Top Artificial Intelligence Jobs in Chennai

This role involves reviewing AI-generated content, ensuring cultural relevance, generating content, and providing assessments to improve AI models. Attention to detail and analytical skills are crucial.

The AI Video Editor / Motion Designer creates AI-driven videos to enhance advertising effectiveness. Responsibilities include video production, concept development, utilizing AI tools, performance analysis, and collaboration with team members.

Design, deploy, and maintain GPU-accelerated enterprise infrastructure (NVIDIA DGX/HGX, Nutanix). Administer VMware and Kubernetes clusters across distributions, automate tasks with scripting/Ansible, monitor performance, and collaborate with DevOps and data science teams to ensure scalable, highly available AI/ML systems.

The Billing Associate will manage outbound insurance tasks, ensure AI performance, and support insurance setups while collaborating on product development.

Design and ship a 14-domain skills taxonomy and SDK/CLI tooling, operate the MCP server, integrate agent protocols, improve LLM grounding for crypto, run developer hackathons, and produce technical content to grow the ecosystem.

Build and scale AI-driven workflow features: integrate AI into Email/SMS/code actions, implement RAG and knowledge-base solutions, develop data extraction, text-to-voice, and analysis tools, optimize low-latency APIs, and mentor junior engineers.

Design, build, and deploy AI-powered legal applications using LLMs, RAG, and agentic AI. Partner with legal stakeholders to translate workflows, build document ingestion and vector search pipelines, ship production-grade features, implement governance/security controls, and mentor/legal users while aligning solutions with enterprise architecture and monitoring quality and evaluation metrics.

Build and scale production-grade AI/LLM capabilities across backend services: design agentic workflows, implement RAG pipelines, develop secure AI APIs, enforce safety/compliance, enable observability and evaluation, optimize reliability and cost, and contribute to CI/CD, IaC, testing, documentation, and cross-team delivery.

Design and build secure, scalable enterprise automation using n8n and related platforms. Implement AI-enabled workflows, API-first and event-driven integrations, CI/CD, observability, governance, and monitoring. Lead architecture and reviews, define standards and templates, mentor teams, and measure impact via automation metrics.

Lead design and delivery of production-grade agentic AI systems: discovery with clients, build multi-agent/ RAG pipelines, develop backend integrations, deploy and scale agent workloads on AWS, and implement safety, observability, and human-in-the-loop controls.

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.

As an AI Data Expert, you will evaluate AI-generated outputs, provide culturally relevant feedback, ensure content accuracy, and participate in quality assurance. This role requires strong analytical skills and attention to detail.

The AI Data Expert position involves evaluating AI outputs, generating content, and providing annotations to enhance AI training, all while considering cultural context. This role requires detail-oriented analysis, native language fluency, and strong English command.

As an AI Data Expert, you'll evaluate AI-generated outputs, review text, analyze multimedia, and provide structured feedback based on cultural standards.

The role involves evaluating AI outputs, generating content, providing annotations, and ensuring quality through cultural and contextual awareness.

The role involves reviewing AI outputs, generating content, ensuring cultural accuracy, and providing structured feedback to improve AI models.

Review and evaluate AI-generated outputs, provide annotations, and contribute cultural insights to improve AI training. Requires detail-oriented judgment and strong language skills.

Design and implement graph compiler optimizations (fusion, quantization, tiling) to convert TensorFlow/PyTorch models into IR, improve performance and hardware utilization, collaborate with ML researchers and hardware architects, and lead a team focused on compiler and code-generation improvements.

Design and build a production multi-agent harness and MCP integrations that operate across ERPs, CRMs, and business tools. Own end-to-end production concerns (reliability, observability, permissions, safe workflow execution), scope the product, make architecture decisions, and ship features working closely with CTO, product, engineering, and design. Stay current with agent frameworks and use tools like Claude Code in development.

Lead customer-facing SaaS implementations and onboarding, design and deliver custom REST API integrations, troubleshoot complex technical issues, communicate clearly with stakeholders, and drive long-term customer success.

The AI Implementation Manager is responsible for managing customer onboarding, implementing solutions, and ensuring customer satisfaction in B2B environments, with a focus on technical integrations and strong communication with clients.

Build and deploy autonomous AI agents and internal copilots that research, enrich, reason, and execute GTM workflows. Implement RAG with embeddings and vector DBs, integrate agents with HubSpot and internal systems, automate data pipelines and scraping, and own agent systems end-to-end from prototype to production.

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.