Top Artificial Intelligence Jobs in Chennai

The AI Engineer will develop and deploy AI/ML models and solutions, collaborate with teams, and ensure production readiness while addressing complex business problems.

The Software Development Engineer in Test (SDET) designs and maintains automation frameworks using Microsoft Playwright, integrates AI tools for test generation, and performs API testing while collaborating with a global team.

The Senior Engineer will develop and deploy machine learning models and workflows, mentor junior engineers, and collaborate with cross-functional teams to improve patient care through innovative solutions.

The AI Engineer will develop and deploy GenAI applications, serve as a technical advisor, and collaborate on strategic initiatives in AI at Databricks.

The AI Engineer will develop, implement, and maintain AI systems and algorithms, ensuring data quality and deploying models in production. They will collaborate with teams to build data pipelines and ensure AI solutions meet requirements.

Lead architecture and hands-on delivery of production agentic AI solutions: design reusable accelerators, integrate LLMs and retrieval (RAG), ensure reliability, security, observability, and guardrails, collaborate with cross-functional teams, mentor engineers, and contribute IP, patterns, and production best practices across clients.

Design, build, and scale no-code/low-code automation workflows and AI agents across business functions. Analyze processes, integrate systems via APIs/webhooks, implement OpenAI/Claude-powered solutions, build decision and scoring frameworks, deliver client-facing automation projects, and produce documentation and reusable playbooks to improve operational efficiency.

Drive the expansion of software development and AI services by managing client relationships, building sales pipelines, and negotiating contracts.

Execute fashion design briefs using Raspberry AI to produce flats, tech packs, colorways, prints, mood boards, and concept visuals. Translate creative direction into precise prompts, iterate on feedback, maintain brand-consistent quality, document workflows, flag platform issues, and partner with US Customer Success for intake and delivery under tight turnarounds.

Design and build production LLM-based agent systems, governance knowledge pipelines, hybrid retrieval and evaluation frameworks, and platform infrastructure. Implement behavioral shaping, observability, and constraints to ensure agents align with governance and compliance requirements, collaborating with product and data teams.

Lead design, training, and fine-tuning of large-scale ML/DL models (LLMs and generative systems) for drug discovery. Build scalable training pipelines, data pipelines, and production-ready model deployments; collaborate with engineering teams; translate research into applied AI solutions and continuously improve model performance and reproducibility.

Evaluate relevance of filters and options on desktop and mobile, ensuring they match customer queries and preferences. Follow guidelines, conduct online research, verify assessments for accuracy and consistency, and complete required training and qualification tests before starting. Work remotely on a flexible, part-time freelance schedule.