud-native platforms.

Lead the architecture and development of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic systems for intelligent networking. Drive the full software lifecycle, establish technical direction, mentor engineers, and ensure production systems are secure, observable, resilient, and highly performant.

Lead the architecture, development, testing, deployment, and operation of scalable AI infrastructure, distributed microservices, real-time data platforms, and agentic AI systems. Define technical vision, build secure and observable high-performance services, process large-scale network data, and integrate intelligent networking capabilities. Mentor engineers, lead technical discussions and reviews, improve system reliability and performance, and translate complex technical challenges into production-ready solutions.

Lead the architecture and development of scalable, secure, observable AI infrastructure, distributed microservices, real-time data pipelines, and agentic systems for intelligent networking. Drive technical vision, software delivery, system reliability, and operational excellence while mentoring engineers. Build production platforms processing high-volume network and operational data, integrating cloud infrastructure, machine learning, telemetry, and automation capabilities.

Own ambiguous product problems end to end, from defining user flows and API contracts through frontend implementation, backend collaboration, testing, and production delivery. Review Haskell and React code, maintain performance, accessibility, SEO, and product quality standards, and use AI tools for prototyping, implementation, refactoring, debugging, and technical exploration. Work across product, UX, frontend, backend architecture, and AWS infrastructure in a remote-first environment.

Design, operate, scale, and optimize production SQL and NoSQL databases, with a focus on PostgreSQL, distributed systems, concurrency, replication, performance, reliability, backups, disaster recovery, and high availability. Build Python automation for monitoring, diagnostics, migrations, failover validation, and remediation. Partner with application and infrastructure teams on data architecture and operational practices while mentoring engineers.

Leads an engineering team delivering scalable full-stack and AI-enabled products. Responsibilities include setting architecture and coding standards, improving Java APIs and Angular applications, guiding AI solution development, enforcing DevSecOps and testing practices, managing technical roadmaps, mentoring engineers, overseeing delivery, optimizing cost and performance, and evaluating emerging technologies. The role is approximately 50% leadership and 50% hands-on engineering, including architecture, coding, design reviews, and technical problem-solving.

Own end-to-end enterprise architecture across AWS and Azure environments, establishing scalable, secure, reusable integration patterns for GenAI, chatbot, translation, and document-processing services. Define target-state architecture, review designs, resolve integration constraints, lead architecture governance, and establish non-functional requirements covering security, data residency, exactly-once processing, and disaster recovery.

Design, develop, operate, and optimize large-scale software-defined networking solutions for NVIDIA AI Cloud environments. Responsibilities include building OVS/OVN control and data plane software, Kubernetes networking services, observability systems, CI/CD pipelines, GitOps integrations, and secure gRPC/REST services. The role owns production reliability, incident response, performance tuning, and upstream open-source contributions while collaborating with SRE, DevOps, and network engineering teams.

Designs, operates, and improves scalable cloud infrastructure across GCP and AWS. Builds Terraform-based infrastructure, GitHub Actions CI/CD pipelines, observability, automation, and AI-enabled monitoring and remediation. Manages MySQL and SQL Server databases, Cloudflare services, security controls, repository governance, and incident response. Supports reliability, performance, cost optimization, compliance, and cloud modernization while providing 24/7 on-call coverage and mentoring junior engineers.