Director of AI Infrastructure Engineering

Employment Type: [Not Specified] Location Type: Remote (United States) or Oakland, CA Headquarters Salary: [Not Specified]

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.

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

• Build and Lead Team: Build and lead an AI Infrastructure Engineering team, establishing team culture, processes, and technical standards while recruiting top-tier talent to execute on our AI infrastructure roadmap.
• Develop Technical Vision: Develop a comprehensive technical vision for generative AI infrastructure that enables seamless integration of AI-powered developer tools, business productivity applications, and agentic solutions across engineering workflows and business operations while maintaining security and compliance standards.
• Own and Operate Platforms: 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 that accelerate AI adoption across technical and non-technical teams.
• Establish Operational Excellence: Establish generative AI operational excellence including prompt engineering standards, cost optimization strategies, and performance monitoring capabilities that ensure responsible and efficient AI deployment at scale.
• Build Agentic Solutions: Build and deploy agentic AI solutions and automation including custom AI agents, workflow automations, and internal MCP servers that enhance productivity and enable sophisticated AI-driven business processes.
• Partner with Data+ML: 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.
• Create Roadmaps: Create strategic roadmaps and delivery frameworks including OKRs, project structures, and milestone tracking to guide AI infrastructure initiatives and align stakeholders across the organization.
• Manage Costs and Performance: Manage AI infrastructure costs and performance by implementing monitoring, attribution, and optimization mechanisms that ensure efficient resource utilization and demonstrate clear ROI on AI investments.
• Build Partnerships: Build vendor and technology partnerships for AI infrastructure components, evaluating emerging AI technologies, managing integrations, and establishing strategic relationships that accelerate our AI capabilities.
• Mentor and Develop: Mentor and develop team members on AI engineering best practices, infrastructure design patterns, and career growth while fostering a culture of innovation and continuous learning.
• Establish Metrics: Establish metrics and KPIs to measure AI platform adoption, performance, and business impact while communicating progress and outcomes to executive leadership.

Who You Are

• Experience: 8+ years of experience in platform engineering and infrastructure leadership roles with demonstrated expertise in building and scaling generative AI platforms, developer productivity tools, and AI-powered applications.