Director, Applied Artificial Intelligence & Agentic Platform Engineering

CitiIrving, TX
$170,000 - $300,000Onsite

About The Position

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 lead a world-class engineering team 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.

Requirements

  • Bachelor's or Master’s degree in Computer Science, Engineering, or a related technical field.
  • 12+ years of experience in software engineering, with at least 4+ years in a leadership role, leading high-performing engineering teams.
  • Proven experience as a "player-coach" who can lead from the front, contribute to the codebase, and mentor junior and senior engineers.
  • A strong track record of designing, building, and launching scalable, distributed, cloud-native platforms from the ground up.
  • 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.
  • Exceptional ability to communicate complex technical concepts to non-technical stakeholders and to articulate a clear technical vision that aligns with business goals.
  • Deep expertise in building production-grade agentic systems using GCP as primary (ADK, Vertex AI)
  • Hands-on experience designing and implementing multi-agent architectures (task decomposition, coordination, orchestration, and agent-to-agent (A2A) interaction patterns)
  • Experience integrating agents with enterprise tools and data sources using MCP or equivalent context-sharing patterns
  • Building and leveraging knowledge graphs for context enrichment, reasoning, and workflow automation
  • End-to-end RAG pipelines using enterprise search + vector stores (e.g., Elastic, Pinecone) with grounding, evaluation, and optimization
  • Model evaluation, monitoring, prompt/version control, and Responsible AI / MRM compliance
  • API- and event-driven integration of AI into enterprise workflows
  • Databricks, Spark, Snowflake; streaming via Kafka
  • Python (expert), Java/Spring Boot (enterprise standard), Go (plus)
  • Microservices, domain-driven design, event-driven systems
  • REST/gRPC; Apigee, Kong
  • PostgreSQL/Oracle, MongoDB/Cassandra, Kafka
  • Strong experience with GCP (preferred); working knowledge of AWS; Azure exposure optional (not a dependency)
  • Docker, Kubernetes (GKE/EKS)
  • Terraform
  • GitHub Actions, Jenkins
  • Splunk, ELK, Prometheus, Grafana
  • Secure coding, API security, Zero Trust
  • Data privacy, encryption, access control
  • Regulatory compliance and AI governance (MRM)

Nice To Haves

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

Responsibilities

  • Lead the design, architecture, and hands-on development of a scalable, secure, and resilient agentic AI platform from concept to production.
  • 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.
  • Recruit, hire, and mentor a high-performing, agile team of software and machine learning engineers. Foster a culture of innovation, excellence, and accountability.
  • 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.
  • Partner effectively with horizontal AI platform teams, enterprise architecture, and external vendor partners to leverage existing capabilities, influence roadmaps, and accelerate delivery.
  • 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.
  • Implement and champion best-in-class engineering practices, including CI/CD, automated testing, infrastructure-as-code, and robust monitoring to ensure enterprise-grade reliability.
  • 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.
  • Ensure the platform adheres to the highest standards of data privacy, security, and regulatory compliance required in the banking industry.

Benefits

  • competitive compensation package including salary, bonus, and benefits
  • medical, dental & vision coverage
  • 401(k)
  • life, accident, and disability insurance
  • wellness programs
  • paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays
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