Top AWS Jobs in Chennai

Own the technical direction and end-to-end delivery of a backend engineering team supporting high-volume supply chain visibility platforms. Design distributed microservices, event-driven systems, data models, integrations, and production architecture. Drive engineering standards, reliability, observability, technical debt reduction, risk management, code quality, mentoring, hiring, and cross-functional coordination. Remain hands-on in Java or Go development while partnering with Product and Engineering Managers to deliver complex multi-quarter initiatives.

Provides customer-facing WLAN consulting and engineering services for Aruba solutions, including network planning, design, implementation, migration, optimization, troubleshooting, and security improvement. Develops technical documentation, simulates designs in labs, supports customer reviews and training, and collaborates with engineering and field teams. Requires strong wireless, networking, authentication, VoIP, and Aruba product expertise, along with customer-site travel.

Design and implement full-stack features with minimal guidance. Collaborate with PMs, UX, QA, and engineers. Build frontend components (React/Angular) and backend services (Java/Kotlin/.NET). Develop and consume RESTful APIs, use Git, Gradle/Maven, and troubleshoot production issues. Participate in code reviews, follow architectural patterns, and support delivery during critical phases.

Provides pre- and post-sales WLAN consulting, design, implementation, migration, troubleshooting, and optimization for Aruba networking solutions. Creates requirements, network designs, installation and migration plans, and customer review materials. Resolves technical issues, simulates designs in labs, develops knowledge-base content, and collaborates with customers, partners, QA, engineering, and field teams. The role requires customer-site travel, strong communication, independent work, and expertise in Aruba products, authentication, wireless networking, VoIP, routing, switching, and security.

Owns the strategy, roadmap, delivery, and adoption of enterprise AI enablement platforms and AI products. Responsibilities include defining AI capabilities, prioritizing use cases, managing product lifecycles, partnering with engineering and data teams, establishing responsible AI governance, managing budgets and vendors, and influencing senior stakeholders. The role also mentors product teams and drives AI adoption, evaluation, monitoring, compliance, and organizational transformation.

Own the reference architecture and platform for production AI agents, including agent execution, tool use, state management, recovery, context engineering, model routing, guardrails, and human handoffs. Build shared retrieval, memory, and evaluation infrastructure for offline and online quality measurement. Integrate agents with event-driven systems and customer APIs, review designs, mentor engineers, and connect technical metrics to supply chain business outcomes.

Build, deploy, monitor, and retrain machine learning models for ETA forecasting, status extraction, and logistics automation. Develop NLP and LLM pipelines, manage end-to-end production ML workflows, diagnose performance gaps, and translate model improvements into business value. Collaborate with product, engineering, and operations teams while mentoring data scientists and making architecture tradeoffs.

Leads the architecture and development of scalable Big Data pipelines and agentic AI systems. Establishes technical vision, cloud and application security standards, and enterprise architecture practices. Drives secure, reliable, high-performance production platforms, evaluates emerging technologies, mentors engineers, collaborates cross-functionally, and owns complex initiatives from architecture through deployment and optimization.

Build and scale machine learning systems for search, including ranking models, feature engineering, model deployment, monitoring, experimentation, and online inference. Design fault-tolerant distributed infrastructure, optimize search latency and throughput, and develop reliable ML services from proof of concept through production. Collaborate across engineering and product teams, communicate technical decisions, review code, document systems, and mentor junior engineers.

Owns FinOps strategy, cloud and AI infrastructure cost reporting, capacity planning, optimization tracking, governance standards, and value realization. Partners with engineering, finance, and business leaders to improve cost transparency, forecasting, accountability, and investment decisions. The role also enables federated FinOps teams through reporting, training, benchmarks, and operating practices while mentoring junior professionals and communicating executive-level recommendations.

Leads delivery of enterprise conversational AI platforms, including chatbots and voice bots. Oversees Agile execution, technical architecture, cloud-native engineering, CI/CD, Terraform, Responsible AI, and AI adoption. Partners with product, security, architecture, and business teams while managing risks and executive communication. Mentors engineers and technical leads, supports hiring and performance management, and ensures scalable, secure, compliant, and operationally excellent solutions.

Lead end-to-end delivery of enterprise conversational AI platforms, including chatbots, voice bots, and virtual assistants. Design scalable cloud-native solutions using Amazon Lex, Dialogflow, CI/CD, Terraform, and responsible AI practices. Drive Agile execution, stakeholder alignment, operational excellence, and AI adoption while mentoring engineers and technical leads. Partner with product, architecture, security, and business teams to deliver secure, compliant, and innovative AI solutions.

Build and operate production LLM systems, including prompt and pipeline versioning, evaluations, monitoring, observability, RAG and vector-store infrastructure, safety guardrails, and cost governance. Develop CI/CD and operational tooling for non-deterministic AI outputs, manage reliability and compliance requirements, and collaborate with engineering and product teams to turn AI prototypes into scalable, secure, cost-effective production systems.

Leads complex technical programs spanning product integration and AWS-to-GCP cloud migration. Coordinates engineering, testing, data, cloud, and product teams; translates initiatives into workstreams, milestones, dependencies, and execution plans; manages risks, blockers, validation, reconciliation, cutover readiness, and stakeholder reporting. Requires strong software architecture, API, database, cloud-platform, and technical delivery knowledge, plus experience coordinating distributed teams across India and North America.

Leads complex technical programs across product integration and AWS-to-GCP cloud migration initiatives. Coordinates engineering, testing, data, cloud, and product teams; manages workstreams, dependencies, risks, testing, validation, data reconciliation, release cutover, and production readiness. Communicates status and escalates issues to senior stakeholders while supporting distributed teams across India and North America.

Designs, automates, and manages reliable Azure cloud infrastructure, with a focus on AKS clusters, Terraform, Helm, Argo CD, CI/CD pipelines, Docker, observability, security, networking, and high availability. Collaborates with software engineering and information security teams to improve deployments, system architecture, operational processes, disaster recovery, and cloud cost optimization.

Lead the design and development of scalable web applications using Java, Python, React, and cloud platforms. Architect backend and frontend solutions, optimize deployment pipelines, mentor developers, conduct code reviews, and ensure application performance, security, and scalability. Preferred experience includes microservices, container orchestration, CI/CD, observability tools, OAuth2, and cloud fault-tolerance patterns.

Designs, builds, and scales agentic AI, LLM, predictive, prescriptive, and reinforcement learning systems. Develops autonomous workflows, customer lifecycle models, next-best-action engines, causal models, and production AI APIs. Partners with MLOps and data engineering teams on scalable deployment, monitoring, and model reliability. Leads complex AI initiatives, establishes engineering standards, reviews code and models, and mentors junior engineers while translating business needs into production solutions.

Own release quality for SaaS products through requirements review, test planning, manual and automated testing, defect triage, and post-release validation. Develop Playwright and TypeScript E2E automation, improve unit test coverage, establish accessibility checks, monitor quality metrics, and automate non-functional testing. Collaborate with product managers, developers, and engineering managers while analyzing logs and data to identify issues.

Leads site reliability and cloud infrastructure initiatives for business systems. Designs and deploys integrations, infrastructure-as-code, CI/CD pipelines, containerized platforms, monitoring, high availability, and disaster recovery solutions. Diagnoses customer integration issues, develops utilities and SDKs, and communicates technical issues to stakeholders. Requires strong AWS, Terraform, Kubernetes, observability, scripting, networking, security, leadership, and cross-functional collaboration expertise.

Build and maintain automated cloud, product, and AI/ML deployments; manage AWS infrastructure through Terraform and other IaC tools; maintain CI/CD and MLOps pipelines; implement monitoring, AIOps, observability, self-healing, disaster recovery, and incident-management solutions; automate operations with Python and scripting; support Kubernetes, GPU/EKS clusters, model-serving frameworks, vector stores, and LLM workflows while meeting service availability and performance targets.

Leads architecture and technical governance for scalable, highly available cloud-native backend services. Responsibilities include designing distributed systems, standardizing cloud usage, conducting architecture reviews, managing cloud costs, advancing serverless and Kubernetes platforms, mentoring engineers, and communicating technical risks to business stakeholders. The role requires extensive software architecture experience, expertise in cloud infrastructure, orchestration, event-driven systems, infrastructure as code, backend development, and enterprise-scale implementations.

Leads and mentors pre-sales Solution Architects supporting complex enterprise telecom and technology deals. Oversees network, cloud, wireless, 5G, voice, security, and automation architectures; sponsors executive-level deal escalations; guides legacy modernization and go-to-market strategies; coordinates Sales, Product, OEM, and Implementation teams; ensures regulatory and architectural compliance; and promotes LLM-based workflow automation.

Leads enterprise Data Loss Prevention and cybersecurity operations across endpoint, network, email, SaaS, cloud, and multi-cloud environments. Designs and tunes DLP controls, investigates data exfiltration and insider-risk incidents, develops detection content, and manages response activities. Uses AWS, Azure, SIEM, SOAR, automation, and AI/ML-driven analytics to improve detection and reduce response times. Provides technical leadership, mentors analysts, develops metrics, and partners with business, technology, and risk stakeholders.

Supports and maintains enterprise GenAI, Big Data, and analytics platforms across cloud and on-premises environments. Responsibilities include L2/L3 production support, Kubernetes and Linux administration, incident management, monitoring, capacity planning, disaster recovery, application onboarding, platform reliability, and automation using Python, Shell, or Ansible. The role also supports Databricks, infrastructure maintenance, compliance, observability, model access, stakeholder engagement, documentation, and mentoring.