Top Artificial Intelligence Jobs in Chennai

Lead research and engineering of cutting-edge AI models, fine-tune LLMs, design agentic systems, prototype novel algorithms, optimize training pipelines, benchmark and deploy scalable RAG-powered solutions, ensure ethical AI practices, and mentor junior researchers while integrating AI into production products.

Lead research and development in AI/ML, design scalable pipelines, implement models, and collaborate with cross-functional teams for optimal solutions.

Design, prototype, and benchmark advanced AI/ML algorithms and agentic systems; optimize large-scale training pipelines; integrate generative AI, RAG, and Azure OpenAI solutions into production; collaborate with cross-functional teams; ensure ethical, interpretable, and robust model deployment.

Lead and operate enterprise-scale cloud infrastructure and SaaS/PaaS production systems. Manage Kubernetes workloads, implement SRE best practices (Terraform, CI/CD, observability, incident response), automate with Python/JavaScript/Go, apply cloud security measures, and leverage AI-Ops tools for operations and analysis.

Lead the AI Capability Centre, driving strategic development and operational excellence in AI solutions while managing a team of AI experts.

The AI Engineer is responsible for designing, validating, and supporting engineering processes, ensuring compliance with development plans and customer requirements.

Lead multiple engineering teams to deliver an AI-native SaaS product. Define technical strategy and architecture, drive platform and LLM integrations, scale teams and processes, ensure high-quality product delivery, and collaborate cross-functionally to build reliable, scalable AI-powered capabilities.

Lead the ethical use and governance of AI, ensuring compliance with legal standards, managing AI risks, and fostering collaboration across teams.

The Technology Architect will lead AI architecture governance, establish standards for AI applications, and ensure alignment with enterprise goals. Responsibilities include overseeing production AI deployments, promoting best practices, and collaborating on AI initiatives across the organization.

Develop Power Apps, Power Automate solutions and Power BI reports using SharePoint/Dataverse; gather requirements, convert to process flows and user stories; lead development, run design reviews, support UAT, handle change requests, and ensure compliance.

Execute independent technology and cybersecurity control testing across SDLC, cloud (Azure/AWS), access control, encryption, endpoint, network, logging, incident response, and vulnerability management. Assess control design and effectiveness, document findings (Risk & Control Matrices), collaborate with business and risk teams to remediate gaps, and report results to management.

Design, build, and operate agentic LLM-powered workflows, autonomous agents, and RAG/vector retrieval systems. Own end-to-end delivery including CI/CD, IaC, observability, DevSecOps, and Salesforce integrations to productionize enterprise AI for GTM applications.

Lead AI/ML engineering vision and roadmap for healthcare and life sciences. Oversee multiple client engagements, design and deploy scalable production-grade AI solutions (ML, NLP, deep learning, computer vision, LLMs), ensure regulatory readiness, responsible AI practices, and drive adoption and value realization while managing executive client relationships and expanding AI adoption.

Build and maintain Java backend services and end-to-end features (backend and frontend). Design data models and DB schemas, integrate with frontend, perform code reviews, troubleshoot, deploy with DevOps, and collaborate with US teams and partners to expand the supply-chain platform.

Lead technology vision and architecture for enterprise projects; design cloud-native, data-driven and Generative AI solutions; ensure scalability, security, governance, and engineering excellence; run architecture reviews, POCs, and implementations; evaluate emerging technologies; influence clients via workshops and executive engagements; mentor architects and distributed engineering teams.

Lead technology strategy and governance for multiple business units, aligning IT investments with business goals. Drive digital transformation, cloud and automation adoption, risk management, service delivery, and cost optimization. Build and mentor high-performing teams, engage C-suite stakeholders, and ensure enterprise integration and compliance to deliver measurable business value across global operations.

Build end-to-end full-stack AI features on a Ruby on Rails backend and React frontend, design and run experiments (A/B tests and AI evaluations), implement AI infrastructure for reliable LLM inference, and iterate quickly to scale production-ready LLM-powered products.

Design and implement Generative AI solutions to improve operational efficiency. Collaborate with teams to identify opportunities and ensure data governance.

Lead the development of AI-powered customer support solutions, guiding a team to build scalable, reliable, and secure systems using LLMs and third-party integrations.

Design and build enterprise-scale AI search and retrieval systems using Azure AI Search and Azure OpenAI. Implement RAG/vector search, embeddings, prompt engineering, secure document-level access controls, scalable backend services, and observability to improve relevance, accuracy, and latency. Mentor engineers and drive architecture for secure, compliant enterprise RAG platforms.

Manage and grow an India-based AI Development team to deliver enterprise agent applications. Translate product priorities into sprints, partner with the Director of AI on roadmap and technical execution, establish async-first delivery rhythms across US/India, handle India operations (hiring, performance, compensation), coach on modern programming practices, and unblock work through cross-team relationships.

Lead and align Engineering, ML, and Analytics to deliver scalable, reliable production AI and data systems. Own technical direction, architecture, MLOps, and platform reliability while partnering with Product, Sales, and Customers to ensure engineering work maps to measurable business outcomes.

Build and optimize Angular front-end features that integrate AI/ML models and APIs. Collaborate with data scientists, backend engineers, and designers to implement responsive, secure UI components, visualize model outputs, and deploy AI-powered web functionality.

Hands-on pre-sales technical lead who designs AI/data solution architectures, builds POCs and reusable assets, authors RFP responses, and transitions solutions to delivery across cloud data platforms, ETL/ELT, and applied ML to drive client outcomes.

Build and deploy production-grade generative AI applications: design multi-agent systems and LangGraph workflows, implement advanced RAG with vector DBs, fine-tune and host LLMs, develop scalable FastAPI backends, optimize latency/cost, and containerize services for production.