Director, Agentic Engineering

Fifth Third BankFarmington Hills, MI
Hybrid

About The Position

Fifth Third is establishing a new Agentic Engineering team within Technology. This team will focus on building autonomous agents, multi-agent architectures, and the platform capabilities necessary for their safe, observable, and production-ready deployment within a regulated financial institution. The Director of Agentic Engineering will be responsible for building and leading this team from its inception, while also maintaining a hands-on role in architecture and code. This player-coach position involves leading a team of engineers, designing, and delivering agent systems in production. The scope of work includes agentic platform engineering, safety and governance, developer experience, and collaboration with executive stakeholders. The Director will define the technical vision for autonomous agents at the bank, encompassing approved architectural patterns, guardrail enforcement, and the APIs, SDKs, and tooling that facilitate secure and efficient AI solution development by other teams.

Requirements

  • Experience leading highly technical engineering teams responsible for production systems at enterprise scale.
  • Hands-on experience building with AI agent frameworks (e.g., LangChain, LangGraph, Deep Agents) and deploying agentic systems to production.
  • Direct experience building and deploying MCP servers and tool-use integrations.
  • Strong background in cloud architecture and system design on AWS (Bedrock, Lambda, Fargate, IAM, networking).
  • Production coding proficiency across multiple languages (Python, TypeScript/Node.js preferred).
  • Extensive experience in automation, infrastructure-as-code (Terraform), and platform engineering.
  • Proven track record delivering world-class AI-based architecture aligned with successful business outcomes.
  • Background in security, enterprise architecture, or systems engineering sufficient to partner credibly with risk and compliance teams.
  • Experience working in banking, financial services, or another regulated industry.
  • Ability to operate as a player-coach — setting technical direction, reviewing code, and developing people simultaneously.
  • Strong product judgment and the ability to separate high-value agent applications from novelty.
  • Clear communication style, especially when translating between business, engineering, and risk stakeholders.
  • Bachelor's degree in Computer Science, Information Systems, or equivalent combination of education and experience.
  • Demonstrated expertise in LLM integration, AI/ML systems, and agentic architecture patterns.
  • 10+ years of progressive experience in software engineering, cloud architecture, DevOps/SRE, or platform engineering.
  • At least 5 years in a hands-on engineering leadership role with direct reports.
  • Production experience designing and operating distributed systems on AWS.
  • Demonstrated ability to write production-quality code while leading teams.
  • Strong understanding of cloud security, identity/access control, and enterprise governance patterns.
  • Must be able to communicate ideas clearly — both verbally and in writing — to engineering, business, and executive stakeholders.

Nice To Haves

  • Experience with agent-to-agent (A2A) communication patterns and multi-agent coordination.
  • Background in developer experience, internal platform engineering, or API/SDK design.
  • Experience with agent evaluation frameworks, LLM observability tooling, and production debugging of non-deterministic systems.
  • Understanding of enterprise AI risk, model governance, and responsible AI practices in regulated environments.
  • Published work, internal or external, on agent architecture, orchestration patterns, or enforcement systems.
  • Familiarity with React for agent UI delivery channels.
  • Industry-relevant certifications such as AWS Certified Generative AI Developer – Professional, AWS Certified Solutions Architect – Professional, GitHub Certified: Agentic AI Developer, or Google Cloud Professional Machine Learning Engineer.

Responsibilities

  • Design and build autonomous agent and multi-agent systems for high-value bank workflows.
  • Define and implement tool-use patterns, agent orchestration, and Model Context Protocol (MCP) integrations.
  • Write and review production code in critical system components.
  • Establish approved architectural patterns for agentic development.
  • Own the guardrail enforcement layer for agentic systems.
  • Partner with risk, compliance, legal, and information security.
  • Build evaluation, observability, and debugging capabilities.
  • Define agent governance standards.
  • Build and maintain APIs, SDKs, and developer tooling.
  • Define and secure approved patterns and reference architectures.
  • Create reusable frameworks, templates, and playbooks.
  • Recruit, hire, and build the Agentic Engineering teams.
  • Mentor and coach engineers across career levels.
  • Partner with senior business and technology leaders to identify where autonomous agents can deliver measurable business impact.
  • Establish delivery patterns for safe experimentation, piloting, production release, measurement, and ongoing support.
  • Maintain a practical view of emerging AI capabilities and their responsible application.

Benefits

  • Comprehensive benefits
  • Differentiated compensation offerings
  • Incentive compensation plan
  • Extensive benefits programs designed to support the individual needs of our employees and their families, encompassing physical, financial, emotional and social well-being.
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