Top Artificial Intelligence Jobs in Chennai

Design and build agentic AI solutions and complex agent workflows using Python. Train and deploy models on AWS or other cloud, build prototypes with Streamlit/Gradio, apply MLOps, collaborate in Agile/Scrum with Git and JIRA.

Lead design, operation, and reliability of large-scale AI/HPC clusters. Manage day-to-day operations, incident response, automation, performance tuning, scheduler and storage optimization, and collaborate with researchers and global teams to improve GPU-accelerated infrastructure.

The AI Platform Engineer leads the development of production AI agents and components, collaborates on AI implementations, and maintains AI systems for reliability and observability.

Lead architecture and engineering of enterprise-scale Generative AI and data platforms. Design reusable platform services for end-to-end AI/ML lifecycle, build agentic applications and event-driven systems, enforce CI/CD and DevSecOps, ensure security/governance/observability, mentor engineers, and drive platform modernization using cloud-native, containerized, and distributed technologies.

Lead platform automation for enterprise Generative AI and data platforms: design and build IaC, CI/CD, observability, deployment automation, and self-service capabilities to accelerate AI/ML lifecycle, reliability, governance, and developer productivity across cloud-native distributed environments.

Lead end-to-end design, build, deployment and iteration of AI-agent solutions. Embed with clients to map workflows, architect multi-agent systems, integrate enterprise systems and RAG pipelines, implement guardrails and observability, and liaise with non-technical stakeholders to drive adoption.

Build and maintain lab environments and CI/CD pipelines for the Skylar AI platform. Create automated end-to-end tests, simulate user journeys and telemetry, validate integrations and performance, manage versioning and rollback tests, support data generation, and document environments. Partner with product, data science, QA, and engineering to ensure reliable monthly updates and platform availability.

Design, build, test, and ship production AI-enabled software and reusable components for enterprise workflows. Implement context-aware agentic systems, integrate models and APIs, write unit tests, debug production issues, lead code reviews, mentor engineers, participate in on-call rotation, and collaborate with U.S. business partners while working remotely from India.

Design, build and deploy AI workflows using Azure AI, Copilot Studio and Microsoft Fabric; integrate solutions with SAP and Salesforce; own end-to-end delivery, DevOps/MLOps/AIOps practices, governance, monitoring, and stakeholder adoption; provide technical leadership and reusable patterns to scale AI adoption across the business.

Design and implement end-to-end AI platform features integrating agent frameworks, vector search/RAG, and relational database capabilities. Build multi-cloud deployable services, enforce multi-tenant data governance, optimize performance, and own APIs, monitoring, and security.

Senior AI Architect responsible for designing production GenAI/ML systems, RAG/LLM architectures, vector DBs and evaluation, agentic and conversational AI (ASR), Arabic NLP quality, enterprise integrations (Oracle Fusion/Dynamics, API-first), cloud/MLOps (containers, GPU inference, CI/CD, observability, DR), security and Saudi compliance (NCA ECC, PDPL), and authoring technical proposals for government tenders.

Design, develop, and deploy ML models and LLM-based applications; implement RAG and vector database pipelines; fine-tune models, optimize inference and scalability; build REST APIs and backend integrations; monitor AI system performance; collaborate cross-functionally and stay current with AI advancements.

Design reproducible coding environments and high-quality reference solutions to train AI. Create and validate complex programming challenges, debug and optimize codebases, refactor legacy systems, document technical decisions, and review technical submissions while collaborating remotely.

Research, design, and train large-scale transformer and hybrid foundation models. Diagnose training instabilities, optimize scaling tradeoffs, define next-gen architectures, develop loss and alignment strategies (RLHF/DPO/GRPO), and lead distributed training (FSDP, ZeRO-3, tensor/pipeline parallelism) with mixed precision and gradient checkpointing while partnering with ML systems teams.

Lead AI-enabled customer support initiatives across a SaaS product portfolio. Identify and implement AI triage, automation, deflection and self-service improvements. Own and optimize Zendesk AI capabilities, collaborate with support, product and operations, define success metrics, and communicate outcomes to stakeholders.

Lead product strategy, roadmap, and market launch for agentic AI solutions. Collaborate cross-functionally to define requirements, validate features, integrate with ServiceNow, drive POCs and production rollouts, and measure ROI and IP/services revenue.

Lead architecture and development of customer-facing AI agents and multi-agent "Super Agents," design agent orchestration and automated workflow frameworks, drive LLM integration and prompt engineering best practices, provide technical leadership across cloud-native backend systems, and mentor senior engineers to productionize AI-driven solutions at scale.

Lead design, development, testing, and App Store submission of production-scale iOS features in Swift. Collaborate cross-functionally, enforce code quality via reviews and refactoring, maintain technical documentation, and adopt AI-assisted tooling to improve productivity across large, user-facing modules.

The role involves developing enterprise applications using Java and Spring, integrating AI features, mentoring junior developers, and collaborating with cross-functional teams.

Independent full-cycle recruiter managing sourcing, client engagement, offer negotiation, and placements using AI-driven tools. Acts as commercial advisor, provides market insights, and maintains self-directed billing and activity in a results-only, remote environment.

The role involves evaluating AI outputs, reviewing text, analyzing multimedia, and providing culturally relevant content in Kannada while ensuring quality and accuracy.

The role involves reviewing and evaluating AI-generated content, providing feedback based on cultural appropriateness and clarity, and ensuring high-quality deliverables for AI projects.

As an AI Expert, you will review and evaluate AI-generated outputs, correct text, analyze multimedia content, and ensure cultural appropriateness and accuracy in the outputs.

The role involves evaluating AI outputs, creating culturally relevant content, spotting issues, and providing structured feedback to improve AI models.

The role involves evaluating AI-generated content, reviewing text, creating annotations, and ensuring quality by applying cultural insights. Candidates must be detail-oriented and fluent in Assamese and English.