Director, Applied AI & Agentic Platform Engineering - Citi - #2130559

Discover your future at Citi
Working at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you'll have the opportunity to grow your career, give back to your community and make a real impact.

Job Overview
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 Roadmapping: 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, LangChain,), 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.

• 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, FinTech) 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.

• AI / GenAI / Agentic Platforms
  • LLM & 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

• • 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 & Data
  • API- and event-driven integration of AI into enterprise workflows
  • Data platforms: Databricks, Spark, Snowflake; streaming via Kafka
• Backend & Distributed Systems
  • Languages: Python (expert), Java/Spring Boot (enterprise standard), Go (plus)
  • Architecture: Microservices, domain-driven design, event-driven systems
  • APIs & Integration: REST/gRPC; Apigee, Kong
  • Data & Messaging: PostgreSQL/Oracle, MongoDB/Cassandra, Kafka
• Cloud & DevSecOps
  • Cloud Platforms: Strong experience with GCP (preferred); working knowledge of AWS; Azure exposure optional (not a dependency)
  • Containers: Docker, Kubernetes (GKE/EKS)
  • IaC: Terraform
  • CI/CD: GitHub Actions, Jenkins
  • Observability: Splunk, ELK, Prometheus, Grafana
• Security & Compliance
  • Secure coding, API security, Zero Trust
  • Data privacy, encryption, access control
  • Regulatory compliance and AI governance (MRM)