Top AWS Jobs in Chennai

Own cloud and infrastructure security architecture across Azure and AWS, including network segmentation, workload isolation, hardened images, Kubernetes, policy as code, AI workload security, and vulnerability management. Build secure-by-default infrastructure modules, landing zones, and automated evidence processes. Establish cloud posture and workload protection practices, drive remediation through pull requests, and ensure controls satisfy ISO 27001, SOC 2, and future regulatory requirements.

Designs end-to-end AI and generative AI solutions, leads RFP responses, develops proposals and sales collateral, conducts client workshops, and engages executive stakeholders. The role establishes AI governance, compliance, and observability frameworks; partners with engineering teams on delivery; and manages and mentors solution architects, data scientists, and engineers. It requires strong expertise in GenAI stacks, RAG, multi-agent systems, LLMOps, responsible AI, consulting, and enterprise pre-sales.

Defines enterprise security architecture strategy and standards across Nokia, leading complex initiatives involving Zero Trust, IAM, multi-cloud security, application and network segmentation, AI security, and cyber resiliency. Advises senior stakeholders on security strategy, supplier risk, M&A due diligence, and regulatory matters. Assesses vulnerabilities, validates security solutions, supports penetration testing and hardening, and delivers automated security capabilities across cloud-first infrastructure and DevSecOps environments.

Develop and lead scalable SaaS features for government-focused products using ReactJS, TypeScript, GraphQL, and NodeJS. Translate business requirements into technical solutions, troubleshoot complex issues, mentor engineers, improve development processes, and promote operational excellence. The role requires full-stack development, cloud-native application experience, AI-driven UX familiarity, event-driven architecture, API integration, observability, and AWS or Azure expertise.

Build and improve full-stack APIs, microservices, database models, and frontend experiences for enterprise government software. Own features from problem definition through production monitoring, collaborate with Product and Design, and develop AI-powered workflows and user experiences. Use AI-assisted coding tools, review human- and AI-generated code, mentor teammates, improve engineering processes, and work directly with customers in a fast-paced SaaS environment.

Develop and maintain SAP ABAP solutions, customizations, reports, workflows, and integrations. Build SAP data extraction and integration pipelines using ODP, CDS Views, OData, and SAP Datasphere. Translate business requirements, especially SAP SD processes, into scalable technical solutions and integrate SAP data with cloud platforms. Collaborate with functional consultants, data engineers, stakeholders, and external partners while independently resolving technical issues and strengthening internal SAP capabilities.

Develops, upgrades, integrates, commissions, and supports complex broadcast and OTT systems across on-premise and cloud environments. Responsibilities include third-party system integration, coding and scripting, technical design, deployment planning, acceptance testing, documentation, performance planning, audit reporting, and staff training. The role also supervises associate engineers and requires expertise in Windows and Linux servers, networking, databases, API testing, and broadcast or digital media environments.

Designs end-to-end technology solutions for media, OTT, and digital platforms. Translates business requirements into scalable and secure architectures, evaluates technologies, recommends integrations, and guides implementation. Collaborates with business, engineering, infrastructure, and technology teams while ensuring alignment with enterprise architecture and security standards. The role requires AWS expertise, cloud and microservices experience, infrastructure as code, programming and scripting skills, solution documentation, and stakeholder management.

Build and operate production AI systems for financial products, including LLM pipelines, RAG, document extraction, anomaly detection, model serving, and automated reconciliation. Develop reliable backend integrations, vector search infrastructure, monitoring, evaluation, observability, and human-in-the-loop workflows. Collaborate with product, backend engineering, and data science teams to establish scalable AI engineering practices.

Build and deploy production-ready Generative AI and LLM applications, including RAG systems, chatbots, copilots, intelligent automation, and agentic workflows. Develop Python backend services, integrate LLM APIs, optimize model quality and performance, implement evaluation and guardrails, and troubleshoot deployed systems. Collaborate with engineering, product, operations, and business teams in a globally distributed environment while translating AI capabilities into scalable production solutions.

Provides technical support for a zero-trust cloud networking platform. Resolves, escalates, tracks, and closes customer incidents and service requests within SLAs. Troubleshoots WAN/LAN, software-defined networking, cloud networking, firewalls, ACLs, and cloud security environments across AWS, Azure, and GCP. Works rotational 24/7 shifts with globally distributed teams and supports incident, change, and problem management processes.

Own platform architecture, infrastructure security, access controls, database maturity, and AWS migration. Write secure production code, establish infrastructure standards, review security changes, partner with InfoSec, mentor engineers, troubleshoot recurring failures, and guide DevOps implementation. The role also supports AI infrastructure, model serving, agent observability, React and TypeScript applications, and infrastructure security on-call responsibilities.

Build, test, deploy, and maintain production automations using n8n, custom code, AI models, PostgreSQL pipelines, and cloud platforms. Own automation initiatives end to end, integrate systems, monitor reliability and business outcomes, maintain CI/CD pipelines, respond to incidents, troubleshoot failures, and support security and compliance reviews. The role also involves stakeholder collaboration, process improvement, research into emerging automation technologies, and on-call participation.

Provides database consulting and reliability services for customer environments, including MySQL database design, administration, monitoring, backup and disaster recovery, replication, failover, troubleshooting, and infrastructure optimization. Advises clients on operational best practices, supports incident and change management, enhances automation and monitoring tools, contributes to presales and technical content, and mentors database consultants.

Design, build, and maintain centralized data pipelines, warehouses, lakes and hubs. Assemble complex datasets, implement ETL processes, build analytics tools and reports, support cross-functional teams, ensure secure cross-region data separation, and create product data tools to enable insights on acquisition and operational metrics.

Lead the architecture and delivery of complex SaaS applications and platform services across the full stack. Build scalable APIs, databases, cloud-native services, and AI-powered workflows while improving reliability, observability, and developer productivity. Provide technical leadership through architecture reviews, mentoring, engineering standards, and production ownership. The role requires autonomy, deep TypeScript and Node.js expertise, full-stack delivery, internal tooling experience, and experience shipping AI capabilities in production.

Leads the design and development of scalable AI-powered productivity tools and modern web applications. Responsibilities include architecting generative AI and RAG workflows, integrating LLMs, adopting AWS or GCP cloud-native architectures, collaborating cross-functionally, mentoring engineers, and driving technical initiatives that improve employee productivity.

Lead the design and production deployment of LLM-powered AI agents, generative AI systems, and retrieval-augmented generation infrastructure. Build and fine-tune models, develop multi-step agents, apply data science methods, and establish evaluation, monitoring, observability, and feedback systems. Partner with product, backend, and infrastructure teams to scale AI capabilities across messaging, scheduling, sales, and operations while influencing the AI roadmap and mentoring engineers.

Supports CI/CD pipeline maintenance, cloud and on-premises infrastructure, application deployments, containerization, scripting automation, monitoring, troubleshooting, and incident resolution. Collaborates with Development, QA, and Security teams across development, staging, and production environments.

Provide technical support to customers by debugging and resolving application issues, advising on architecture and integrations, improving the platform and AI agent, maintaining documentation, automating support workflows, and handling platform incidents and customer communications. The role requires strong TypeScript and React skills, modern web application knowledge, production debugging experience, clear written communication, and customer-facing experience.

Delivers and supports Genesys Cloud implementations for enterprise customers and partners. Responsibilities include technical solution deployment, project-plan execution, testing, post-go-live support, customer environment management, escalations, training, troubleshooting, documentation, and project-status communication. The consultant collaborates with project managers, quality assurance, customer care, and internal teams while maintaining implementation standards, billable utilization, timesheets, and ongoing product expertise.

Lead global MLOps delivery by designing scalable software architectures, data pipelines, and machine learning solutions. Guide architecture decisions, collaborate with research, architecture, and product teams, and coordinate software delivery. Manage and mentor developers, conduct code reviews, maintain documentation, promote engineering best practices, oversee testing and CI/CD, and remain accountable for technical debt and system quality.

Design, build, and operate AWS/Azure cloud infrastructure and DevOps workflows. Own IaC, CI/CD, container and serverless deployments, monitoring, security, cost optimization, and cloud migrations while automating operations and collaborating with development, data, and ML teams.

Develop, test, document, deploy, and support Java applications using JavaScript, Spring Boot, REST APIs, SQL, cloud services, and DevOps tools. Responsibilities include creating unit tests, contributing to technical designs, maintaining documentation, providing production support, following software standards, participating in Agile SDLC activities, and improving continuous integration and delivery practices while managing technology risks.

Develop, test, document, deploy, and support software applications using Snowflake technologies and SQL. Design application components, create unit tests, follow coding and design standards, and participate in SDLC and Agile practices. Collaborate with architects, product managers, subject matter experts, and end users. Contribute to CI/CD improvements, production support, risk controls, and continuous process improvement while using AWS, DevOps, scripting, and AI tools.