Top Artificial Intelligence Jobs in Mumbai

Manages regulatory finance data strategy and program initiatives across global regions. Responsibilities include data profiling, lineage mapping, governance, quality assessment, reconciliation, metadata management, requirements gathering, and regulatory reporting support. Partners with product, technology, and corporate teams to implement solutions, coordinate target operating models, improve processes, and deliver regulatory changes. The role requires strong stakeholder management, analytical, communication, and program management skills, with experience in financial services and data platforms.

Supports global network management operations by overseeing third-party due diligence, onboarding and offboarding, reference data, documentation, screening, governance reporting, and audit inquiries. The role coordinates with internal teams and external parties, investigates exceptions, maintains control evidence, prepares communications and briefing materials, supports technology changes and testing, and recommends process improvements that increase accuracy, efficiency, and risk control effectiveness.

Develop and enhance quantitative portfolio construction, asset allocation, optimization, risk management, and investment decision-support models. Conduct research, back-testing, stress testing, performance attribution, and analysis of large financial datasets. Partner with investment, product, and technology teams to implement analytical capabilities, integrate research into advisor workflows, and support model governance. Apply AI and machine learning to investment processes while maintaining transparency, controls, and analytical rigor.

Manages strategic programs and cross-functional projects within global Payments Operations. Responsibilities include project planning, governance, risk and dependency management, executive communications, dashboards, performance reporting, operational data analysis, process improvement, automation, and transformation initiatives. Partners with Operations, Product, Technology, Risk, Compliance, and Finance teams while maintaining firm-wide risk and control standards.

Execute T+1 control and AFR reconciliations, investigate and resolve discrepancies, coordinate with technology and business stakeholders, maintain reconciliation data and logic, escalate unresolved issues, and produce recurring reports. The role supports trade processing from order entry through settlement while improving operational efficiency, data quality, and process resilience.

Leads regional order-to-cash product integration across order capture, fulfillment, billing, collections, cash application, and customer care. Owns business requirements, portfolio visibility, governance, BPO performance, digital adoption, and value realization. Establishes a regional community of practice, aligns requirements with enterprise roadmaps, tracks Celonis KPIs, and holds product and operations leaders accountable. Requires strong OTC, SAP, Celonis, portfolio governance, financial, analytical, and executive stakeholder-management expertise.

Shape the Customer Care product across order-to-cash processes, translating business needs into scalable workflows, data requirements, integrations, and technology solutions. Lead SAP-informed solution design, roadmap development, transformation initiatives, analytics, AI-enabled service capabilities, testing, and vendor/SI partner management. Collaborate with business, architecture, integration, data, product, and delivery teams to improve customer service effectiveness, exception handling, visibility, and operational performance.

Manage second-line oversight of liquidity and interest rate risks across United Kingdom legal entities. Analyze bank balance sheets, monitor risk limits and indicators, assess emerging funding risks, review controls and regulatory requirements, and provide independent challenge to Treasury and risk teams. Prepare risk committee materials, support stress testing and scenario analysis, fulfill regulatory requests, and identify scalable technology solutions for management information and risk monitoring.

Supports central control management by coordinating governance routines, committee reporting, risk and control activities, remediation tracking, attestations, and third-party intermediary reviews. Maintains audit-ready documentation, dashboards, action logs, and executive reporting. Partners with stakeholders to escalate issues, monitor control performance, and close deliverables. Improves processes through standardization, automation, analytics, and approved AI-enabled workflows while ensuring compliance with internal policies and control frameworks.

Performs risk assessments, control testing, regulatory reporting quality reviews, remediation tracking, root-cause analysis, and process improvements for payments operations. Monitors reporting accuracy, completeness, timeliness, and control adherence while synthesizing leadership insights. Leads change initiatives and uses AI and machine learning for anomaly detection, data validation, and workflow analysis. Partners with global teams to strengthen regulatory compliance and reporting standards.

Lead and establish the Mumbai Core Risk Governance technology and risk team, deliver data, analytics, automation, and AI-enabled solutions, ensure controlled production-grade deployments, enforce governance, and partner with stakeholders to strengthen investment risk oversight and operational resilience.

Owns post-sales outcomes for large enterprise ServiceNow accounts in India, including implementation, adoption, value realization, renewals, and expansion. Builds trusted C-suite relationships, translates customer goals into platform roadmaps, establishes success metrics, coordinates ServiceNow and implementation partners, supports governance and organizational change, and communicates measurable business value. The role requires digital transformation expertise, consulting experience, AI fluency, and the ability to guide complex multi-track programs.

Manage full-cycle technical recruiting for Engineering, Product, Security, UX, and R&D roles. Partner with hiring leaders on role definition, structured interviews, sourcing strategy, market research, candidate assessment, pipeline management, and offer negotiations. Build diverse talent pipelines, use recruiting data to guide decisions, maintain accurate Greenhouse documentation, deliver an inclusive candidate experience, and improve recruiting practices through responsible AI use and shared resources.

Manage full-cycle recruiting for go-to-market roles across sales, marketing, customer success, professional services, and related teams. Partner with hiring leaders, build diverse talent pipelines, conduct structured assessments, use market and funnel data to guide hiring, manage candidate experiences, negotiate offers, and maintain recruiting documentation. The role also involves improving recruiting practices, responsibly using AI, and advising stakeholders in a globally distributed, remote-first environment.

Product Manager Intern will support AI-focused product development by defining and prioritizing features, documenting requirements, tracking success metrics, and coordinating with UX, research, engineering, and business stakeholders. The role includes translating technical concepts, assisting with bug triage, conducting user research and testing, analyzing product data, and presenting insights. Strong communication, curiosity, adaptability, user empathy, and interest in practical AI applications are emphasized.

Owns the strategic roadmap and implementation of supply chain digital capabilities, coordinating transformation efforts across Supply Chain, Finance, D&T, and external partners. Responsibilities include product and capability prioritization, vendor and contract management, technology exploration, training, documentation, benchmarking, change management, and advancing digital literacy. The role focuses on AI, smart alerts, automation, workflow tools, visibility, and advanced analytics while leading global, cross-functional initiatives.

Leads derivatives regulatory capital production, governance, controls, analytics, and remediation for SA-CCR RWA and supplementary leverage exposure. Oversees calculations, model implementation, regulatory compliance, variance attribution, control reviews, audit responses, and process improvements. Partners with Finance, Risk, Treasury, Technology, Front Office, Audit, and regulators while presenting complex derivative analytics to senior stakeholders. Requires deep knowledge of Basel III, derivatives lifecycles, counterparty credit risk, regulatory controls, and financial modeling.

Lead architectural design and modernization for an equity flow derivatives technology ecosystem. Build and maintain Java-based software solutions, collaborate with product owners and business stakeholders, solve complex technical problems, and improve technology platforms. The role requires hands-on development with Java, Java EE, microservices, REST, Spring Boot, reactive and event-driven architectures, databases, messaging, caching, and AI technologies. It also provides technical mentorship and leadership to a developer squad.

Leads end-to-end solution architecture and hands-on development across Java, Spring Boot, Python, APIs, distributed systems, data platforms, and AI/ML services. Defines high- and low-level designs, integration patterns, nonfunctional requirements, and production-readiness standards. Guides AI-assisted engineering practices, model productionization, MLOps, observability, security, resiliency, and responsible AI controls. Investigates performance and production issues while partnering with data science teams to deliver scalable, reliable services.

Build and deploy production-grade AI solutions for banking client onboarding, KYC, and document operations. Develop document intelligence models, LLM-based extraction and summarization frameworks, automation pipelines, APIs, and reusable AI modules. Collaborate with stakeholders, monitor and retrain models, analyze data, ensure privacy and governance compliance, and explore emerging AI technologies. The role may eventually expand into leadership of a specialized AI team.

Leads reporting analytics and modeling initiatives that deliver business insights to leadership. Designs dashboards, produces forecasts and reports, identifies risks, and improves performance through stakeholder engagement. Manages analytics projects and teams while ensuring data accuracy and quality. Requires advanced Excel, Power BI or Tableau, SQL, VBA, predictive analytics, data science, automation, storytelling, project management, and problem-solving skills.

Own strategic enterprise accounts in Mumbai, driving SAP cloud revenue through complex sales cycles, renewals, expansions, and upsells. Build executive relationships, lead account planning and governance, manage forecasts and pipeline growth, coordinate cross-functional teams and partners, mentor account executives, and ensure customer value realization. The role focuses on large enterprise and conglomerate clients across SAP’s cloud portfolio, including AI and public cloud solutions.

Build and lead production AI/ML components, including embeddings, retrieval, agents, and multimodal systems, for reuse across domain teams. Translate architectural direction into technical specifications and production-ready implementations, make implementation-level decisions, identify scalability issues, and mentor engineers. The role requires deep expertise in representation learning, vector search, retrieval-augmented systems, deep learning, LLMs, agent frameworks, distributed systems, and ML engineering.

Lead the architecture, development, deployment, and monitoring of production-grade machine learning systems for high-definition, ADAS, ISA, and IVI maps. Lead work across computer vision, NLP, deep learning, Generative AI, Agentic AI, MLOps, data ingestion, model training, inference, and scalable cloud or in-vehicle deployment. Provide technical leadership, conduct architecture and code reviews, integrate ML outputs with mapping workflows, and translate business requirements into reliable ML system designs.

Design, develop, and deploy production-grade AI systems using generative AI, LLMs, agentic architectures, retrieval, deep learning, and multimodal models. Build scalable representation and vector-search layers, lead experiments, optimize and evaluate models, and apply responsible AI practices. Collaborate cross-functionally to solve spatial and business challenges, mentor engineers and data scientists, and contribute to patents and publications. The role requires strong Python and ML framework expertise, production MLOps experience, and independent architectural decision-making.