Top Artificial Intelligence Jobs in Mumbai

Serve as a field-facing technical authority bridging generative AI and enterprise security. Architect AI technical strategy, deliver demos and POVs, advise on LLM/RAG/agent risks and data protection, and scale enablement and product feedback across sales and engineering.

Design and implement generative AI and ML solutions for fixed income investing, including RAG/LLM workflows, embeddings, model training/fine-tuning, feature engineering, statistical evaluation, production deployment, and stakeholder collaboration while ensuring responsible AI practices and data governance.

Design and build scalable systems, data pipelines, and full‑stack applications to validate product quality and produce KPI reporting. Integrate AI-driven features (RAG, agents, semantic search), automate statistical analysis, support CI/CD, conduct code reviews, and collaborate in Agile teams to translate business needs into technical solutions.

Partner with investors to design, build, and productionize AI-powered research applications (LLM workflows, RAG, vector search, fine-tuning). Own architecture, data pipelines, backend integration, UX, monitoring, and AI safety/reliability practices from POC to production.

Lead design, development, and deployment of production ML systems for HD mapping, ADAS and IVI. Own end-to-end ML architecture, data ingestion, training, inference pipelines, MLOps (CI/CD, versioning, monitoring), and integrate outputs into map compilation. Drive models in computer vision, NLP, generative/agentic AI, and ensure scalable, reliable in-cloud or in-vehicle deployments while mentoring teams and enforcing engineering best practices.

Lead design and deliver efficient perception models for road scenes, optimize models for edge devices (Jetson, Snapdragon, ARM), improve real-time inference via quantization/pruning/distillation, convert/deploy with TensorRT/ONNX, build scalable training/evaluation with PyTorch or TensorFlow, and collaborate with embedded and software teams to produce production-ready edge AI systems.

Lead end-to-end product development for digital lending: design lending journeys, digitize servicing workflows, collaborate with engineering/ops/compliance, analyze funnel and platform metrics, and iterate post-launch to improve acquisition, conversion, retention, and operational efficiency.

Build end-to-end full-stack AI features on a Ruby on Rails backend and React frontend, design and run experiments (A/B tests and AI evaluations), implement AI infrastructure for reliable LLM inference, and iterate quickly to scale production-ready LLM-powered products.

Design and implement Generative AI solutions to improve operational efficiency. Collaborate with teams to identify opportunities and ensure data governance.

Build, operate, and improve end-to-end Agentic AI/ML pipelines and a map compilation platform for HD maps. Implement scalable CI/CD/CT for ML, design fault-tolerant orchestration, deploy containerized models in cloud-native environments, monitor model performance and data drift, manage model lifecycle/versioning, drive IaC and cloud reliability, and collaborate on architecture and incident resolution.

Manage end-to-end technology procurement for strategic vendors: own renewals pipeline, lead RFI/RFP and negotiations, draft contracts with legal, align stakeholders, qualify suppliers, resolve post-signature delivery or commercial issues, and provide market intelligence for strategic sourcing decisions.

Lead the development of AI-powered customer support solutions, guiding a team to build scalable, reliable, and secure systems using LLMs and third-party integrations.

The Tech Project Manager will define and execute the vision for generative AI products, manage cross-functional teams, and oversee project lifecycles to enhance competitiveness and user experience.

The Account Executive drives growth by managing key accounts, identifying new business opportunities, and deepening customer relationships to enhance market share.

Maintain and improve on-premises MLOps infrastructure: deploy, monitor, and optimize ML models; troubleshoot Linux/Docker/Kubernetes stacks; build CI/CD, deployment, and monitoring tools; productionize research artifacts; enforce testing and engineering standards; collaborate with data scientists and software engineers to scale ML systems.

Manage and grow an India-based AI Development team to deliver enterprise agent applications. Translate product priorities into sprints, partner with the Director of AI on roadmap and technical execution, establish async-first delivery rhythms across US/India, handle India operations (hiring, performance, compensation), coach on modern programming practices, and unblock work through cross-team relationships.

The Senior Data Scientist will architect real-time fraud detection systems, process large data sets, mentor teams, communicate findings, and innovate using AI technologies for effective risk management.

Support and enhance ADI's global compliance program aligned to enterprise risk and ISO 37301. Monitor regulatory developments, update policies, execute risk‑based monitoring and testing, manage investigations and remediation, support audits, develop training and communications, track metrics, and collaborate with Legal, HR, Finance, IT, and Operations to drive continuous improvement.

Lead and support execution of ADI's global compliance programs: risk‑based monitoring, policy management, testing, investigations, training, ISO 37301 alignment, audits, remediation, and cross‑functional stakeholder coordination.

The Senior Software Engineer will develop and maintain AI agents and applications, modernize platforms, and enhance product experiences using various AI tools, while following Agile methodologies.

Evaluate and author high-quality computer science content to improve AI model reasoning and accuracy. Analyze complex CS problems, create scenarios/datasets, review AI outputs for correctness, and collaborate remotely to refine guidelines and documentation.

Lead and deliver multiple complex APAC equities projects from conception through implementation. Scope and document requirements, coordinate stakeholders across business and control functions, manage risks/issues, produce executive communications, oversee testing and post-implementation activities, and drive business optimization and regulatory control initiatives.

The Lead AI Engineer designs and delivers AI/ML and Generative AI solutions for banking platforms, integrating data and enabling AI-driven decisions.

Support the Business Supervisory Office by performing trade surveillance, transaction monitoring, AML review, and regulatory compliance oversight for US Private Banking. Analyze trade alerts, review customer transactions for money laundering indicators, prepare surveillance reporting, assist with regulatory audits, maintain procedures, and coordinate remediation and control improvements with onshore stakeholders.

As a Staff Backend Engineer, you'll design backend architecture for AI governance, ensuring auditability and compliance, while collaborating with engineering teams to enhance product capabilities.