Top Artificial Intelligence Jobs in Mumbai

Create AI-powered videos for Reels, advertisements, campaigns, and social media. Transform concepts into visual stories using AI-generated assets, live-action footage, animation, audio, and effects. Edit and package polished videos with Premiere Pro, After Effects, Canva, and similar tools. Collaborate with creative and marketing teams, apply short-form storytelling principles, experiment with emerging AI workflows, and improve content quality and efficiency.

Develop scalable enterprise applications and REST APIs using Python or .NET/C#, integrate Azure and Microsoft Fabric services, build SQL-based data and ETL/ELT solutions, and support Lakehouse, OneLake, and Data Warehouse architectures. Integrate LLMs and RAG capabilities into enterprise applications, troubleshoot application and data-pipeline issues, and collaborate with product, data, AI, and business teams. Backend and integration development are the primary focus, with working knowledge of modern front-end frameworks expected.

Designs, operates, and improves scalable cloud infrastructure across GCP and AWS. Builds Terraform-based infrastructure, GitHub Actions CI/CD pipelines, observability, automation, and AI-enabled monitoring and remediation. Manages MySQL and SQL Server databases, Cloudflare services, security controls, repository governance, and incident response. Supports reliability, performance, cost optimization, compliance, and cloud modernization while providing 24/7 on-call coverage and mentoring junior engineers.

Architect and build production-grade generative AI and agentic AI applications, including LLM workflows, multi-agent systems, RAG pipelines, APIs, and ML/GenAI infrastructure. Develop and optimize models, manage deployment and monitoring, apply responsible AI practices, and collaborate directly with customers. The role also involves mentoring engineers and shaping AI platform strategy.

Build and deploy production-ready AI agents and multi-agent systems on Azure. Design RAG pipelines, orchestration patterns, tool integrations, APIs, prompt engineering workflows, evaluation loops, and unstructured-data pipelines. Implement CI/CD, monitoring, responsible AI controls, and enterprise integrations with Microsoft Teams and M365 Copilot. The role requires hands-on GenAI/LLM engineering, Python development, cloud infrastructure expertise, and flexibility across data engineering, low-code configuration, and AI-native development tools.

Design and architect production-grade ML and GenAI solutions on Databricks, including RAG and agentic systems, MLOps pipelines, training/inference optimization, model monitoring, and customer-facing technical enablement and mentorship.

Design, build, test, and deploy production-grade agentic AI systems using Python, LangGraph, LangChain, AWS Bedrock, and orchestration tools. Integrate AI agents with APIs and business systems, implement memory and retrieval, establish observability and safeguards, and develop reusable SDKs and templates. Collaborate directly with clients to define requirements, run experiments, and rapidly deliver reliable AI solutions using modern software engineering, cloud deployment, and CI/CD practices.

Designs and maintains a centralized AI platform and agentic framework for secure enterprise deployment and access. Builds scalable AI agents, unified APIs, distributed systems, and microservices; integrates agents into customer and internal applications; optimizes cloud-native workloads; ensures security and regulatory compliance; and leads technical strategy, mentoring, performance analysis, and capacity planning.

Designs and maintains a centralized AI platform and agentic framework supporting secure deployment, management, and integration of AI agents. Responsibilities include building scalable agentic solutions, developing unified APIs, integrating agents into applications, optimizing cloud-native workloads, ensuring security and compliance, conducting capacity planning, mentoring engineers, and shaping the platform roadmap.

Build governed Databricks Lakehouse foundations and productionize machine learning and GenAI solutions, including forecasting, anomaly detection, NLP, RAG, and predictive analytics. Develop reliable batch and streaming workflows, CI/CD, monitoring, governance, security, lineage, and semantic models. Collaborate with product, data, platform, and domain teams to deliver measurable customer value while meeting reliability, compliance, cost, and operational objectives.

Develop, deploy, and maintain machine learning and AI solutions, including predictive models, NLP applications, chatbots, LLMs, and agentic AI systems. Build scalable data and ETL pipelines using cloud platforms, big data technologies, and databases. Apply TensorFlow, PyTorch, Hugging Face, and cloud AI services while creating data visualizations and optimizing analytics workflows.

Audit AI agent call and chat transcripts against quality and compliance standards, identify regressions and edge cases, document actionable engineering issues, and participate in client QA and audit calls. Reconcile internal findings with client audits, explain performance data, and provide recurring quality insights to the Technical Program or Product Manager for release communications and client reviews.

Sell and position the FICO Platform to enterprise clients in consumer lending and retail banking. Build senior stakeholder relationships, uncover decision-management opportunities, collaborate with pre-sales and internal teams to design solutions, and drive long-term, profitable customer engagements. Manage quarterly and annual sales targets and travel up to 50% to engage customers across Southeast Asia and adjacent industries (fintech, telecom, media, entertainment).

Build and deploy AI-powered tools, agents, MCP integrations, and workflow automations. Own packaging, testing, hosting, monitoring, and production release cycles. Develop evaluation sets, regression checks, and human review processes to validate AI outputs. Use Claude and other LLM platforms, Python, SQL, React, and Docker. Collaborate across teams to identify automation opportunities, document technical solutions, assess data confidentiality, and communicate results to technical and non-technical stakeholders.

Lead discovery, rapid prototyping, and deployment of production-ready AI solutions for supply chain and manufacturing. Build Python-based RAG pipelines, semantic search, multi-agent workflows, data integrations, and enterprise platform connections. Engage frontline operations, translate business needs into technical requirements, manage agile delivery, and ensure prototypes are scalable and transferable to core engineering teams. Work across SAP, MES, shop-floor platforms, databases, telemetry, and unstructured data while collaborating with security, data, and architecture teams.

Leads the design, deployment, governance, monitoring, and lifecycle management of finance AI agents. Builds semantic data layers using BigQuery, dbt, and Fivetran; defines agent architecture, controls, escalation thresholds, auditability, and performance KPIs. Reengineers finance processes for agent-assisted workflows, manages AI risk and internal controls, and trains finance teams on adoption, usage, limitations, and change management.

Lead visual design across brand identities, campaigns, digital platforms, social media, presentations, and other creative touchpoints. Translate strategic briefs into visual systems, explore AI-assisted design workflows, develop generative visuals and prototypes, maintain brand consistency, collaborate with strategy and copy teams, support pitches, manage multiple projects, review AI outputs, and mentor junior designers.

Lead architecture and hands-on development of Accrete’s AI Platform across frontend, backend, infrastructure, and platform services. Build scalable APIs, AI agent orchestration infrastructure, developer tools, data integrations, and production AI/ML systems. Drive technical direction, reliability, security, performance, observability, and cloud-native operations while mentoring engineers and owning initiatives from architecture through deployment and iteration.

Build and test LLM applications, AI agents, multi-agent systems, RAG pipelines, and autonomous workflows. Integrate tools, APIs, databases, and vector search; experiment with agent frameworks, transformers, prompt engineering, evaluation, monitoring, and AWS deployment. Collaborate on prototyping and productionizing AI copilots and intelligent automation. Requires Python, machine learning, LLM, agentic AI, RAG, and AWS knowledge, with hands-on project experience preferred.

Coordinates the AI Accountability Network’s newsletters, training programs, grants, fellowships, payments, events, communications, and community initiatives. Manages editorial workflows, contractors, applications, logistics, websites, listservs, dashboards, metrics, and stakeholder communications. Supports grant administration, funder reporting, travel, curriculum development, and website publishing while improving processes and tracking program impact.

Build and refine AI-powered prototypes for supply chain and manufacturing operations. Engage with factory and warehouse teams, translate operational needs into software requirements, develop Python-based RAG and agentic systems, integrate APIs and data sources, and iterate prototypes based on frontline feedback. The role involves SQL and document data preparation, agile collaboration, occasional manufacturing-site travel, and progressive adoption of enterprise AI frameworks and production engineering practices.

Design, build, and scale production AI agents across EveryWatch. Own the agent roadmap, architecture, shared tools, memory, state, observability, evaluation, and cost controls. Harden WatchChat, develop RAG and tool-calling systems, establish measurable quality standards, and ship solutions directly in Python. Collaborate with sales, product, data, and engineering teams to identify high-impact use cases and take agent concepts from discovery through production.

Join Welo Data’s Canadian French contributor network for potential remote AI projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts for large language models; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and details provided before each assignment.

Join Welo Data’s French AI Trainers Network as a flexible contributor supporting annotation, evaluation, and prompt creation projects. Contributors may label text, images, or audio; assess search results, advertisements, and chatbot responses; create prompts for large language models; and ensure cultural and linguistic accuracy. This is a talent community rather than an active opening, with project details and compensation provided when assignments become available.

Designs and implements end-to-end generative AI and LLM solutions, researches emerging AI techniques, develops supporting libraries and frameworks, and participates in software delivery from design through maintenance. The role applies NLP, computer vision, audio, and multimodal AI methods; uses cloud and open-source platforms; contributes to code reviews and roadmaps; and collaborates with cross-functional teams.