Top Artificial Intelligence Jobs in Chennai

Design, build, and optimize AI-driven automation workflows using platforms like n8n, Make, and Zapier. Train, fine-tune, and deploy custom LLMs (OpenAI, Hugging Face, TensorFlow) and integrate LLM APIs. Collaborate with stakeholders, troubleshoot and document workflows, and stay current on generative AI and automation technologies.

Design, build, and optimize AI-driven automation workflows using platforms like n8n, Make, and Zapier. Train, fine-tune, and deploy custom LLMs (OpenAI, Hugging Face, etc.), integrate LLM APIs, collaborate with stakeholders, troubleshoot and document solutions, and stay current on generative AI advances. Mandatory technical assessment required.

Build end-to-end infrastructure for AI agents: design React/TypeScript UIs, implement Python agent harnesses, develop Kubeflow-based MLOps pipelines, fine-tune foundation LLMs (LoRA/QLoRA/SFT/RLHF), deploy and operate services on Kubernetes, integrate agent frameworks, and apply software engineering best practices, testing, and CI/CD.

Design and implement production-grade AI agent harnesses, build and operate MLOps pipelines with Kubeflow, fine-tune foundation LLMs (LoRA/QLoRA, SFT, RLHF), deploy and manage services on Kubernetes, integrate agent frameworks, and apply software engineering best practices to move models from prototype to production.

The AI Creative Designer creates high-quality, AI-generated visuals for marketing campaigns, collaborating with teams to optimize visual content for conversion rates.

Evaluate and improve AI-generated tax analyses by reviewing legal and tax documentation, analyzing statutory language, identifying compliance issues, contributing to tax AI datasets, and providing structured feedback while monitoring U.S. tax law updates.

Contractor role to review and analyze U.S. tax statutes, Treasury Regulations, and the IRC; interpret complex tax provisions and identify nuances; summarize tax concepts into structured insights; provide feedback to improve AI-generated tax responses; and collaborate with AI development teams while staying current on legislative changes.

The Senior AI/ML Engineer will design, develop, and deploy language models for African languages, focusing on NLP applications and cultural context.

The role involves reviewing AI-generated outputs, generating content, and ensuring cultural accuracy in various media formats. Attention to detail and analytical skills are essential.

The AI Product Manager will lead product discovery and strategy, prototype solutions using AI tools, perform competitive analysis, track product metrics, advocate for user experience, and collaborate with different teams.

Design, build and ship native Android features for an AI-enabled neobank using Kotlin. Integrate backend APIs, improve performance and reliability, collaborate with product and design to simplify financial user journeys, and apply on-device ML where it improves UX.

Build and ship native Android features in Kotlin and Jetpack Compose; integrate REST APIs; improve performance, crashes and memory; collaborate with product/design; use analytics and on-device AI (TensorFlow Lite) to enhance user journeys for insurance and financial services.

The Applied AI Researcher will design experiments, train models, and build pipelines for a GenAI platform while contributing to research and deploying systems in production.

Responsible for leading end-to-end AI research projects, developing domain-specific models, mentorship, and optimizing research-to-production processes while collaborating across disciplines.

The Principal Applied AI Researcher will define and lead domain-specific model strategies, manage model lifecycle, mentor researchers, and influence platform decisions in AI research.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

Assist in developing AI solutions for financial planning, working on projects involving data structures, algorithms, and integrating AI features into the platform.

The AI Manager will lead a global team in AI project delivery, manage AI roadmaps, oversee LLMOps pipelines, and engage with stakeholders while ensuring compliance and performance metrics are met.

The AI QA Specialist will design and execute test strategies for AI systems, validate model outputs, implement monitoring dashboards, and ensure compliance with safety standards.

The MDM Specialist will design and implement master data management solutions, integrate AI workflows, and ensure data governance and quality across customer and vendor domains.

Design and implement production-grade AI models and algorithms, lead AI initiatives across organizations, enhance Agentic AI capabilities, and collaborate with teams to develop high-impact AI features.

Build and deploy full-stack AI applications integrating LLMs, RAG architectures, vector databases, and multi-agent systems. Develop Python backends, APIs, ingestion pipelines, responsive interfaces, and real-time dashboards. Design and optimize PostgreSQL databases, containerize applications with Docker and Kubernetes, manage AWS and GPU infrastructure, and operate Linux environments. Mentor developers, conduct demonstrations, evaluate emerging AI technologies, and improve reliability through testing, debugging, performance tuning, and quality processes.

Leads the architecture and delivery of production-grade agentic and generative AI systems, including LLM agents, RAG pipelines, multi-agent workflows, and scalable cloud applications. Guides technical architecture, production engineering, LLMOps, evaluation, observability, security, and responsible AI practices. Mentors AI/ML and backend engineers, conducts design and code reviews, and collaborates with product, data, platform, security, compliance, and executive stakeholders.

Leads end-to-end cloud and platform engineering consulting engagements, owning scope, governance, delivery quality, client relationships, and executive outcomes. Manages a 2–3 person engineering pod through staffing, coaching, and performance development. Oversees multi-cloud discovery across AWS, Azure, and GCP, develops prioritized recommendations and roadmaps, applies AI-driven solutions, and evolves repeatable Rapid Solutions playbooks, templates, and delivery standards.

Lead end-to-end cloud and platform engineering consulting engagements, owning scope, governance, client relationships, delivery quality, and executive outcomes. Manage and coach a 2–3 person engineering pod, oversee staffing and utilization, conduct multi-cloud technical discovery, and develop prioritized recommendations and roadmaps. Evolve Rapid Solutions offerings, playbooks, templates, and delivery standards while applying AI-driven solutions to improve efficiency and insight.