Top Artificial Intelligence Jobs in Mumbai

The Senior Business Analyst will design user experiences for virtual agents, gather customer requirements, create conversation flows, and act as a liaison between stakeholders and development teams in Conversational AI projects.

Design and build agentic GenAI systems (chat copilots, workflow/graph agents) using LLMs and multimodal models. Implement vector stores, hybrid search, re-ranking, chunking, monitoring, evaluation, and CI/CD. Integrate and fine-tune models, apply prompt engineering, configure guardrails/PII redaction, and collaborate with presales/customers to deliver production AI solutions.

Lead design and implementation of full-stack cloud applications that integrate AI capabilities: architect scalable services, deploy ML models, build front-end and back-end components, ensure CI/CD and observability, mentor engineers, and collaborate with data scientists and product stakeholders.

The Architecture Consultant delivers multi-technology consulting services, collaborates on solutions architecture, participates in feasibility studies, and engages with clients on business development.

Lead design and implementation of AI-enabled, agentic software delivery solutions using Claude Code and AI-assisted tools. Build AI agents and automation across planning, development, testing, reviews, integration, deployment and production support. Partner with stakeholders to modernize SDLC to Agentic ADLC, improve developer productivity, troubleshoot production issues, and produce documentation and operational procedures.

Build and operate the firm's internal AI application platform: develop production AI services and APIs, implement RAG pipelines, manage vector DBs and retrieval, integrate model serving, ensure reliability and observability, and support agentic workflows and incident response.

Lead product quality across the SDLC by reducing defects, driving root-cause analysis, defining automation strategy and quality gates, building automated test frameworks (Playwright, API, integration, performance), integrating tests into CI/CD, enforcing release readiness, and using Claude Code and other AI tools to analyze issues and improve engineering outcomes.

Lead and operate enterprise Azure and Microsoft 365 platforms, manage hybrid identity (Entra ID/AD), deliver and govern AI solutions (Azure OpenAI, Azure ML, Copilot), provide L2/3 support, secure and govern cloud resources, manage on‑prem infrastructure, and drive vendor, project, and stakeholder engagement to scale AI initiatives.

Early-career full stack internship developing frontend and backend features under senior guidance. Integrate AI coding tools into workflows, translate product requirements to implementations, contribute across the product lifecycle, and suggest cross-team process improvements while learning full-stack practices.

Design and lead enterprise-scale Agentic and Generative AI architectures, multi-agent systems, and knowledge-driven retrieval solutions. Define governance, observability, LLM selection, and production best practices. Lead PoCs to production, mentor teams, and advise stakeholders on AI strategy and transformation.

Implement and configure AI-enabled ServiceNow solutions, modernize portals and workspaces using Next Experience and UI Builder, build workflows with Flow Designer, implement Now Assist/AI Search/Virtual Agent, develop integrations via Integration Hub and REST APIs, and collaborate with stakeholders to deliver scalable ServiceNow solutions.

Develop and integrate AI/LLM-powered applications, build backend services and REST APIs, work on ML models and prompt engineering, integrate third-party APIs, perform testing, debugging, deployment, documentation, and collaborate on live AI projects.

Design, build, and optimize AI-driven automation workflows using platforms like n8n, Make, and Zapier. Train, fine-tune, and deploy custom LLMs (OpenAI, Hugging Face, etc.), integrate LLM APIs, collaborate with stakeholders, troubleshoot and document solutions, and stay current on generative AI advances. Mandatory technical assessment required.

Design, build, and optimize AI-driven automation workflows using platforms like n8n, Make, and Zapier. Train, fine-tune, and deploy custom LLMs (OpenAI, Hugging Face, TensorFlow) and integrate LLM APIs. Collaborate with stakeholders, troubleshoot and document workflows, and stay current on generative AI and automation technologies.

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.

Investigate escalated production incidents (DB anomalies, failed payments, data migrations), write post-mortems and runbooks, and build AI-powered automation (LLM diagnostics, agents) plus developer tooling. Maintain CI/CD, GCP infrastructure, container deployments, observability, and partner on ERP and payment provider integrations.

Design, build, and deploy AI agents and machine learning models; integrate ML/NLP into full-stack applications; develop APIs and data pipelines; deploy and manage services on AWS; collaborate with frontend/backend teams and maintain CI/CD, databases, and production monitoring.

Develop and optimize AI models for efficient inference on custom silicon. Build fine-tuning pipelines, implement acceleration techniques (quantization, sparsity, distillation), create benchmarking and profiling tools, and collaborate with hardware, compiler, and quantization teams to translate algorithmic improvements into real hardware gains.

Lead enterprise clients to improve AI search visibility through analysis, custom GEO playbooks, C-suite presentations, prompt testing, monthly reporting, and cross-functional product collaboration to drive platform adoption and measurable visibility gains.

Design polished, user-centric mobile and web interfaces for BJAK's AI-driven neobank products. Convert requirements into wireframes, flows, prototypes and high-fidelity UI. Maintain and evolve the design system, ensure accessibility and responsiveness, iterate using research and analytics, and collaborate with PMs and engineers to deliver pixel-perfect implementations across insurance, payments, investments and related financial services.

Build and deploy production-grade generative AI applications: design multi-agent systems and LangGraph workflows, implement advanced RAG with vector DBs, fine-tune and host LLMs, develop scalable FastAPI backends, optimize latency/cost, and containerize services for production.

Lead design and architecture of Generative AI solutions on Azure and OpenAI, build end-to-end data pipelines and cloud infrastructure, produce solution blueprints, collaborate with stakeholders, and implement data preprocessing, API deployment, monitoring, and analytics delivery.

Design, build, and maintain AI platform and ML pipelines by assembling LLMs and agentic workflows, integrating assistants with systems, prototyping in low-code and code, writing tests and CI/CD, and iterating with stakeholders on domusAI, domiAI, domusDocs and multi-agent frameworks.

Design, develop, fine-tune, and deploy generative AI models (LLMs, diffusion, VAEs). Build data pipelines, APIs, and integrate AI into production while improving performance and collaborating with cross-functional teams.

Design, build, and scale production Generative AI systems: multi-agent workflows, advanced RAG pipelines, model fine-tuning and quantization, LLM integration and swapping, high-performance FastAPI backends, vector search and retrieval, containerized deployment, and monitoring for latency, cost, and reliability.