Top Artificial Intelligence Jobs in Mumbai

Design, build, test, and ship production AI-enabled software and reusable components for enterprise workflows. Implement context-aware agentic systems, integrate models and APIs, write unit tests, debug production issues, lead code reviews, mentor engineers, participate in on-call rotation, and collaborate with U.S. business partners while working remotely from India.

Design, build and deploy AI workflows using Azure AI, Copilot Studio and Microsoft Fabric; integrate solutions with SAP and Salesforce; own end-to-end delivery, DevOps/MLOps/AIOps practices, governance, monitoring, and stakeholder adoption; provide technical leadership and reusable patterns to scale AI adoption across the business.

Design and implement end-to-end AI platform features integrating agent frameworks, vector search/RAG, and relational database capabilities. Build multi-cloud deployable services, enforce multi-tenant data governance, optimize performance, and own APIs, monitoring, and security.

Design, develop, and deploy ML models and LLM-based applications; implement RAG and vector database pipelines; fine-tune models, optimize inference and scalability; build REST APIs and backend integrations; monitor AI system performance; collaborate cross-functionally and stay current with AI advancements.

Design reproducible coding environments and high-quality reference solutions to train AI. Create and validate complex programming challenges, debug and optimize codebases, refactor legacy systems, document technical decisions, and review technical submissions while collaborating remotely.

Research, design, and train large-scale transformer and hybrid foundation models. Diagnose training instabilities, optimize scaling tradeoffs, define next-gen architectures, develop loss and alignment strategies (RLHF/DPO/GRPO), and lead distributed training (FSDP, ZeRO-3, tensor/pipeline parallelism) with mixed precision and gradient checkpointing while partnering with ML systems teams.

Lead AI-enabled customer support initiatives across a SaaS product portfolio. Identify and implement AI triage, automation, deflection and self-service improvements. Own and optimize Zendesk AI capabilities, collaborate with support, product and operations, define success metrics, and communicate outcomes to stakeholders.

Lead product strategy, roadmap, and market launch for agentic AI solutions. Collaborate cross-functionally to define requirements, validate features, integrate with ServiceNow, drive POCs and production rollouts, and measure ROI and IP/services revenue.

Lead architecture and development of customer-facing AI agents and multi-agent "Super Agents," design agent orchestration and automated workflow frameworks, drive LLM integration and prompt engineering best practices, provide technical leadership across cloud-native backend systems, and mentor senior engineers to productionize AI-driven solutions at scale.

Lead design, development, testing, and App Store submission of production-scale iOS features in Swift. Collaborate cross-functionally, enforce code quality via reviews and refactoring, maintain technical documentation, and adopt AI-assisted tooling to improve productivity across large, user-facing modules.

The role involves developing enterprise applications using Java and Spring, integrating AI features, mentoring junior developers, and collaborating with cross-functional teams.

Independent full-cycle recruiter managing sourcing, client engagement, offer negotiation, and placements using AI-driven tools. Acts as commercial advisor, provides market insights, and maintains self-directed billing and activity in a results-only, remote environment.

The role involves evaluating AI outputs, reviewing text, analyzing multimedia, and providing culturally relevant content in Kannada while ensuring quality and accuracy.

The role involves reviewing and evaluating AI-generated content, providing feedback based on cultural appropriateness and clarity, and ensuring high-quality deliverables for AI projects.

As an AI Expert, you will review and evaluate AI-generated outputs, correct text, analyze multimedia content, and ensure cultural appropriateness and accuracy in the outputs.

The role involves evaluating AI outputs, creating culturally relevant content, spotting issues, and providing structured feedback to improve AI models.

The role involves evaluating AI-generated content, reviewing text, creating annotations, and ensuring quality by applying cultural insights. Candidates must be detail-oriented and fluent in Assamese and English.

This role involves reviewing AI-generated content, ensuring cultural relevance, generating content, and providing assessments to improve AI models. Attention to detail and analytical skills are crucial.

The AI Video Editor / Motion Designer creates AI-driven videos to enhance advertising effectiveness. Responsibilities include video production, concept development, utilizing AI tools, performance analysis, and collaboration with team members.

Design, deploy, and maintain GPU-accelerated enterprise infrastructure (NVIDIA DGX/HGX, Nutanix). Administer VMware and Kubernetes clusters across distributions, automate tasks with scripting/Ansible, monitor performance, and collaborate with DevOps and data science teams to ensure scalable, highly available AI/ML systems.

The Billing Associate will manage outbound insurance tasks, ensure AI performance, and support insurance setups while collaborating on product development.

Design and ship a 14-domain skills taxonomy and SDK/CLI tooling, operate the MCP server, integrate agent protocols, improve LLM grounding for crypto, run developer hackathons, and produce technical content to grow the ecosystem.

Build and scale AI-driven workflow features: integrate AI into Email/SMS/code actions, implement RAG and knowledge-base solutions, develop data extraction, text-to-voice, and analysis tools, optimize low-latency APIs, and mentor junior engineers.

Design, build, and deploy AI-powered legal applications using LLMs, RAG, and agentic AI. Partner with legal stakeholders to translate workflows, build document ingestion and vector search pipelines, ship production-grade features, implement governance/security controls, and mentor/legal users while aligning solutions with enterprise architecture and monitoring quality and evaluation metrics.

Build and scale production-grade AI/LLM capabilities across backend services: design agentic workflows, implement RAG pipelines, develop secure AI APIs, enforce safety/compliance, enable observability and evaluation, optimize reliability and cost, and contribute to CI/CD, IaC, testing, documentation, and cross-team delivery.