Top AWS Jobs in Chennai

The Site Reliability Engineer will design scalable infrastructure, automated deployment pipelines, monitoring, and alerting systems. Responsibilities include troubleshooting production incidents, participating in on-call rotations, maintaining systems, improving security and compliance, optimizing reliability and efficiency, and mentoring junior engineers. The role requires collaboration with development and cross-functional teams, technical communication, infrastructure automation, and expertise in distributed systems, cloud platforms, and networking.

Designs and implements web and API test automation frameworks, migrates automation to Playwright, integrates tests into CI/CD, and measures product quality. The role defines testing standards, develops functional UI and service-level tests, maintains testing infrastructure, conducts peer reviews, manages risks, documents strategies, reports quality outcomes, mentors team members, and advises QA teams. Requires strong JavaScript, testing methodologies, database, cloud DevOps, version control, and Agile expertise, with four hours of overlap with Central US hours.

Leads client-facing delivery of complex data, analytics, AI, cloud, and modern data platform solutions. Owns technical workstreams from discovery through deployment, designs pipelines and integrations, modernizes legacy data environments, applies testing and governance practices, troubleshoots complex issues, and ensures production readiness. Guides engineers, reviews technical deliverables, contributes to proposals and technical discovery, mentors consultants, and develops reusable engineering patterns for the Data Practice.

Analyze sales, financial, customer, and commercial performance data to support forecasting, business planning, growth opportunity identification, and executive decision-making. Build dashboards, reporting solutions, forecasts, scenarios, and actionable recommendations. Partner with business and technology stakeholders to improve data quality, KPI governance, analytics adoption, and measurement of commercial initiatives. Apply statistical, predictive, machine learning, and experimentation techniques when they deliver measurable business value.

Designs and leads enterprise AI Factory and GPU infrastructure architectures spanning compute, networking, storage, Kubernetes, cloud, security, observability, and AI/ML platforms. Assesses workloads, develops reference architectures and detailed designs, performs capacity planning and technology evaluations, leads proof-of-concepts, and supports deployment, migration, troubleshooting, and production transition. Collaborates across infrastructure, security, cloud, data, application, and operations teams to ensure scalable, secure, reliable, and cost-effective AI platforms.

Lead the transformation from DevOps to DevSecOps across a large-scale eCommerce platform. Build and manage CI/CD pipelines, containerized applications, infrastructure automation, and cloud environments across Azure and Google Cloud. Ensure system reliability through monitoring, logging, alerting, and production troubleshooting. Collaborate with cross-functional teams, improve engineering practices, provide technical leadership, and mentor junior engineers.

Design and deliver cloud-native data platforms, scalable big data pipelines, lakehouses, warehouses, transformation frameworks, BI solutions, and ML-enabled data workflows. Lead client-facing pre-sales engagements, technical workshops, proof-of-concepts, executive conversations, and enterprise data modernization initiatives. Build reusable architectural IP, influence senior stakeholders, and translate ambiguous business challenges into production-ready solutions using AWS and modern data technologies.

Own and improve cloud infrastructure, Kubernetes platforms, Infrastructure as Code, CI/CD, GitOps, observability, security, reliability, and cost efficiency. Build automation and self-service tooling, lead complex production incident investigations, improve resilience and disaster recovery, evaluate architecture, and mentor engineers. The role requires autonomous platform ownership, strong systems judgment, and thoughtful use of AI-assisted engineering tools.

Designs, operates, and optimizes cloud infrastructure and internal developer platforms. Responsibilities include Kubernetes management, infrastructure-as-code automation, CI/CD, observability, troubleshooting distributed systems, cloud networking, security controls, cost optimization, and developer tooling. The role uses Go, Python, and Bash and applies AI/ML tools to improve DevOps workflows and operational efficiency across AWS, GCP, and Azure environments.

Lead full-stack software architecture and development, with a frontend emphasis, across scalable backend services and frontend microapps. Drive technical design, reliability, DevOps, CI/CD, and cloud-native engineering; mentor engineers and collaborate across distributed teams. Build AI-powered platform features using LLMs, agents, and related frameworks. Improve React performance, service reliability, incident response, and engineering effectiveness while integrating customer-focused solutions across multiple domains.

Manage the full customer journey for a portfolio of cloud security customers. Drive adoption, customer success plans, business outcomes, renewals, and expansion while serving as a trusted advisor. Lead executive and quarterly business reviews, manage risks and escalations, communicate product updates, and collaborate with technical, sales, and cross-functional teams. The role requires cloud security and SaaS experience, knowledge of AWS, Azure, and Google Cloud, strong communication, AI proficiency, and 30% travel.

Lead technical presales for enterprise AI, data analytics, and digital twin solutions in telecommunications and other industries. Build customer relationships, conduct discovery workshops, design solutions, deliver demos, lead proofs of concept, support RFPs and proposals, and guide post-sale optimization. Translate complex technical capabilities into business outcomes for technical and executive stakeholders while collaborating with sales, product, engineering, and delivery teams.

The Business Analyst translates client and business requirements into detailed technical and functional specifications for Cassini’s derivatives analytics platform. Responsibilities include creating Jira requirements and acceptance criteria, documenting workflows, prototyping calculators and wireframes, supporting QA validation, researching margin and collateral models, testing APIs and UI functionality, and producing user documentation. The role requires financial services experience with derivatives, initial margin, collateral workflows, and strong collaboration across product, development, QA, delivery, and support teams.

Develop scalable full-stack web applications using React.js, Java, Spring Boot, MongoDB, AWS, and Azure. Build RESTful APIs, optimize databases, deploy and monitor cloud applications, maintain CI/CD pipelines, and apply DevOps, security, testing, and code-quality practices. Collaborate with cross-functional Agile/Scrum teams and use containerization, infrastructure-as-code, and AI coding tools to improve delivery.

Design, automate, and maintain highly available AWS cloud infrastructure. Build and operate containerized workloads (ECS/Fargate), manage RDS/PostgreSQL, implement IaC (Terraform/CloudFormation), CI/CD pipelines, caching, observability, incident response, troubleshooting, and collaborate with engineering teams to improve reliability and scalability.

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.

Build production AI-powered automation, data pipelines, analytics, alerting, and anomaly detection systems. Integrate LLM features with internal tools, develop cloud and platform services, and collaborate with stakeholders to automate manual processes. Engineers specialize initially in AI, data, or platform engineering while contributing across tracks through pairing, code review, and shared delivery. The role requires strong API and data-handling skills, production engineering experience, clear communication, and willingness to work from the Chennai office during US Eastern overlap hours.

Owns test strategy and coverage across UI, API, and service layers. Designs and maintains automation and performance testing frameworks, leads risk assessments and release validation, performs root-cause analysis, and establishes shift-left quality practices and quality gates. Partners with engineering, product, and platform teams while using AI-assisted tools to accelerate testing and debugging for SaaS and AI/ML-powered products.

Own HUD’s production infrastructure and backend platform systems, focusing on reliability, scalability, performance, cost, deployment safety, and developer experience. Build AWS infrastructure with Terraform and Kubernetes, improve CI/CD and observability, design resilient services and asynchronous systems, manage incidents, and develop internal automation and tooling. The role supports high-availability AI, marketplace, and data-heavy workloads.

Build and automate cloud cost optimization and governance across AWS and GCP. Analyze billing and usage, identify and implement savings, maintain cost attribution, create reporting and anomaly detection, and write Python, Terraform, and Lambda automation. Partner with Engineering, Finance, Product, and leadership on architecture tradeoffs, forecasting, budgeting, and cost accountability.

Implements enterprise cryptographic strategy and post-quantum readiness through certificate automation, DigiCert self-service, PKI integrations, and cryptographic asset inventories. Builds certificate lifecycle workflows across cloud, CI/CD, infrastructure, and application environments; establishes CBOMs; remediates certificate and cryptographic risks; develops runbooks and dashboards; and supports crypto-agility, PQC migration planning, and technical adoption across global teams.

Own AWS-based infrastructure automation, provisioning, reliability, and hybrid-cloud integrations with Azure. Build Azure DevOps multi-stage pipelines, manage Terraform infrastructure as code, administer Docker and EKS environments, and implement secure cross-cloud authentication. Configure container registries, monitoring, logging, metrics, tracing, and alerting. Support deployment troubleshooting, risk assessments, and client operational procedures.

Design and drive the target-state architecture for a Databricks-native data platform. Define scalable ingestion, governance, security, analytics, and reliability standards while delivering hands-on proofs of concept with SQL, PySpark, and Python. Partner with product, operations, and engineering teams to align platform investments with business needs, reduce technical debt and total cost of ownership, mentor engineers, evaluate technologies, and support AI-powered development and data analytics capabilities.

Build and maintain scalable AWS cloud infrastructure, observability and monitoring systems, deployment pipelines, and automation. Participate in on-call rotations, incident response, post-mortems, and root-cause analysis. Support product engineering teams with infrastructure troubleshooting and operational best practices while applying security and compliance controls. The role requires experience with Terraform, CI/CD, Linux, shell scripting, cloud services, managed Kubernetes, databases, and debugging application code.

Own end-to-end development of modules across Amtech’s AWS-hosted .NET/C# Cloud API and legacy 4D ERP platform. Design RESTful APIs, integrate AWS services, resolve complex business-logic issues, improve testing and reliability, maintain data integrity, participate in Agile ceremonies and code reviews, and mentor junior engineers. The role requires independent technical judgment across modern and legacy enterprise systems, with opportunities to use AI-assisted development tools.