Director of AI Infrastructure Engineering

Position Overview

As the Director of AI Infrastructure Engineering within our Infrastructure Engineering organization, you will build, lead, and scale a new team towards our bold AI transformation vision. This role is uniquely focused on establishing generative AI platforms and enablement capabilities that will accelerate AI productivity across both engineering and non-engineering functions. You will architect and implement foundational AI infrastructure powered by services like AWS Bedrock, Amazon Q Developer, and Amazon Q for Business, while building targeted agentic AI solutions and internal MCP (Model Context Protocol) servers.

Working closely with engineering, product, business leaders, and our Data+ML organization, you will define and execute a comprehensive generative AI infrastructure strategy that positions Marqeta at the forefront of AI-driven innovation in fintech.

This role will report directly to the SVP of Infrastructure Engineering and will define a generative AI infrastructure strategy and technical vision to support Marqeta's enterprise-wide AI adoption, with particular emphasis on building scalable, secure, and cost-effective generative AI platforms and agentic solutions that serve diverse organizational needs.

Work Environment

We work Flexible First. This role can be performed remote within the United States or from our Oakland, CA headquarters. We'd love for you to join us!

The Impact You'll Have

• Team Leadership & Development:
  • Build and lead an AI Infrastructure Engineering team, establishing team culture, processes, and technical standards.
  • Recruit top-tier talent to execute on our AI infrastructure roadmap.
  • Mentor and develop team members on AI engineering best practices, infrastructure design patterns, and career growth.
  • Foster a culture of innovation and continuous learning.
• AI Infrastructure Strategy & Vision:
  • Develop a comprehensive technical vision for generative AI infrastructure.
  • Enable seamless integration of AI-powered developer tools, business productivity applications, and agentic solutions across engineering workflows and business operations.
  • Maintain security and compliance standards.
• Platform Ownership & Operations:
  • Own and operate comprehensive generative AI platforms including AWS Bedrock integrations, Amazon Q Developer and Q for Business deployments, custom agentic AI solutions, and internal MCP servers.
  • Accelerate AI adoption across technical and non-technical teams.
  • Establish generative AI operational excellence including prompt engineering standards, cost optimization strategies, and performance monitoring capabilities.
  • Ensure responsible and efficient AI deployment at scale.
• Agentic AI Solutions & Automation:
  • Build and deploy agentic AI solutions and automation including custom AI agents, workflow automations, and internal MCP servers.
  • Enhance productivity and enable sophisticated AI-driven business processes.
• Cross-Functional Collaboration:
  • Partner closely with the Data+ML organization to ensure complementary AI strategies, shared infrastructure components, and seamless integration between generative AI tools and traditional ML capabilities.
• Roadmap & Delivery:
  • Create strategic roadmaps and delivery frameworks including OKRs, project structures, and milestone tracking.
  • Guide AI infrastructure initiatives and align stakeholders across the organization.
• Cost & Performance Management:
  • Manage AI infrastructure costs and performance by implementing monitoring, attribution, and optimization mechanisms.
  • Ensure efficient resource utilization and demonstrate clear ROI on AI investments.
• Vendor & Technology Partnerships:
  • Build vendor and technology partnerships for AI infrastructure components.
  • Evaluate emerging AI technologies and manage integrations.
  • Establish strategic relationships that accelerate our AI capabilities.
• Metrics & Reporting:
  • Establish metrics and KPIs to measure AI platform adoption, performance, and business impact.
  • Communicate progress and outcomes to executive leadership.

Who You Are

• Experience: 8+ years of experience in platform engineering and infrastructure leadership roles.
• AI Expertise: Demonstrated expertise in building and scaling generative AI platforms, developer productivity tools, and enterprise AI enablement.