Top Artificial Intelligence Jobs in Mumbai

Develop scalable enterprise full-stack applications using Java and modern front-end frameworks. Build, integrate, test, debug, and document backend and frontend components; use AI copilots and LLM tools to accelerate development; integrate AI services and APIs, including RAG features; and collaborate with architects and AI specialists. The role requires strong SDLC knowledge, cloud-native development, API integration, and delivery of reliable software using agile engineering practices.

Build, train, evaluate, and deploy machine learning and generative AI models for fraud detection, financial agents, and safety systems. Develop high-throughput data and inference pipelines using distributed technologies, optimize GPU model serving, maintain feature stores, fine-tune language models, and implement evaluation guardrails. Collaborate with architects and engineers while applying MLOps, cloud, containerization, and software engineering practices.

Manage a strategic enterprise account within a large conglomerate, building executive relationships and driving value-based growth. Expand Databricks adoption across business units and use cases, exceed pipeline and revenue targets, forecast opportunities in Salesforce, and sell the Databricks Data Intelligence Platform powered by Apache Spark and Delta Lake. The role requires guiding complex deals, communicating technical value, and collaborating with customers, system integrators, and internal teams.

Lead strategic enterprise relationships in the IT-Enabled Services sector, helping customers execute AI, cloud, cybersecurity, automation, and digital transformation initiatives. Build C-suite partnerships, shape transformation roadmaps, identify growth opportunities, develop account and go-to-market plans, lead co-sell execution, manage pipelines, and align Microsoft and partner teams to achieve revenue and cloud consumption targets.

Create social media, digital campaign, internal, and external communication creatives across formats including banners, thumbnails, carousels, and infographics. Maintain brand consistency, collaborate with marketing and content teams, incorporate feedback, and use AI tools for ideation, image generation, creative enhancement, and workflow optimization.

Lead technical sales engagements with multinational enterprise customers, shaping Azure-based application modernization, AI, cloud, and hybrid solutions. Own technical direction for complex opportunities, conduct discovery and demonstrations, build prototypes, advise executive and technical stakeholders, and connect architecture decisions to business value. Collaborate with specialists, partners, and account teams to drive adoption, develop roadmaps, overcome technical barriers, and create reusable architectures and approaches.

Leads advanced analytics, KPI governance, process mapping, and digital transformation across global procurement, supply chain, fulfillment, logistics, manufacturing, and commercial operations. Develops dashboards, predictive analyses, SAP-based reporting, and actionable insights to improve inventory, fulfillment, supplier performance, forecasting, and customer service. Partners with global stakeholders on process standardization, technology adoption, change management, and continuous improvement initiatives.

Design, build, deploy, integrate, and optimize production voice AI agents for enterprise clients. Develop backend integrations using APIs, WebSockets, webhooks, CRM systems, cloud services, and AI frameworks. Monitor agent performance, analyze logs and traces, conduct root-cause investigations, optimize conversational funnels, and lead client workshops and deployment reviews.

MBA summer associates join Roland Berger consulting teams for 8–12 weeks, working on real client projects across global offices. Interns apply strategic thinking, analytical and creative problem-solving, teamwork, entrepreneurial skills, and AI and data capabilities to complex business challenges. Outstanding performers may receive full-time offers.

Leads enterprise IT operations, data security, AI strategy, automation, Salesforce optimization, infrastructure scalability, disaster recovery, vendor management, and technology cost optimization. The role drives digital transformation, regulatory compliance, risk mitigation, process efficiency, and measurable business outcomes while coordinating cross-functional technology initiatives.

Designs and leads scalable AI platform infrastructure, agent frameworks, orchestration layers, backend services, APIs, and cloud deployments. Optimizes LLMs and fine-tunes small language models using techniques such as quantization, distillation, RAG, caching, and prompt optimization. Implements MCP integrations, supports enterprise multi-agent workflows, evaluates emerging AI tools, partners with stakeholders, mentors engineers, and establishes engineering standards.

Supports development and maintenance of core AI infrastructure, including AI agents, LLM and prompt optimization, backend services, APIs, cloud deployments, and MCP integrations. Writes tested Python code, troubleshoots infrastructure, participates in code reviews and sprint planning, and documents technical processes. Requires Python, AI agent, LLM, backend, AWS, and MCP knowledge, plus a bachelor's degree and at least three years of experience.

Lead architecture, design, and development of production-grade Generative AI and agent-based solutions for KYC operations. Define technical strategy, implement agent training and feedback loops, ensure compliance/security/performance, mentor engineers and data scientists, and manage projects with Agile processes.

Leads consultative discovery and solution development for AspenTech customers across Oil & Gas, Chemicals, Power, Mining, and Food & Beverage industries. Partners with sales teams to identify business challenges, demonstrate software capabilities, develop value propositions, create proposals and scopes of work, and support opportunities through solution design and delivery. Requires strong industry, technical, analytical, communication, and consultative expertise, with substantial regional travel across APJ.

Owns QAD Support’s AI roadmap and governance while coordinating cross-functional initiatives from opportunity identification through implementation, adoption, and optimization. The role manages milestones, dependencies, risks, stakeholders, vendors, success criteria, and measurable business outcomes. It also drives AI enablement, training, communications, continuous improvement, and compliance with security, privacy, legal, and data governance requirements. This is an individual contributor position requiring strong program management and practical AI knowledge, without hands-on AI development.

Leads the design, development, and deployment of advanced data science and AI solutions across business areas. Provides hands-on technical leadership, solution architecture, stakeholder engagement, mentoring, and portfolio-level decision-making. Applies machine learning, GenAI, LLMs, RAG, AI agents, graph technologies, and cloud platforms to deliver measurable business impact and improve operational efficiency and decision-making.

Leads enterprise technology strategy, delivery, and transformation across Finance, FinTech, Legal, and Risk. Oversees product platforms, Agile and DevOps adoption, AI and data initiatives, digital transformation, change management, vendor partnerships, governance, and technology operations. Partners with executive stakeholders to align global priorities, integrate platforms, manage dependencies, and deliver scalable, secure, value-driven outcomes across a federated enterprise technology organization.

Drive technical sales for Azure infrastructure and AI solutions by leading architecture workshops, demos, proofs of concept, migrations, and modernization initiatives. Design secure, scalable, resilient hybrid-cloud architectures; advise on networking, containers, enterprise applications, compliance, and Azure services. Partner with customers, engineering teams, and platform leaders to remove technical blockers, accelerate deployments, and communicate Microsoft’s cloud capabilities through technical forums and thought leadership.

As a Senior Business Systems Analyst, you will define system goals, capture business requirements, and work with engineering teams on SFDC implementations.

Drive new business and acquire customer accounts across a Mumbai territory. Responsibilities include prospecting, managing end-to-end sales cycles, building pipeline with SDRs, partnering with Sales Engineers, forecasting, reporting, and exceeding quotas. The role also supports subscription renewals and cross-selling. Candidates should be technically adept, persuasive, disciplined, coachable, and experienced in selling complex solutions to executives and technical evaluators. Cybersecurity, SaaS, cloud-native security, and EDR experience are advantageous.

Coordinate workforce planning and deployment for over 1,800 contributors across AI training projects. Allocate resources based on project demand and capacity, maintain deployment and availability records, monitor onboarding and throughput, identify conflicts and shortages, track requests, coordinate with project and training teams, conduct shift handoffs, and improve resource-planning processes and workflows.

Leads quality assurance for AI training data by managing review queues, auditing annotations, monitoring quality trends, coaching reviewers, clarifying guidelines, training new team members, identifying recurring errors, and escalating complex issues. The role also supports corrective actions and continuous improvement while ensuring accurate, consistent, and timely project delivery.

Leads AI data annotation teams through project delivery, translating client guidelines into workflows, setting production targets, monitoring quality and productivity metrics, coaching team members, managing staffing and deadlines, and resolving operational risks. Partners with QA and tooling teams to improve processes and maintain accurate, timely training data delivery in a fast-paced environment.

Lead enterprise architecture strategy for a global financial institution. Review fraud-domain application portfolios, assess architecture options and build-versus-buy decisions, conduct rationalization assessments, define target-state “north star” architectures, and create estimates, roadmaps, and transition architecture diagrams. Serve as a technical authority while translating complex business challenges into scalable solutions and collaborating with technical and business stakeholders.

Leads emerging product innovation from opportunity discovery through prototyping, pilots, product-market validation, commercialization, and scale. Owns AI, data, analytics, automation, and platform product strategies; establishes experimentation and stage-gate governance; develops investment cases and go-to-market plans; and aligns cross-functional teams and executives. Manages product leaders, builds incubation practices, and drives measurable customer, revenue, efficiency, and strategic outcomes.