Top Artificial Intelligence Jobs in Mumbai

Leads strategy, transformation measurement, executive reporting, performance analytics, and decision support for a global control testing organization. Translates operational, workforce, quality, risk, regulatory, and transformation data into insights and recommendations for senior leaders. Develops performance frameworks, dashboards, scorecards, and reporting roadmaps while identifying opportunities to improve data quality, simplify reporting, and automate management information. Partners across risk, compliance, audit, operations, technology, and analytics teams to drive accountability and organizational effectiveness.

Owns product quality frameworks and governance for ESG products across the product lifecycle. Defines quality standards, KPIs, dashboards, controls, and assurance plans; validates features, releases, and methodologies; monitors performance; leads root cause analysis and corrective actions; and drives automation, AI-enabled quality controls, process improvement, and cross-functional transformation with Product, Research, Technology, Data Operations, and Client Services.

Provides technical and domain expertise during sales cycles for ServiceNow solutions. Leads discovery workshops, product demonstrations, customer and partner technical discussions, competitive positioning, and solution development. Partners with sales, product management, marketing, and professional services teams to support pipeline growth and revenue goals. Contributes product feedback, reusable best practices, and marketing event support while managing an assigned territory.

Execute high-volume global payment processing, validate fund transfers, investigate sanctions/fraud, resolve reconciliation exceptions, collaborate cross-functionally, coach team members, and drive process improvements including AI-enabled optimizations.

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.

Lead design, implementation, and monitoring of control frameworks (CORE); drive automation, AI/ML and analytics for proactive risk identification; own RCSAs and control testing; partner with stakeholders to ensure regulatory compliance, streamline controls, and present findings to senior management.

Lead design and adoption of cloud-native architecture and AI-enabled engineering across Asset & Wealth Management. Advise on technology selection, create scalable reusable frameworks, develop and review secure production code, set multi-year roadmaps, and establish governance and guardrails for agentic AI, automation, and responsible AI use at scale.

Designs and develops generative AI and machine learning solutions for fixed income investment and business problems. Builds and fine-tunes models, analyzes structured and unstructured data, engineers features, evaluates performance, and supports deployment through APIs and scalable pipelines. Collaborates with portfolio managers, researchers, data engineers, and stakeholders while applying responsible AI principles, data governance, and clear communication of insights.

Leads development of secure, scalable Java and Spring Boot microservices and APIs. Designs, tests, debugs, and operationalizes production software while improving engineering productivity through AI-assisted development tools. Builds AI agents and LLM-enabled workflows using Python, with appropriate grounding, validation, security, and guardrails. Supports Kubernetes operations, CI/CD, application resiliency, and responsible adoption of AI engineering practices across the team.

Lead architecture and development of cloud‑native .NET microservices and high‑performance Web APIs. Drive AI adoption—design LLMs, agentic workflows, vector search/RAG, and AI‑augmented SDLC. Mentor senior engineers, own high‑impact technical decisions, optimise performance, and ensure secure, scalable delivery across the full SDLC in Finance/KYC domains.

Lead AI use-case discovery, design, prototyping and delivery. Partner with business leaders to frame outcomes, design architectures (RAG, LLMs, cloud AI), build MVPs using Python/APIs and low-code tools, and drive adoption with governance and responsible AI practices.

Lead design and deliver production-grade agentic AI systems (LLM orchestration, RAG, vector DBs, multi-agent setups). Develop secure, high-quality Python code, drive cloud-native deployments on AWS, CI/CD automation, and platform stability. Mentor teams, promote AI-assisted engineering practices, translate business/regulatory needs into technical designs, and guide adoption of responsible AI and validation standards across cross-functional squads.

Lead end-to-end AI architecture and delivery for commercial initiatives: design RAG and agent systems, select/configure LLMs, build data and MLOps pipelines, write production-quality code, mentor engineers, partner with business stakeholders, and champion responsible AI practices to scale commercial AI solutions.

Hands-on individual contributor who designs, builds, and deploys production-grade generative AI, RAG, and agentic systems for commercial analytics. Responsibilities include end-to-end RAG and agent pipelines, vector DB and embedding engineering, cloud LLM integrations, data pipelines, MLOps, model monitoring, prompt engineering, and cross-functional collaboration with compliance and business stakeholders.

Lead design, deployment, and management of prompt-based LLM models for NLP in financial services. Build data pipelines, MLOps tooling, and APIs; research prompt engineering and orchestration techniques; evaluate and optimize model performance; collaborate with cross-functional teams and communicate results to stakeholders.

Leads Citi’s global horizontal AI solutions strategy across Operations. Designs reusable capabilities such as knowledge assistants, operational intelligence tools, workflow copilots, and decision-support services. Partners with Product, Technology, Data, Risk, and Control teams to ensure scalable, secure, compliant delivery. Manages the AI solutions portfolio, drives operational readiness and adoption, measures impact, and aligns senior stakeholders around standardized solutions across multiple functions.

Leads consultative presales for credit and fraud risk solutions across Asia Pacific. Partners with clients and sales teams to discover challenges, develop proposals, business cases, platform demonstrations, executive presentations, and deal strategies. Serves as a subject matter expert across the risk lifecycle, payment ecosystems, authorization, authentication, lending, fraud, and collections. Supports go-to-market initiatives, innovation workshops, thought leadership, and proof-of-concept engagements, with travel of up to 50%.

Supports solution proposals, technical solution design, integrations, customer requirements gathering, demos, proofs of concept, technical questionnaires, scoping, documentation, implementations, training, and service estimates under senior mentorship. The intern helps customers understand technology solutions and applies AI, software development, and communication skills to practical customer-facing projects.

Lead design, build, and maintain secure, scalable software systems; write and review production-quality Python code; drive adoption and safe use of enterprise AI-assisted engineering tools; improve automation, resiliency, and operational stability; evaluate vendors and lead engineering communities of practice within Commercial and Investment Banking.

Design, develop, and maintain production ML solutions for trade surveillance and financial crime. Perform end-to-end model lifecycle work (feature engineering, training, validation, calibration, monitoring), support model governance and audits, collaborate with SMEs and MLOps for CI/CD and productionization, deliver interpretable explainability outputs, and incorporate GenAI/LLMs for unstructured text signal extraction.

Design, develop, and maintain production ML solutions for trade surveillance and financial crime use cases. Apply supervised and unsupervised methods, execute model lifecycle (feature engineering, training, validation, monitoring), support model governance, partner with MLOps for CI/CD, deliver explainable outputs, and leverage GenAI/LLMs for unstructured data extraction and summarization.

Designs and develops agentic artificial intelligence solutions. The posting provides limited details beyond a full-time, permanent role based in Bengaluru working the US Eastern Time shift.

The Agentic AI Architect role is a permanent, full-time position based in Bengaluru, working the US Eastern Time shift for Merkle. The provided description does not specify detailed responsibilities, qualifications, compensation, travel, or clearance requirements.

Leads consultative solution discovery and technical presales for AspenTech APM and related software across Oil & Gas, Chemicals, Power, Mining, and Food & Beverage industries in APJ. Develops customer-specific solutions, value propositions, proposals, scopes of work, sales campaigns, and implementation roadmaps. Partners with sales, consulting, and customers to identify business challenges, demonstrate software capabilities, and drive pipeline growth. Requires strong industry, technical, analytical, communication, and consultative skills, with 50–60% regional travel.

Lead journalism-style owned storytelling for Asia: edit and produce feature stories, blogs, visuals and social assets; drive syndication and engagement; collaborate across stakeholders to translate technical topics for nontechnical audiences and manage project execution to meet deadlines.