Lead AI Engineer

Mastercard

. Design and build platform capabilities for Mastercard’s enterprise MCP deployment and open weight AI models .

Posted 11/9/2026full-timeUnited StatesSenior💰 $140,000 - $277,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and operating enterprise-level AI models and platforms, with a strong focus on MLOps practices, cloud technologies, and security protocols. Proficient in model evaluation and benchmarking, ensuring quality and performance in production environments.

Highest-signal resume keywords

MLOps ExperienceCI/CD ImplementationCloud Platform KnowledgeModel EvaluationAPI Security

ATS Keywords

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Hard Skills

Production-Quality CodeModel BenchmarkingInfrastructure-As-CodeOpen Weight Model ServingIdentity And Access ControlData ProtectionRate LimitingModel PackagingSelf-Hosted InferenceMonitoring Practices

Soft Skills

Clear CommunicationCollaboration SkillsLearning AgilityCuriosityIndependent Work

Tools & Technologies

AWSAzureGCPDatabricksContainersObservability ToolsMCPAI Governance

Industry Keywords

Financial-Services RegulationData SovereigntyModel ProvenanceAI TechnologyFoundation Models

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformSwitching

About the role

Key responsibilities & impact

Design and build platform capabilities for Mastercard’s enterprise MCP deployment and open weight AI models
Build components such as the security gateway, MCP registry, and reference server implementations through production operation
Implement identity, authentication, and authorization patterns for MCP across the estate
Establish standards for internal and external MCP servers, including discovery, versioning, inspection, data protection, rate limiting, and kill-switch controls
Build and operate open weight model serving, including self-hosted inference, model packaging, and workload switching across models and providers
Build evaluation and testing tooling to benchmark models for quality, cost, latency, and safety
Apply CI/CD, infrastructure-as-code, observability, and model and service monitoring practices
Partner with security, privacy, legal, AI governance, MCP SIG, and open weight working group stakeholders
Monitor developments in MCP, open weight models, and related agentic protocols and help determine adoption priorities

Requirements

What you’ll need

Strong knowledge of modern AI technology, including LLMs, foundation models, agents, and tooling and protocols such as MCP
Good software engineering skills and ability to write production-quality, well-tested code
Solid MLOps experience with CI/CD, infrastructure-as-code, containers, observability, and monitoring for models and services in production
Good cloud platform knowledge; AWS preferred, with Azure or GCP valuable
Familiarity with a modern data/AI platform such as Databricks is a bonus
Practical experience with model evaluation, including benchmarks and tests measuring quality, cost, latency, and safety
Hands-on experience serving or operating open weight models, self-hosting, and scaling inference
Ideally, experience with fine-tuning or adapting models to proprietary data and workflows
Working knowledge of API security, identity, and access control
Awareness of model provenance and licensing, data sovereignty, and financial-services regulation
Clear communication and collaboration skills
Intense curiosity and demonstrated learning agility
Ability to work independently once given guidance and direction

Benefits

Comp & perks

Insurance including medical, prescription drug, dental, vision, disability, and life insurance
Flexible spending account and health savings account
16 weeks of new parent leave
Up to 20 days of bereavement leave
80 hours of Paid Sick and Safe Time
25 days of vacation time
5 personal days
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
Tuition reimbursement eligibility