Top Artificial Intelligence Jobs in Mumbai

Develop, optimize, and deploy computer vision algorithms (detection, recognition, tracking) across GPUs, TPUs, FPGAs, and edge devices. Integrate and tune hardware, accelerate models with TensorRT/OpenVINO/ONNX, collaborate with cross-functional teams, and maintain production AI systems for performance, reliability, and efficiency.

Design and architect production-grade ML and GenAI solutions on Databricks, including RAG and agentic systems, MLOps pipelines, training/inference optimization, model monitoring, and customer-facing technical enablement and mentorship.

The Senior Software Engineer will lead the design and development of AI-driven solutions, mentor junior engineers, and optimize AI/ML models for various applications.

The AI Research Freelancer will design machine learning algorithms, collaborate on research projects, and develop models for educational assessments.

Lead architecture and build of an in-house agentic AI stack to replace third-party SaaS for claims adjudication, FWA detection, and provider network automation. Design backend pipelines for NHCX/FHIR, develop scalable distributed systems, deploy Vertex AI/Gemini models and agentic workflows, and deliver real-time risk scoring and provider trust signals while working onsite in Mumbai.

Lead design and delivery of a GCP-native, agentic AI insurance core replacing SaaS systems across product, pricing, quoting, underwriting, and policy accounting. Build multi-agent pipelines, RAG/LLM solutions, and secure, auditable architectures handling PHI/SPDI while integrating national healthcare exchanges.

Lead CRM strategy and MarTech solutioning for enterprise clients: win and run large RFPs, design customer lifecycle, segmentation, personalization and journey orchestration, select and integrate CEP/CDP/CRM/data platforms, present to executives, and mentor cross-functional teams in a consulting or agency environment.

Lead CRM strategy and MarTech solutioning for enterprise clients: design customer lifecycle, segmentation, personalization, and cross-channel journey orchestration; architect integrations across CEPs, CDPs, CRM systems and data warehouses; win large RFPs; present to executives; and mentor cross-functional teams.

Lead development and implementation of the EisnerAI Platform; design scalable AI/agent solutions, ensure data governance and responsible AI, mentor developers, perform model evaluation and post-training optimization, and coordinate cross-functional delivery.

As a Vice President Data Analyst at Citi, you will lead a team in developing advanced data analytics solutions, integrating AI/ML strategies for risk management, while ensuring data governance and delivering impactful presentations to stakeholders.

Design and build AI-powered SOC automation: develop LLM/RAG solutions, NLP/ML models for log parsing and alert triage, integrate AI with SIEM/SOAR and ticketing, maintain CI/CD and MLOps, and collaborate with SOC and engineering teams.

An App Engineer will build AI-powered automations and workflows, improve productivity, integrate systems, and collaborate globally to deliver solutions.

Develop autonomous AI systems with a focus on multi-agent pipelines and real-time AI applications, improving model performance and building APIs.

Manage and design integration processes using Boomi and Workato, supporting and developing solutions for complex business issues. Mentor team members and ensure effective communication with stakeholders.

The Deployment Strategist role focuses on deploying AI agents in the consumer finance industry, managing customer projects from contract to go-live, ensuring operational excellence and continuous system improvement.

Seeking a Product Owner with experience in Java, Python, Springboot, AWS, and Artificial Intelligence to manage product development.

Evaluate Chinese multi-turn AI conversations for relevance, grounding, helpfulness, and personalization. Create scenarios, compare and rank responses, identify errors, and provide structured feedback following guidelines. Maintain data quality and use a personal Google account for evaluations.

Design and build production AI backend services, APIs, and data pipelines integrating LLMs and multimodal models; implement retrieval, context assembly, and grounded outputs; create evaluation and regression-testing frameworks; develop internal review tools and React operational UIs; ensure observability, monitoring, and scalable, cost-effective deployments. Own features end-to-end and collaborate with product and engineering stakeholders.

Advance detection and measurement in AI systems: expand jailbreak/adversarial libraries; build bias, fairness, and hallucination evaluation methodologies; develop interpretability techniques; translate research into engineering specs and methodology docs; publish work and represent the company with customers, regulators, and at conferences.

The AI Engineer will integrate advanced language models into software solutions, develop applications using .NET, and enhance user interactions with JavaScript and XML.

Build and maintain LLM-powered applications and MCP servers, implement tool/function calling and prompt pipelines, rapidly prototype new AI tools, track AI tool releases, and deliver weekly intelligence reports with demos and recommended integrations.

The role involves software development in Python, focusing on Gen AI projects, collaborating with technical teams to develop and enhance products.

The AI Engineer will develop and deploy AI/ML models and solutions, collaborate with teams, and ensure production readiness while addressing complex business problems.

Lead creation of integrated digital, social, e-commerce, and motion assets using GenAI and Adobe Creative Cloud. Work from brief to delivery, ideating with GenAI tools, animating and optimizing assets for multi-channel rollouts, ensuring brand consistency, quality, and timely delivery while contributing to AI knowledge-sharing and continuous upskilling.

The Software Development Engineer in Test (SDET) designs and maintains automation frameworks using Microsoft Playwright, integrates AI tools for test generation, and performs API testing while collaborating with a global team.