Agentic AI Leader - FS & Banking | 15+ years

Capgemini -
Chennai, Tamil Nadu

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Job details

Permanent

Qualifications

CI/CD
Azure
Law
Doctoral degree
Computer Science
MCP
Enterprise Software
Master's degree
OS Kernels
AWS
Bachelor's degree
Continuous integration
Natural language processing
APIs
Business Administration
Fraud prevention and detection
Solution architecture
AI
Banking

Full job description

Job Description

We are looking for a strong Agentic AI Leader to drive enterprise-wide AI transformation initiatives with a deep focus on Agentic AI, Generative AI (GenAI), and intelligent automation. This role demands expertise in multi-agent orchestration, LLM-based architectures, and enterprise AI strategies, with a strong focus on Financial Services (FS) Banking operations including risk management, compliance, fraud detection, and customer experience.

Primary Skills

The ideal candidate will have a proven track record of leading large-scale, transformative AI programs, delivering autonomous agent frameworks that redefine business processes and accelerate digital transformation. This role requires proficiency in strategic assessments, solution architecture, and ROI modelling, shaping the future of our AI-driven solutions with emphasis on reusability, scalability, governance, and secure deployment at an enterprise level.

Key responsiblities:-

Define the Agentic AI strategy and roadmap, aligned to enterprise digital transformation, regulatory priorities, and growth objectives.
Own end to end delivery of agentic AI initiatives from discovery and feasibility through architecture, build, production deployment, and value realization.
Identify high impact automation opportunities where intelligent agents can orchestrate complex, multi step workflows (e.g. compliance checks, personalized customer service, fraud monitoring and dispute resolution, collections and payment recoveries).
Lead and direct cross functional squads (AI/ML engineers, data scientists, domain SMEs, platform/IT, risk/compliance) to deliver robust, scalable Solution on time and on budget.
Adhere to organizational best practices for agent design by embedding advanced planning and reasoning capabilities, secure and compliant tool integration, robust memory and state management, and optimized retrieval strategies for performance and scalability.
Collaborate with Product, Technology, and Platform teams to secure infrastructure, tooling, and data required to scale agent-based solutions (including capacity planning and cost governance).
Foster a culture of innovation, and continuous learning playbooks, and re usable assets/accelerators.
Promote engineering excellence (coding standards, MLOps/AIOps, testing, observability) and domain literacy across delivery teams.
Strong business acumen with the ability to build business cases & ROI driven proposals.
Stakeholder influence and executive storytelling; ability to lead geographically dispersed, multi disciplinary teams.
Knowledge of industry best practices in automation, governance, process improvement, and change management for enterprise adoption.

Secondary Skills

Experience: 18+ years of progressive leadership in technology, strategic consulting, or complex program delivery within Financial Services/Banking; 5+ years driving GenAI/agentic AI programs at enterprise scale.
Education: Bachelor’s or Master’s in Computer Science or Ph.D., Engineering, Business Administration, or related quantitative field.
Agentic AI Expertise: Demonstrable end‑to‑end delivery of solutions using LLM orchestration frameworks, planning & reasoning architectures, memory/state management, and secure tool‑use by agents.
Domain Knowledge: Deep understanding of core banking processes (retail banking, commercial lending, wealth management), and risk & compliance disciplines (KYC/AML, fraud, credit).
Deep expertise in modern AI/ML technology stacks, proficiency with leading cloud platforms (Azure, GCP), strong understanding of data governance principles, and hands-on experience in API integration with core enterprise systems
Proven ability to lead large, geographically dispersed teams; exceptional communication and executive presence, able to translate technical detail to business impact.
Agentic orchestration & frameworks: LangGraph, Semantic Kernel, Agent Framework, CrewAI (or equivalent), and Model Context Protocol (MCP) for cross‑agent interoperability.
Multimodal Agents: Architect and deliver solutions leveraging Azure AI capabilities, including Azure AI Foundry, Azure OpenAI Service, Cognitive Services (Vision, Speech, Language), Document Intelligence, and Conversational AI enabling agents to process documents, conversational interfaces (chat/voice), tabular and transactional data, knowledge of OCR/NLP pipelines and speech recognition frameworks for enterprise grade.
Cloud & AI services: Azure AI Foundry/Agent Service, Copilot Studio, Azure OpenAI (or equivalents AWS Sagemaker, GCP Vertex AI); strong MLOps/AIOps patterns and CI/CD for ML.

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Job Description

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