Top Artificial Intelligence Jobs in Chennai

Design and implement the core AI layer for enterprise workflows: document extraction, retrieval, ranking, evaluation, agentic task execution, structured data generation, and integration into a polished product with emphasis on accuracy, traceability, and human review.

Design, build, and own AI-powered full-stack platforms and features from discovery through production. Embed AI into products and workflows, ensure reliability and security, support incidents, and mentor teammates.

Design polished, user-centric mobile and web interfaces for BJAK's AI-driven neobank products. Convert requirements into wireframes, flows, prototypes and high-fidelity UI. Maintain and evolve the design system, ensure accessibility and responsiveness, iterate using research and analytics, and collaborate with PMs and engineers to deliver pixel-perfect implementations across insurance, payments, investments and related financial services.

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

Design, build, and deploy enterprise AI solutions including ML, deep learning, computer vision, generative AI, and agentic systems. Develop feature pipelines, train/optimize models (PyTorch/TensorFlow), implement RAG/embedding-based retrieval, MLOps workflows, monitoring, and multi-agent architectures. Collaborate with stakeholders and document models, architectures, and best practices.

Lead architecture and development of agentic AI solutions for optical networks: design agent orchestration, memory, tool integration, guardrails, and human-in-the-loop workflows; convert processes into autonomous/semi-autonomous automation; document designs and best practices for scalable delivery.

Build and productionize LLM-powered agents, workflows, and RAG systems. Apply prompt engineering, embeddings, fine-tuning, and traditional ML to automate tasks and improve products. Mentor teammates and help design scalable, production-grade AI infrastructure while staying current on LLM advances.

Develop and deploy AI/ML models using Python. Focus on model development, production deployment, and collaborating with cross-functional teams. Communicate findings, solve technical problems, and work in a fast-paced environment. React and TypeScript experience and AI security/risk familiarity are nice-to-haves.

Lead design and implement a data governance operating model: define ownership/stewardship/RACI, policies, controls, data contracts, quality, metadata, lineage and cataloguing. Ensure privacy, security and GDPR compliance, embed Responsible AI/AI governance, and translate governance into practical delivery for city, sensor and AI-ready datasets. Provide senior leadership and stakeholder engagement; advise on governance for video, IoT, geospatial and simulation use cases.

Design, build, and maintain AI platform and ML pipelines by assembling LLMs and agentic workflows, integrating assistants with systems, prototyping in low-code and code, writing tests and CI/CD, and iterating with stakeholders on domusAI, domiAI, domusDocs and multi-agent frameworks.

Lead AI strategy and implement GenAI, agentic AI, and automation to modernize legacy systems, integrate AI into engineering lifecycle, and build production-grade, scalable AI solutions with cloud, containerization, MLOps, and data pipeline best practices.

Design and architect AI/GenAI solutions on GCP; create architecture diagrams; develop, deploy, and optimize ML models; preprocess and manage large datasets; provide technical guidance to engineering teams; and present solutions to clients.

Design and implement end-to-end machine learning solutions: analyze use cases, build statistical and ML models, prepare and enrich data, implement scalable PySpark models in Databricks, and collaborate with product and engineering to productionize analytics for personalization and business insights.

Lead enterprise clients to improve AI search visibility through analysis, custom GEO playbooks, C-suite presentations, prompt testing, monthly reporting, and cross-functional product collaboration to drive platform adoption and measurable visibility gains.

Build AI-driven developer tools: coding assistants, knowledge retrieval, workflow automation, and LLM-powered apps for code generation, understanding, and test automation. Collaborate with engineering teams to identify pain points, ship solutions, and experiment with prompt engineering, RAG, and AI agents.

Support development of internal LLM-based tools (coding assistants, RAG pipelines, prompt optimization), improve engineering efficiency, test and document AI tools, and research emerging AI technologies.

Early-career software engineer in a fixed-term accelerator contributing to backend/full-stack feature development, testing, CI/CD, and deployments. Collaborate on API and system design, integrate and deploy AI/LLM capabilities (LLM APIs, RAG, embeddings, agents), build datasets/benchmarks, monitor performance, debug issues, and produce technical documentation.

Early-career role building AI-powered developer tools and internal LLM applications. Tasks include coding assistants, lightweight RAG pipelines, prompt optimization, testing, documentation, and researching emerging AI technologies to improve engineering productivity.

Build internal AI developer productivity tools (coding assistants, retrieval systems, workflow automation). Develop LLM-powered apps for code generation, understanding, and test automation. Integrate AI across the SDLC, embed with teams to remove friction, experiment with prompt engineering, RAG, and AI agents, and evaluate emerging AI technologies.

Build and optimize high-traffic, responsive web applications and hybrid in-app pages. Implement user-facing features, improve performance and scalability, and create libraries/frameworks to accelerate development and enhance code quality.

Early-career DevOps role focusing on Kubernetes and AWS operations, embedding security into the development lifecycle, automating processes, and implementing CI/CD solutions. Remote, fixed-term accelerator program for students and recent graduates.

Design, build, and maintain high-performance backend services and APIs using Java/Spring Boot. Develop and productionize recommendation algorithms and LLM systems, optimize LLM workloads (including on-prem), ensure scalability, reliability, and security, and collaborate across time zones with product and project teams to own end-to-end architecture.

Lead planning, design, delivery and promotion of a customer-service chatbot management platform. Use AI and big data to improve CS operations (corpus training, SOPs, assistant replies, summaries). Collaborate with engineering, UX, and CS teams. Monitor KPIs and user cases to drive product improvements.

Early-career research role designing and running experiments on LLM reasoning, post-training alignment, and test-time scaling. Implement model variants and training pipelines in PyTorch/Hugging Face, evaluate on crypto-native data, maintain experiment tracking (W&B), and partner with engineering to translate research to production.

Six-month early-career internship building LLM-powered agent workflows and production AI components. You'll design prompts, retrieval and tool-use logic, run benchmarks, improve quality/latency/reliability/safety, contribute to backend services/APIs, and ship working prototypes alongside full-time engineers.