Director, Software Engineering - AI Infrastructure

Summary

Join Marqeta as the Director of AI Infrastructure Engineering and lead a new team in building and scaling generative AI platforms. You will architect and implement foundational AI infrastructure using services like AWS Bedrock and Amazon Q, while developing agentic AI solutions. Collaborate with engineering, product, and business leaders to define and execute a comprehensive generative AI infrastructure strategy. This role reports to the SVP of Infrastructure Engineering and requires establishing a generative AI infrastructure strategy and technical vision to support enterprise-wide AI adoption. The position offers flexibility to work remotely within the United States or from the Oakland, CA headquarters. You will be responsible for building and leading a team, developing a technical vision, and managing AI infrastructure costs and performance.

Requirements

• 8+ years experience in platform engineering and infrastructure leadership roles with demonstrated expertise in building and scaling generative AI platforms, developer productivity tools, and enterprise AI enablement solutions
• 2+ years hands-on experience with generative AI platforms and services including AWS Bedrock, Amazon Q, OpenAI APIs, and similar enterprise AI services, with proven track record of production deployments and user adoption
• Proven track record of building teams from zero to one with experience recruiting, hiring, and developing high-performing engineering teams while establishing technical vision and execution standards
• Deep expertise in cloud ML platforms and services with strong preference for AWS (Bedrock, EKS, EC2) and experience with Google Workspace, along with proficiency in Kubernetes, Infrastructure as Code, MLOps CI/CD pipelines, and ML observability tools
• Excellent leadership and communication skills with ability to influence senior stakeholders, build cross-functional partnerships, and translate complex technical concepts into business value
• Platform ownership mindset with proven experience taking end-to-end responsibility for generative AI platform reliability, performance, and user experience while building self-service capabilities for developers and business users
• Strong bias toward action and innovation with ability to operate effectively in ambiguous, fast-paced environments while maintaining high standards for quality and reliability
• High ethical standards and commitment to responsible AI with understanding of AI ethics, bias mitigation, and responsible deployment practices

Responsibilities

• 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 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 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 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 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 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 strategic roadmaps and delivery frameworks including OKRs, project structures, and milestone tracking to guide AI infrastructure initiatives and align stakeholders across the organization
• 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 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 team members on AI engineering best practices, infrastructure design patterns, and career growth while fostering a culture of innovation and continuous learning
• Establish metrics and KPIs to measure AI platform adoption, performance, and business impact while communicating progress and outcomes to executive leadership

Preferred Qualifications

• Background in fintech or regulated industries preferred, with strong understanding of security, compliance, and governance requirements for AI systems handling sensitive financial data
• Experience with AI productivity tools and developer enablement such as AI-powered code generation, automated documentation, intelligent testing tools, and workflow optimization platforms
• BS/MS degree in Computer Science, Engineering, or related technical field preferred

Benefits

• Multiple health insurance options
• Flexible time off – take what you need
• Retirement savings program with company contribution and after tax contributions
• Equity in a publicly-traded company and an Employee Stock Purchase Program
• Family-forming benefits, fertility support, and up to 20 weeks of Parental Leave
• Free therapy sessions, financial and professional coaching, and legal advice
• Monthly stipend to support our remote work model
• Annual “development dollars” to support our people growth and development