Lead AI Engineer

Mastercard Inc.; O’Fallon (MO); On-site; USD 140,000 - 277,000; Full time

Benefits offered by this job

Insurance (medical, dental, vision)

Paid time off

401k with company match

Tuition reimbursement

On-site fitness facilities

Job summary

Mastercard Inc. is seeking an experienced AI platform engineer to design and operate enterprise MCP deployment components, including a security gateway, MCP registry, and reference server implementations.

You will drive implementations from design to production, implement identity and access controls, and ensure secure, auditable data and tools across the MCP estate while building open weight model serving and reproducible evaluation tooling.

Qualifications

• Strong knowledge of modern AI tech including LLMs and enterprise tooling.
• Production-grade software engineering practices and reliable services.
• MLOps experience covering CI/CD, IaC, containers, observability, and monitoring.
• Cloud platforms (AWS preferred; Azure/GCP valuable) and Databricks.
• Model evaluation with reproducible results (quality, cost, latency, safety).
• Hands-on open weight model operations with self-hosted inference.
• API security and access control for MCP authentication/authorization.
• Governance concepts: provenance, licensing, data sovereignty, finance regs.
• Strong communication and collaboration with engineers and security partners.
• Self-motivated, able to work with minimal hand-holding.

Responsibilities

• Design and build MCP deployment components, including a security gateway and MCP registry.
• Drive implementations from design to running production services.
• Implement identity, auth, and authorization patterns for MCP across the estate.
• Ensure agent, tool, and data access is secure and auditable end to end.
• Define MCP server standards for exposure, discovery, versioning, and controls.
• Build and operate open weight model serving with self-hosted inference and packaging.
• Create evaluation tooling benchmarking models for quality, cost, latency, and safety.
• Apply MLOps: CI/CD, IaC, observability, and monitoring for models and services.
• Partner with security, privacy, legal, AI governance teams, and MCP groups.
• Stay current with MCP developments and decide on adoption.

Skills

AI knowledge

Software engineering

MLOps

Model evaluation

Open weight ops

API security

Governance

Communication

Learning agility

Self-starter

Tools

OAuth

Databricks

AWS

Azure

GCP

CI/CD

IaC

Containers

Observability

Self-hosted inference

Job description

Join Mastercard to help build and operate enterprise AI platform capabilities for secure adoption of MCP and open weight models.

Responsibilities

• Design and build enterprise MCP deployment components, including a security gateway, an MCP registry (governing what exists and ownership), and reference server implementations used by other teams
• Drive implementations from design through to running production services
• Implement identity, authentication, and authorization patterns for MCP across the estate with senior engineering support and central security and identity teams
• Ensure agent, tool, and data access is secure and auditable end to end
• Help define internal and external MCP server standards for tool and data exposure, discovery and versioning, plus gateway-enforced controls such as inspection, data-protection, rate limiting, and a kill switch
• Build and operate open weight model serving, including self-hosted inference, model packaging for deployment, and enabling workload switching across models and providers for cost, flexibility, and resilience
• Create evaluation and testing tooling that benchmarks candidate open weight models for quality, cost, latency, and safety, producing reproducible evidence for governance and security reviews
• Apply MLOps practices for production reliability, including CI/CD, infrastructure-as-code, observability, and monitoring for models and services
• Partner with central security, privacy, legal, and AI governance teams, plus the MCP SIG and OW working group, to implement required platform architecture expectations
• Stay current with a fast-moving landscape (new MCP developments, frontier open weight releases, and related agentic protocols) and help decide what to adopt, prototype, or hold

Requirements

• Strong knowledge of modern AI technology, including LLMs, foundation models, agents, and enterprise connectivity tooling and protocols (such as MCP)
• Production-grade software engineering: write well-tested code and build services others can rely on (not one-off scripts)
• Solid MLOps experience covering CI/CD, infrastructure-as-code, containers, observability, and monitoring for models and services in production
• Cloud platform knowledge (AWS preferred; Azure or GCP valuable); familiarity with a modern data/AI platform such as Databricks is a bonus
• Practical model evaluation experience, including building benchmarks and tests for quality, cost, latency, and safety with reproducible results
• Hands-on open weight model operations: serving or operating self-hosted inference and scaling; ideally some experience fine-tuning or adapting to proprietary data and workflows
• API security and access control knowledge to implement MCP authentication and authorization and collaborate effectively with security teams
• Awareness of enterprise AI governance drivers such as model provenance and licensing, data sovereignty, and financial-services regulation
• Strong communication and collaboration with senior engineers, hands-on peers, and specialist governance and security partners
• Demonstrated curiosity and learning agility beyond a single function
• Self-starter who can deliver without extensive hand-holding once direction is clear

Technologies

• Model Context Protocol (MCP)
• open weight models
• OAuth
• LLMs, foundation models, agents
• CI/CD
• infrastructure-as-code
• containers
• observability
• AWS, Azure, GCP
• Databricks
• self-hosted inference
• API security
• identity and access control

Benefits

• Insurance (including medical, prescription drug, dental, vision, disability, life insurance)
• Flexible spending account and health savings account
• Paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave)
• 80 hours of Paid Sick and Safe Time
• 25 days of vacation time and 5 personal days (pro-rated based on date of hire)
• 10 annual paid U.S. observed holidays
• 401k with a best-in-class company match
• Deferred compensation for eligible roles
• Fitness reimbursement or on-site fitness facilities
• Eligibility for tuition reimbursement
• Many more
• 56 hours of Paid Sick and Safe Time (interns generally)
• Jury duty leave (interns generally)
• On-site fitness facilities in some locations (interns generally)

Corporate Security Responsibility

• Abide by Mastercard’s security policies and practices
• Ensure confidentiality and integrity of the information being accessed
• Report suspected information security violation or breach
• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines

Location: O'Fallon, MO (onsite)

Compensation: USD 140,000 - 277,000 per year