Top Artificial Intelligence Jobs in Chennai

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.

Design and build scalable, AI-native backend microservices (Java/Spring Boot) using hexagonal architecture. Own domain models, Kafka event contracts, DB schemas (MongoDB, PostgreSQL, Cosmos), Temporal workflows, and AI integration patterns. Ensure performance, reliability, observability, and mentor engineering teams.

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 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.

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.

Maintain and improve on-premises MLOps infrastructure: deploy, monitor, and optimize ML models; troubleshoot Linux/Docker/Kubernetes stacks; build CI/CD, deployment, and monitoring tools; productionize research artifacts; enforce testing and engineering standards; collaborate with data scientists and software engineers to scale ML systems.

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.

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 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.

Senior SRE responsible for administering enterprise-scale SaaS/PaaS cloud infrastructure, managing Kubernetes workloads, applying SRE principles (CI/CD, Terraform, observability), automating with Python/JavaScript/Go, ensuring cloud security, and leveraging AI-Ops tools for operations and incident response.

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

The Senior Data Scientist will architect real-time fraud detection systems, process large data sets, mentor teams, communicate findings, and innovate using AI technologies for effective risk management.

Support and enhance ADI's global compliance program aligned to enterprise risk and ISO 37301. Monitor regulatory developments, update policies, execute risk‑based monitoring and testing, manage investigations and remediation, support audits, develop training and communications, track metrics, and collaborate with Legal, HR, Finance, IT, and Operations to drive continuous improvement.

Lead and support execution of ADI's global compliance programs: risk‑based monitoring, policy management, testing, investigations, training, ISO 37301 alignment, audits, remediation, and cross‑functional stakeholder coordination.

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

Evaluate and author high-quality computer science content to improve AI model reasoning and accuracy. Analyze complex CS problems, create scenarios/datasets, review AI outputs for correctness, and collaborate remotely to refine guidelines and documentation.

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.

The Lead AI Engineer designs and delivers AI/ML and Generative AI solutions for banking platforms, integrating data and enabling AI-driven decisions.

As a Staff Backend Engineer, you'll design backend architecture for AI governance, ensuring auditability and compliance, while collaborating with engineering teams to enhance product capabilities.

Evaluate AI-generated technical content, craft and answer advanced ML/AI prompts, assess model responses for accuracy, relevance, and clarity, identify errors or hallucinations, and provide feedback to improve AI systems.

The Senior Software Engineer will develop and deploy AI/ML solutions, improve model performance, and collaborate with stakeholders to enhance customer experience.