Top Artificial Intelligence Jobs in Mumbai

Build and maintain real-time data pipelines and front-end dashboards; train, deploy, and monitor ML models for trend detection and release success scoring; implement data tokenisation/anonymisation for cross-border compliance; automate briefing intake and ad deployment workflows using LLMs and Gen AI; collaborate with paid media and creative teams to operationalise AI-driven marketing solutions.

Deploy, monitor, and optimize enterprise AI models on Azure. Implement MLOps pipelines (CI/CD) with Azure ML and GitHub Actions, ensure governance, telemetry, drift detection, cost/performance tuning, versioned rollouts, and compliant change management across client-facing applications.

Build the AI layer for SigNoz: implement agent orchestration, long-running execution, streaming APIs (SSE), and MCP server integrations to expose observability data to LLM agents. Ship production LLM features, design scalable distributed backends in Go and async Python, and drive projects end-to-end in a remote-first environment.

Design, develop, and deploy generative AI agents and end-to-end ML pipelines. Lead prompt engineering, LLM integration, model training, and productionization, collaborating with customers and stakeholders to deliver AI solutions.

This job is for candidates with AI infrastructure experience to submit their resumes for future opportunities. No specific role is posted.

As a Senior Agentic AI Lead, you will manage the agentic AI domain, engage with customers, oversee the AI lifecycle, and ensure effective data governance and analytics across various teams.

Own strategy, roadmap, and execution for HighLevel VoiceAI. Deliver reliable inbound/outbound AI voice agents integrated with telephony, CRM, workflows, and analytics. Improve agent setup, call quality, compliance, APIs/webhooks, monetization, and developer extensibility. Partner with engineering, design, support, and GTM to drive adoption, instrumentation, and measurable business outcomes for SMBs and agencies.

Build and scale a full-stack Next.js application tracking PRs, CI health, test parity, and benchmarks across AI accelerator open-source projects. Integrate GitHub APIs and webhooks, design PR/metrics schemas, visualize results, and produce technical digests and reports on cross-accelerator parity and performance trends.

Create platform-optimized short- and long-form educational and marketing videos using AI-powered editing tools. Build scalable AI-assisted post-production workflows, optimise content for social platforms, transform complex topics into engaging learning experiences, and research/implement emerging AI video technologies.

Design and deploy AI/ML solutions on Snowflake, build ML pipelines and POCs using SQL/Python/APIs, advise customers and systems integrators, enable teams via best practices, collaborate with Product/Engineering, and travel to customer sites (~25%).

Embed with customers to scope, prototype, and deploy production-grade agentic and generative AI solutions. Own client relationships, technical direction, delivery, optimization, observability, and mentoring of FDE squads while contributing platform feedback and rapid prototypes to drive measurable business outcomes.

The Vendor Program Manager develops vendor marketing plans, manages product categories, coaches staff, and reports on marketing performance while ensuring profitability and alignment with vendor objectives.

The Lead Solution Architect will oversee Data, AI, and Analytics solutions across APJ, driving technical strategies, engaging stakeholders, delivering demos, and collaborating with partners.

The Presales Consultant supports the Sales Team by providing technical presales support, conducting product demonstrations, and assisting with customer qualifications and RFP responses. They also manage Proof of Concept activities and deliver training to partners.

Build production-grade agentic AI systems that reason, search, and execute workflows. Develop RAG pipelines, AI agents, semantic search layers, data processing solutions, dimensional data models, and scalable AI workloads. Work with structured and unstructured data, LLMs, vector databases, cloud infrastructure, CI/CD, and ML observability. Responsibilities include fine-tuning models, prompt engineering, optimizing context windows, and deploying reliable AI applications.

Develop and deploy AI/ML models using Python. Focus on model development, production deployment, and collaborating with cross-functional teams. Communicate findings, solve technical problems, and work in a fast-paced environment. React and TypeScript experience and AI security/risk familiarity are nice-to-haves.

Lead enterprise AI strategy and productization for research transformation: scope, develop, test, and scale AI tools/agents, advise clients, vet third-party tools, create documentation and upskilling materials, and present outcomes to senior leadership.

Lead full-stack development using Python and FastAPI; build high-performance APIs integrated with AWS (SQS, Lambda). Implement front-end using React/Angular, manage Mongo/MySQL/Oracle databases, integrate AI features via prompt engineering and GitHub Copilot/Cursor, optimize performance, apply DevOps/CI-CD, troubleshoot and collaborate in Agile/Scrum with Jira and Git.

Design and lead GenAI and agent-based AI solutions for large-scale modernization programs. Define prompt engineering, orchestration, validation, guardrails, and human-in-the-loop workflows. Apply AI to legacy systems (COBOL, HP NonStop, C++) for code comprehension, dependency mapping, documentation, and test generation. Collaborate with solution and platform architects, work in Agile sprint-based delivery, and guide distributed offshore/onshore teams.

Design, build, and deploy production-grade AI automation and agentic workflows for payments processes (reconciliations, audit and reporting). Integrate AI systems into operational pipelines to automate high-effort financial operations while preserving control, audibility, and reliability.

Serve as the technical pre-sales architect for regional AI PODs: design end-to-end AI architectures (GPU clusters, networking, storage, MLOps, inference), validate solutions with NVIDIA and cloud partners, lead technical discovery and proofs-of-concept through the ATC, and ensure clean handoff to delivery while driving deal momentum.

Evaluate AI-generated technical content, craft and answer advanced ML/AI prompts, assess model responses for accuracy, relevance, and clarity, identify errors or hallucinations, and provide feedback to improve AI systems.

Develop and optimize small language models using Hugging Face, TRL, LoRA, QLoRA, and PEFT. Build MLOps pipelines, optimize models through quantization and distillation, deploy them to edge and mobile environments, and monitor production performance. Evaluate model quality with benchmarking frameworks and custom evaluation suites while meeting strict latency and hardware utilization targets.

Design and evangelize agentic AI solutions by mapping customer journeys, identifying automation opportunities, architecting LLM-driven workflows and integrations, leading POCs to production, articulating ROI, engaging stakeholders, and building repeatable playbooks to enable enterprise sales.

Design, implement, test, and deploy software components for AI-powered solutions. Build and maintain CI/CD pipelines, write unit tests, integrate cloud and distributed systems, work with data engineering tools (Pandas/Spark), and collaborate with stakeholders to estimate and deliver features.