Top Artificial Intelligence Jobs in Mumbai

Delivers Microsoft Azure data and AI consulting solutions for strategic customers. Designs modern data platforms, scalable pipelines, lakehouse architectures, generative AI and machine learning solutions, governance frameworks, security controls, and Power BI analytics. Advises senior client stakeholders, manages projects and priorities, mentors peers, contributes reusable intellectual property, and drives customer outcomes. Requires deep technical expertise, strong communication, client relationship management, and 10+ years of technology experience, including four or more years delivering Azure data and AI solutions.

Designs and builds scalable AI/ML infrastructure and computational science solutions on AWS. Responsibilities include scientific data pipelines, simulation analytics, feature engineering, model development, deployment, monitoring, MLOps, optimization, and cloud-native integration. Leads technical workstreams, guides implementation decisions, mentors engineers, creates reusable engineering assets, and collaborates with architects, data scientists, domain experts, clients, and delivery teams. Requires strong Python, SQL, AWS, scientific computing, machine learning, data engineering, and production deployment expertise.

Own the vision, roadmap, development, and commercialization of AI interfaces and agent solutions for sustainability and climate products. Lead MCP and AI Insights enhancements, ensure data is AI-ready across APIs, data feeds, Snowflake, and client platforms, and collaborate with Engineering, Research, Legal, Data Operations, and Client Coverage. Validate solutions with clients, define requirements and documentation, support governance reviews, present business cases, and track adoption, quality, and commercial impact.

Designs and delivers applied AI and automation solutions for insurance, asset-management, and finance processes. Responsibilities include architecture, RAG, LLM and agentic workflows, systems integration, AI evaluation, responsible-AI controls, LLMOps/MLOps, and value measurement through analytics and process mining.

Designs and oversees enterprise software architecture, development, testing, implementation, and technical documentation. Partners with stakeholders and Product teams to define requirements, evaluate technologies, create scalable solutions, review code, support application integrations, and guide development teams. The role also coordinates technology projects, training, system improvements, security, quality, and extensibility while providing technical support for case and client efforts.

Develop and ship Yahoo Mail mobile features for Android, owning projects from technical design through deployment, monitoring, and improvement. Build scalable solutions using Kotlin, Java, Android frameworks, Jetpack Compose, and React Native; integrate APIs; address performance, reliability, and usability challenges; conduct code reviews; collaborate cross-functionally; mentor teammates; and use AI development tools to improve engineering productivity while maintaining quality and security.

Own enterprise AI customer deployments from discovery and product scoping through delivery, adoption, and value realization. Translate customer workflows into product requirements, technical solutions, deployment roadmaps, and measurable outcomes. Partner with engineering, sales, customer success, finance, legal, security, and operations while evaluating AI trade-offs, business value, and production readiness. Identify reusable customer needs and help establish scalable product, operating, and deployment playbooks.

Leads quantitative finance initiatives within Corporate Treasury, supporting production analytics, reporting, forecasting, market risk, and operational stability. Responsibilities include developing analytical solutions, modernizing platforms, automating processes with AI and advanced analytics, improving data governance, collaborating with global stakeholders, maintaining documentation, and managing project scope, risks, timelines, dependencies, and delivery governance.

Manage enterprise customer portfolios and drive onboarding, adoption, ROI, renewals, and expansion of Anaplan’s platform. Serve as a strategic advisor to executive stakeholders, lead business reviews, develop success plans, promote AI and platform expansion, mitigate renewal risks, and advocate for customers internally. The role requires deep FP&A or supply chain planning expertise, experience with enterprise planning platforms, and strong consultative communication skills.

Chief of Staff to the CHPO, responsible for building the HP function’s operating system, translating strategy into priorities, improving leadership cadences, supporting executive decision-making, and driving cross-functional execution. The role will lead selected organization-development initiatives, strengthen accountability, use data to form recommendations, and identify practical AI applications across recruiting, employee listening, analytics, knowledge management, and HR operations.

Build applied AI systems and prototypes using LLMs, RAG pipelines, vector databases, agentic workflows, structured extraction, and custom models. Design evaluation frameworks, measure accuracy and grounding, analyze errors, and iterate on solutions. Work with large structured and unstructured datasets using Python, SQL, and cloud data platforms. Partner with product, data, engineering, and business teams to translate ambiguous problems into measurable AI solutions and document architectures, prompts, runbooks, and results.

Architect and optimize production AI and Snowflake infrastructure, including scalable warehouses, Snowpark workloads, secure data and feature pipelines, model integrations, automation, CI/CD, observability, governance, and cost controls. Evaluate technologies and architecture alternatives, lead assessments and roadmap planning, establish reliability and compliance practices, and mentor engineers while aligning technical decisions with client business requirements.

Develop scalable full-stack enterprise applications using Java and modern frameworks. Build frontend and backend components, integrate AI services and APIs, implement RAG features, and use AI-assisted development tools for coding, testing, debugging, and documentation. Collaborate with architects and AI specialists while following software engineering, SDLC, agile, quality, and CI/CD practices.

Architects and engineers scalable Snowflake-based AI and data infrastructure for production applications. Designs warehouses, Snowpark workloads, AI-ready pipelines, model integrations, governance, CI/CD, observability, and cost optimization. Evaluates infrastructure technologies, leads architecture reviews, defines roadmaps and standards, ensures security and compliance, and mentors engineering teams while aligning technical solutions with client requirements and business outcomes.

Architects and engineers scalable Snowflake-based AI and data infrastructure for production workloads. Designs warehouses, Snowpark workloads, feature pipelines, model integrations, automation, CI/CD, observability, governance, security, and cost optimization. Leads architecture assessments, technology evaluations, roadmaps, capacity planning, and infrastructure standards while ensuring compliance and reliability. Partners with clients and engineering teams, provides technical direction, reviews designs and code, and mentors engineers.

Develop and enhance enterprise-grade full-stack applications using Java, .NET, Python, React, or Angular. Design scalable cloud-native solutions across AWS, Azure, and Google Cloud, build API and microservices integrations, and implement AI-enabled features. Collaborate with DevOps teams on Docker, Kubernetes, infrastructure as code, and CI/CD. Apply secure coding, performance optimization, testing, and architectural best practices while mentoring teams and translating business needs into technical solutions.

Develop scalable enterprise full-stack applications using Java and modern frameworks. Build front-end and back-end components, integrate APIs and pre-built AI services, implement RAG features, and use AI-assisted development tools for coding, testing, debugging, and documentation. Collaborate with architects and AI specialists while applying software engineering, SDLC, agile, cloud-native, and CI/CD practices.

Develop scalable full-stack enterprise applications using Java and modern frameworks. Build frontend and backend components, integrate AI services and APIs, implement RAG features, and use AI-assisted development tools for coding, debugging, testing, and documentation. Collaborate with architects and AI specialists while applying software engineering, SDLC, agile, cloud-native, and CI/CD best practices.

Develop full-stack enterprise applications using Java and AI-assisted development tools. Build front-end and back-end components, integrate AI services and APIs, implement RAG features, and deliver scalable solutions through modern engineering, SDLC, testing, documentation, and CI/CD practices. Collaborate with architects and AI specialists to accelerate delivery while maintaining software quality.

Develop scalable full-stack enterprise applications using Java and modern frameworks. Build front-end and back-end components, integrate AI services and APIs, implement RAG features, and use AgentAI copilots and LLM tools for coding, testing, debugging, and documentation. Collaborate with architects and AI specialists while applying software engineering, SDLC, agile, integration, and quality practices.

Develop and enhance scalable Java full-stack software solutions for complex business environments. Responsibilities include technical design, coding, testing, maintenance, architecture and code reviews, debugging distributed systems, improving existing applications, and supporting customers. The role leads technical initiatives, mentors developers, evaluates new technologies, and collaborates with product, engineering, and cross-functional teams. Experience with cloud infrastructure, DevOps, web services, databases, testing practices, AI modernization, and enterprise systems is required.

Develop and enhance scalable full-stack enterprise applications using Java and modern frameworks. Build front-end and back-end components, integrate AI services and APIs, implement RAG features, and use AgentAI copilots and LLM-based tools for coding, testing, debugging, and documentation. Collaborate with architects and AI specialists while applying enterprise engineering, SDLC, cloud-native, API, and CI/CD practices to accelerate delivery without compromising quality.

Develop scalable enterprise full-stack applications using Java and modern frontend frameworks. Build, integrate, test, debug, and document software with AI-assisted development tools and LLM services. Implement APIs, cloud-native solutions, CI/CD pipelines, and RAG-based features where appropriate while collaborating with architects and AI specialists. The role requires strong SDLC knowledge, enterprise engineering experience, and the ability to deliver quality software efficiently.

Develop and enhance scalable full-stack enterprise applications using Java and modern frameworks. Build frontend and backend components, integrate AI services and APIs, implement RAG features, and use AI-assisted development tools for coding, testing, debugging, and documentation. Collaborate with architects and AI specialists while following engineering best practices, SDLC processes, agile methods, cloud-native development, and CI/CD practices.

Develop and enhance scalable enterprise full-stack applications using Java and modern frameworks. Build front-end and back-end components, integrate AI services and APIs, implement RAG features where appropriate, and use AgentAI copilots and LLM-based tools for coding, testing, debugging, and documentation. Collaborate with architects and AI specialists while maintaining engineering quality, SDLC standards, and delivery speed.