Vice President, Product Manager - Technical & AI-Enabled - Investor Services

The role of Product Manager is evolving. It is no longer sufficient to write requirements and hand them to engineering. The most impactful product leaders today are those who can think in systems, prototype in code, and ship with conviction. We are hiring a Technical Product Manager within our Investor Services division to own the product vision and roadmap for strategic platform initiatives (including Citi Velocity today and Citi Direct in the future), while being highly technically literate and ready to build alongside engineering teams, challenge architectural decisions, and prototype solutions directly. This is a product role at its core. You will drive strategy, define OKRs, manage stakeholders, and lead complex change programs. But you will do so with a level of technical depth that sets you apart: you understand codebases, you can read and write code, you can evaluate AI architectures, and you can sit in a room with engineers and contribute - not observe.

Our primary stack is Java and React, with Python supporting scripting, data pipelines, and AI/ML integrations. Our engineering philosophy is AI-native - we expect you to understand and leverage large language models, agentic workflows, and AI-assisted development as core tools reshaping how products are built and delivered.

Responsibilities

• Define, prioritise, and communicate our product roadmap for strategic application changes, upgrades, and migrations in close partnership with our engineering team, other Product teams and senior leadership.
• Lead and product-manage complex programs end-to-end – from inception through architecture, data migration, integration, testing, cutover, and successful client adoption.
• Establish and track OKRs for product success, client adoption rates, and change effectiveness. Implement feedback loops to continuously improve delivery frameworks.
• Identify where AI, LLMs, and agentic automation can transform Investor Services workflows. Own the product vision for AI-enabled capabilities and drive them from concept to production.
• Build and maintain strong relationships across Technology, Operations, Product, Sales, Client Services, and external clients within a complex, matrixed global organisation.
• Ensure adherence to internal policies, regulatory requirements, and industry best practices throughout the product lifecycle, demonstrating sound ethical judgment in a regulated financial services environment.

Technical Depth and Hands-On Delivery

• Prototype solutions, contribute to technical design discussions, and validate approaches by building – using Java, React, or Python as the situation demands.
• Understand the current landscape of foundation models and make informed product decisions about when to use fine-tuning vs. RAG vs. prompt engineering vs. full agentic orchestration.
• Evaluate AI architectures proposed by engineering teams with genuine technical judgment. Know the trade-offs around latency, cost, hallucination mitigation, and guardrails in production AI systems.
• Understand how LLM-powered agents reason, plan, use tools, and orchestrate multi-step tasks autonomously. Be familiar with frameworks such as LangChain, LangGraph, Google ADK, CrewAI, AutoGen, and Semantic Kernel with the ability to make sound product decisions about feasibility, risk, and their transformative potential.
• Serve as the critical link between product vision and technical execution. Translate business needs into technical specifications and technical constraints into business language.
• Participate meaningfully in architecture design, data migration strategies, integration patterns, and testing approaches – ensuring data integrity and seamless client experience.

Client and Stakeholder Engagement

• Embed with internal stakeholders and clients to understand complex problems, facilitate adoption of new systems, and manage expectations through clear, proactive communication.
• Present to technical and non-technical audiences, run discovery sessions, and produce clear documentation that drives alignment and adoption.
• Identify, assess, and mitigate execution risks and issues, ensuring timely resolution and escalation.

Qualifications

• Significant experience in Product Management within Investor Services or Financial Services, with a track record of owning roadmaps, defining OKRs, and driving products from concept to client adoption.
• Genuine technical literacy – ability to read and write code in at least one of Java, Python, or JavaScript/TypeScript. Practical understanding of APIs, data models, microservices architecture, and CI/CD pipelines.
• Strong understanding of AI/ML and the current LLM landscape – ability to articulate the differences between fine-tuning, RAG, prompt engineering, and agentic orchestration.
• Understanding of foundation models, how they are accessed, and the production considerations around deploying them: latency, cost, safety, evaluation, and guardrails.
• Experience in Data, Digital, and Innovation – leading initiatives involving data migration, platform modernisation, or digital transformation.
• Demonstrated experience in a client-facing role, managing client expectations and facilitating adoption of new systems or processes.
• Proven ability to manage complex interdependencies between product development and project delivery.
• Exceptional leadership presence with a proven ability to influence, motivate, and align diverse, cross-functional stakeholders within a complex, matrixed global organisation.
• Ability to operate at both strategic and tactical levels.
• Excellent verbal, written, and interpersonal communication skills.
• Strong analytical and problem-solving abilities, with a focus on root cause analysis and proactive issue resolution.
• Bachelor’s/University degree required; Master’s degree preferred.

Nice-to-Haves

• Hands-on proficiency in Java (Spring Boot, microservices, RESTful APIs) and/or React (TypeScript).
• Working knowledge of Python for scripting, data engineering, and AI/ML integration.
• Experience with public cloud platforms (AWS, Azure, or GCP), including infrastructure-as-code, serverless architectures, containerisation (Docker/Kubernetes), and CI/CD pipelines.
• Hands-on experience building with AI agent frameworks (LangChain, LangGraph, Google ADK, CrewAI, AutoGen, Semantic Kernel) or implementing RAG systems with vector databases.
• Experience in a Forward Deployed Engineer, Solutions Engineer, or Technical Consultant role.
• Background in data engineering – ETL/ELT pipelines, data modelling, or analytics platforms.
• Familiarity with event-driven architectures, message queues (Kafka, SQS, RabbitMQ), and microservices patterns.
• Experience with advanced AI/ML engineering, including fine-tuning open-source models, building evaluation frameworks for LLM outputs, or designing guardrails for enterprise AI deployments.
• Experience with Citi Velocity, Citi Direct, or similar institutional client-facing platforms.
• Familiarity with Agile/SAFe methodologies and product management tooling (Jira, Confluence, Aha!)

Benefits

• Generous holiday allowance starting at 27 days plus bank holidays; increasing with tenure.
• Discretionary annual performance-related bonus.
• Private medical insurance packages to suit your personal circumstances.
• Employee Assistance Program.
• Pension Plan.
• Paid Parental Leave.
• Special discounts for employees, family, and friends.
• Access to an array of learning and development resources.