Top Artificial Intelligence Jobs in Chennai

The Forward Deployed Senior Software Engineer will lead initiatives in building custom solutions and algorithms for healthcare data, collaborating with various teams to enhance customer experience and project delivery.

Lead enterprise AI strategy and roadmap; build and scale cross-functional AI/ML teams; architect and deliver LLM, RAG, predictive and data-heavy AI products; establish MLOps, governance, cloud-native platforms (Azure/Databricks/AWS/GCP); drive product lifecycle, KPI tracking, security, and responsible AI practices.

Implement and customize ServiceNow ITSM and Service Portal solutions, perform integrations (REST, SOAP, MID Server), maintain Discovery and CMDB, develop and optimize server/client scripts (Business Rules, Script Includes, UI Policies), run workshops/demos, translate client requirements into user stories, mentor junior developers, and participate in Agile delivery cycles.

Lead design, customize, and implement ServiceNow ITSM, Service Portal, and ITOM solutions. Perform integrations (REST, SOAP, MID Server), Discovery and CMDB maintenance, and develop/optimize scripts. Run workshops, mentor junior developers, and participate in Agile delivery to translate client requirements into scalable ServiceNow solutions.

Design, scale, and maintain Salesforce Flow and orchestration workflows to automate seller, recruiter, and ops tasks. Implement Agentforce and AI-driven next-best-action processes, build repeatable automation frameworks across service lines, identify data quality gaps, create SLA triggers/escalations, run experiments, and maintain documentation and governance.

Develop, fine-tune, deploy, and optimize AI/ML models and LLM-based RAG systems using Python, AWS Bedrock, and major ML frameworks. Build scalable REST APIs and microservices with FastAPI or Flask, deploy containerized solutions on AWS, and manage CI/CD. Design databases and automated ETL pipelines, integrate cloud services, and document AI workflows while collaborating with cross-functional technical and product teams.

Implement, configure, and support Oracle Fusion Procurement modules and related SCM processes. Gather requirements, design solutions, configure workflows and procurement controls, support AI-driven automation, manage integrations and data migration, conduct testing and UAT, resolve defects, prepare documentation, train users, and provide production support. Collaborate with Finance, Accounts Payable, Inventory, Supplier Portal, and other stakeholders while assessing quarterly Oracle releases.

Design and manage AI architectures using AWS, develop cloud-native solutions, mentor teams, ensure compliance, and evaluate emerging technologies.

Build AI-assisted workflows and tool-using agents for semiconductor engineering automation: connect agents to platform APIs and data, create knowledge-ingestion pipelines, design evaluation datasets and tests, develop reusable workflow templates, and integrate agents with real tools producing traceable results.

Design and implement optimization and planning algorithms for engineering automation. Build constraint-handling logic, benchmarking and visualization tools, define metrics, run applied ML experiments for ranking and learned cost functions, and collaborate with platform, AI, and domain engineers to productionize algorithmic solutions.

Lead strategy and development of AI/ML engineering solutions, enhancing decision-making and automation across the enterprise. Oversee advanced analytics and mentoring of data science teams.

As an AI Intern at Valeo, you'll support innovative projects aimed at developing environmentally friendly mobility solutions while working in a diverse, global team.

Lead implementation of AI and automation across legal functions: deploy contract intelligence, fraud detection, and KYC automation; digitize manual legal workflows and inbox triage; build self-service document tools; maintain the legal tech stack and KPIs; train legal teams to drive adoption. First-six-month goals include KYC digitization, AI-driven inbox triage, and a contract analysis tool that reduces review time by 30%+.

Lead design and delivery of AI-driven applications and analytics for engineering and manufacturing. Research AI technologies, build PLM-based automation, collaborate with global teams, deploy IT infrastructure, and maintain academic partnerships to accelerate digital transformation.

Integrate and deploy AI-driven HVAC control solutions by mapping client data to internal standards, testing and deploying algorithms, supporting project handoffs, documenting building HVAC systems and control points, updating configurations, and coordinating cross-functional teams to ensure timely, standardized digitalization and post-deployment support.

Lead full ML lifecycle to design, build, and deploy AI/ML (including Agentic and LLM) solutions for enterprise-scale reconciliation. Analyze large financial datasets, define model roadmaps, integrate models into production, ensure scalability, manage risks, and communicate results to senior stakeholders.

Create and optimize AI prompts for cinematic image and video generation in a theatrical feature film. Translate directors’ vision into high-quality visuals using cinematography, framing, lighting, and storytelling principles. Collaborate with directors, editors, and creative teams to maintain visual consistency, continuity, and coherence across scenes. Experiment with AI generation tools, troubleshoot outputs, and refine results to meet professional film-quality standards.

Lead design and implementation of agentic AI enablement systems: build end-to-end agentic workflows (orchestration, guardrails, evaluation), maintain retrieval/search infrastructure (indexing, ranking, relevance), integrate MCP/APIs, and create human-in-the-loop editorial and enablement tooling with cross-functional stakeholders.

Lead design, build, and scale production-grade Generative AI applications using LLMs, RAG, LangChain, vector databases, and agentic systems. Own AI orchestration, containerized Kubernetes deployments, CI/CD, data ingestion from enterprise sources, monitoring for high uptime, and governance/compliance to deliver measurable business impact and reusable AI accelerators.

Own product areas in BJAK's AI Neobank app (insurance, payments, savings, investing, travel). Define problems, scope, success metrics and roadmaps; collaborate with engineering, design, data, ops, compliance and business teams; launch features, monitor performance, run experiments and iterate to improve user experience and business impact.

Lead product direction and roadmaps for major areas of BJAK's AI neobank app. Own prioritization, execution, launch quality, and metrics across multiple squads. Guide PMs, designers, and engineers, turning regulatory and operational constraints into practical product decisions across payments, savings, investing, insurance and travel.

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.