Top Artificial Intelligence Jobs in Mumbai

Support engineering teams in adopting AI code assistants and IDE tooling, troubleshoot and optimize development environments, maintain DevOps/DevSecOps pipelines and MCP integrations, implement agentic AI workflows, provide end-user support and documentation, and collaborate to improve onboarding and developer productivity.

The role involves creating SEO, CRO, and GEO-optimized content for the Australian market, leveraging AI tools and ensuring high editorial quality for improved organic traffic and conversions.

Lead an AI-first transformation of procurement operations: assess Source-to-Pay maturity, design automation and LLM data governance, select and deploy S2P and CLM technologies, implement RPA/ML solutions, enable high-fidelity spend categorization and supplier compliance automation, and drive stakeholder integration and change management with IT and executive leadership.

Lead multi-disciplinary teams in driving strategic change for Kyndryl's clients. Build relationships with CXO-level executives, ensuring profitable growth through effective client engagement and operational excellence. Foster talent development and innovation, contributing to strategic initiatives and enhancing client satisfaction.

Responsible for executing supplier strategy, managing full sales cycle, and enhancing customer satisfaction through relationship building and operational excellence.

Design and deliver enterprise AI solutions on SAP BTP: build/deploy ML models (AI Core/Launchpad), integrate Joule across SAP products, prototype AI use cases, create intelligent workflows with SAP Build Process Automation, define AI architecture, MLOps pipelines, and multi-cloud integration patterns aligned with Clean Core.

Build and productionize LLM-powered agents, workflows, and RAG systems. Apply prompt engineering, embeddings, fine-tuning, and traditional ML to automate tasks and improve products. Mentor teammates and help design scalable, production-grade AI infrastructure while staying current on LLM advances.

Join a remote team as a Lead Data Scientist focusing on building Generative AI applications. Responsibilities include developing applications, implementing pipelines, and performing model tuning.

As a Senior Full Stack Developer, you will design and build end-to-end features across backend and frontend using .NET and React, collaborate on system architecture, and integrate AI capabilities.

The AI Platform Engineer leads the development of production AI agents and components, collaborates on AI implementations, and maintains AI systems for reliability and observability.

The AI Engineer will maintain and enhance AI services on the Sootra platform, optimizing pipelines, managing microservices, and developing feedback systems to improve AI performance.

The Senior Product Manager will lead AI product strategy at CoinMarketCap, focusing on user needs and data analysis to drive product development.

The Senior AI Engineer designs and implements AI solutions, develops LLM applications, builds production ML pipelines, and engages directly with customers for high-impact AI projects.

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.

Build and ship AI-powered features for fashion, beauty, and home using large-scale product, image, and consumer data. Prototype with LLMs, agents, multimodal and CV models, run experiments, measure impact, and take models end-to-end from hypothesis to production while collaborating with product, design, and business teams.

Design and implement the core AI layer for enterprise compliance workflows: document extraction, retrieval, RAG, agentic task execution, evaluation pipelines, and human-reviewable AI features to improve accuracy, traceability, and workflow automation.

Design and build the core intelligence layer for enterprise AI workflows: document extraction, retrieval, ranking, generation, evaluation pipelines, agentic task execution, and integration into a polished product while prioritizing accuracy, traceability, and human-in-the-loop review.

Design and execute cloud data migration workflows across AWS/GCP/Azure, build and maintain ETL/ELT pipelines, integrate and evaluate LLM/generative AI components, perform system testing and validation, ensure data integrity and performance, document findings, and collaborate with cross-functional teams.

Independently extract data from CSV and PDF sources, transform and map into strict JSON schemas, build material- and supplier-level records, and validate every record with zero data loss. Use AI tools to assist but manually verify all outputs and follow SOPs and QA checklists.

Annotate and label data to train and improve LLM-based AI models using RAG and other AI tools. Ensure data quality and consistency, collaborate with AI engineers, and stay current with AI tools. Work remotely as a contractor for a minimum of 20 hours/week.

The ServiceNow Solution Architect - AI role involves leading and mentoring a team, designing and deploying AI-driven applications, managing application development, and integrating solutions into ServiceNow modules. Responsibilities include coordinating with stakeholders, troubleshooting, and ensuring adherence to technical standards.

Build and maintain Python/FastAPI backend services and React frontends, design and consume REST APIs, work with relational databases, and implement/debug AI-enabled features including vector DBs, embeddings, semantic search, and RAG workflows. Improve existing codebases, collaborate with product and design, participate in testing, deployment, and monitoring, and ensure performance, security, and maintainability.

Design, develop, and deploy advanced AI/ML models (including LLMs and agentic systems) to improve search, forecasting, text mining, anomaly detection and root-cause analysis. Optimize models and ML pipelines for performance, scalability, and resource efficiency; work with big-data frameworks and vector/search systems.

Evaluate AI-generated coding interactions, assess quality of engineering judgments, provide feedback, and define standards for AI coding agents. Comfortable making subjective judgments about engineering quality.

Senior hands-on Technical Architect to design scalable Java/Spring Boot backend systems, integrate AI/LLM pipelines, lead production incident response, implement observability and CI/CD, and coordinate full-stack integrations across React and mobile platforms.