Top Artificial Intelligence Jobs in Mumbai

Lead product strategy for HighLevel Knowledge Bases and Ask AI, defining architecture, ingestion, retrieval, evaluation, permissions, observability, and commercial models. Drive cross-team platform standards, onboarding, testing datasets, and integrations so AI assistants reliably retrieve context, invoke tools/agents, execute actions, and surface auditable, safe results for multi-tenant SMB customers.

Design, develop, fine-tune, and productionize ML and Generative AI/LLM solutions. Build end-to-end ML pipelines (data ingestion, modeling, deployment, monitoring), implement RAG and vector DB architectures, apply prompt/context engineering and MLOps best practices, and collaborate with cross-functional teams to optimize models for performance, latency, scalability, and cost.

Early-career full stack engineer role to build end-to-end product features, integrate AI coding tools into the workflow, mentor peers, improve cross-team efficiency, and contribute across the product lifecycle from design through deployment.

Build and maintain full-stack web applications using React/Vue frontends and Java/Spring Cloud microservices. Design and consume REST/AI model APIs, work with SQL and NoSQL databases, use AI-assisted development tools, own features end-to-end, collaborate across product and design, ensure high-quality UI/UX, write tests, and contribute to documentation and architecture.

Join as an early-career full stack engineer to build frontend and backend product features, integrate AI coding tools into development workflows, translate product requirements into implementations, and grow toward autonomous full stack delivery while improving cross-team processes.

Support development of internal LLM-based tools (coding assistants, RAG pipelines, prompt optimization), improve engineering efficiency, test and document AI tools, and research emerging AI technologies.

Build AI-driven developer tools: coding assistants, knowledge retrieval, workflow automation, and LLM-powered apps for code generation, understanding, and test automation. Collaborate with engineering teams to identify pain points, ship solutions, and experiment with prompt engineering, RAG, and AI agents.

Early-career role building AI-powered developer tools and internal LLM applications. Tasks include coding assistants, lightweight RAG pipelines, prompt optimization, testing, documentation, and researching emerging AI technologies to improve engineering productivity.

Early-career research role designing and running experiments on LLM reasoning, post-training alignment, and test-time scaling. Implement model variants and training pipelines in PyTorch/Hugging Face, evaluate on crypto-native data, maintain experiment tracking (W&B), and partner with engineering to translate research to production.

Build and operate distributed backend services and genomic reasoning engines that combine whole genome bioinformatics with AI. Design scalable data models, retrieval and vector search systems, and deterministic guardrails to ensure scientifically accurate, explainable genomic AI for production use.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

Own the blog, site content, and backlink strategy to grow organic traffic. Plan, write, and publish SEO-driven content for college and Greek-life audiences; optimize on-page elements; build and pitch backlink assets; track rankings, backlinks, and content performance; and develop strategies for visibility in AI-generated search answers.

The Content Writer/Ai Editor will create high-quality content while leveraging AI tools for optimization, managing multiple projects, and adhering to brand guidelines.

The AI Platform Engineer will design and optimize AI/ML infrastructure, automate pipelines, and manage Kubernetes for effective machine learning model deployment and collaboration.

Lead AI solutions development focusing on Voice AI, Computer Vision, and Conversational AI, enhancing customer support and monitoring platforms.

Develop AI solutions in Voice AI, Computer Vision, and Conversational AI. Architect and build AI systems for monitoring, analytics, and customer support across EV infrastructure.

Design and implement AI-enabled ServiceNow solutions across ITSM, FSM, and ITAM. Provide technical leadership and ensure best practices in AI capabilities, facilitate stakeholder workshops, and guide project teams.

The role involves developing full-stack web apps, creating APIs, improving lead capture models, and collaborating across teams to enhance the Social Planner product.

Design, build, and scale production-grade agentic AI systems and LLM applications (RAG, multi-agent orchestration, tool-augmented reasoning). Lead platform and API development, cloud deployment across GCP/Azure/AWS, observability, incident response, and mentor junior engineers while shaping AI architecture and standards.

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.

Define and deliver AI agents for enterprise spend management. Own vision, architecture, and roadmap; design agent patterns, observability, and closed-loop training; partner with engineering, data science, UX, and go-to-market teams; engage Fortune 100 stakeholders to ship reliable, explainable agentic workflows for invoicing, vendor onboarding, contracts, dispute resolution, and cross-border payments.

Design, build, and deliver enterprise-grade Generative AI and AI/ML platform capabilities: reusable services, APIs, microservices, RAG and agentic solutions, model lifecycle tooling, inference and monitoring, event-driven streaming with Kafka, CI/CD and DevOps automation, and platform observability to accelerate AI adoption across business domains.

Lead and execute AI-driven consumer product initiatives for search, recommendations, personalization, and conversational experiences. Collaborate with engineering, design, data, and business teams to define requirements, use data and user feedback to refine products, and deliver improvements within the contract period.

The Senior Engineer will develop and deploy machine learning models and workflows, mentor junior engineers, and collaborate with cross-functional teams to improve patient care through innovative solutions.

Lead the intelligent transformation of operations support functions through AI and data solutions, overseeing hands-on technical delivery and team leadership in AIOps initiatives.