Director, Applied AI & Agentic Platform Engineering

Job d:

Location:

London, England, United Kingdom Category:
Technology, Applications Development, Executive Company:
Citi Our Vision We are building a next-generation system that reimagines banking workflows for our Corporate, Commercial, and Investment Bankers. Our vision is to empower them with a revolutionary Agentic AI Platform, featuring intelligent, autonomous agents that streamline processes, uncover new opportunities, and deepen client relationships—ultimately leading to significant productivity gains and increased wallet share. We are looking for a visionary, hands-on engineering leader to build and scale the platform that will make this a reality.

The Role As the Director of Agentic Platform Engineering, you will be a player-coach responsible for the technical vision, architecture, and execution of this greenfield platform. You will join a world-class engineering team being built from the ground up, while remaining deeply technical and contributing to the core development of the platform. This is a unique opportunity to blend strategic leadership with hands-on engineering to build a product that will have a direct and measurable impact on the front lines of our business.

Key Responsibilities Platform Architecture & Development:
Lead the design, architecture, and hands-on development of a scalable, secure, and resilient agentic AI platform from concept to production.

Technical Leadership & Hands-On Engineering:
Serve as the lead engineer and technical authority, guiding critical decisions on frameworks, technologies, and infrastructure. You will be expected to write code, build prototypes, and lead by example.

Team Building & Mentorship:
Recruit, hire, and mentor a high-performing, agile team of software and machine learning engineers. Foster a culture of innovation, excellence, and accountability.

Strategic Road mapping:
Partner closely with product management and senior business leaders in banking to define the product strategy and technical roadmap. Translate complex business needs into elegant technical solutions.

Cross-Functional Collaboration:

Partner effectively with horizontal AI platform teams, enterprise architecture, and external vendor partners to leverage existing capabilities, influence roadmaps, and accelerate delivery.

AI & ML Integration:
Drive the strategy for integrating and operationalizing Large Language Models (LLMs), agentic frameworks (e.g., Google ADK, Lang Chain,), and other AI/ML technologies to solve real-world banking challenges.

Operational Excellence:
Implement and champion best-in-class engineering practices, including CI/CD, automated testing, infrastructure-as-code, and robust monitoring to ensure enterprise-grade reliability.

Business Impact:
Define, measure, and report on key performance indicators (KPIs) related to platform adoption, user productivity, and the ultimate impact on business outcomes like wallet share growth.

Compliance & Security:
Ensure the platform adheres to the highest standards of data privacy, security, and regulatory compliance required in the banking industry.

Qualifications & Experience

Education:

Bachelor's or Master’s degree in Computer Science, Engineering, or a related technical field.

Experience:

Significant experience in software engineering, with proven years in a leadership role, leading high-performing engineering teams.

Hands-On Leader:
Proven experience as a "player-coach" who can lead from the front, contribute to the codebase, and mentor junior and senior engineers.

Platform Building: A strong track record of designing, building, and launching scalable, distributed, cloud-native platforms from the ground up.

Domain Knowledge:
Experience in the financial services industry (Corporate Banking, Investment Banking, Fin Tech) is a significant plus. An understanding of banking workflows and data is highly desirable.

Communication

Skills:

Exceptional ability to communicate complex technical concepts to non-technical stakeholders and to articulate a clear technical vision that aligns with business goals.

Technical SkillsAI / GenAI / Agentic PlatformsLLM & Agentic Frameworks:
Deep expertise in building production-grade agentic systems using GCP as primary (ADK, Vertex AI)
Multi-Agent Systems:
Hands-on experience designing and implementing multi-agent architectures (task decomposition, coordination, orchestration, and agent-to-agent (A2A) interaction patterns)
Model Context Protocol (MCP) & Integrations:
Experience integrating agents with enterprise tools and data sources using MCP or equivalent context-sharing patterns

Knowledge Graphs & Reasoning:
Building and leveraging knowledge graphs for context enrichment, reasoning, and workflow automation RAG & Knowledge Systems:
End-to-end RAG pipelines using enterprise search + vector stores (e.g., Elastic, Pinecone) with grounding, evaluation, and optimization

Model Lifecycle & Governance:
Model evaluation, monitoring, prompt/version control, and Responsible AI / MRM compliance

Enterprise AI Integration & DataAPI- and…