Lead AI/DevOps Engineer

Mastercard•Arlington, VA

About The Position

Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. The LLM as a Service team is looking for a Lead AI/DevOps Engineer to drive our customer experience strategy forward by consistently innovating and problem-solving. The ideal candidate is passionate about the customer experience journey, highly motivated, intellectually curious, analytical, and possesses an entrepreneurial mindset.

Requirements

Proficient in DevOps tools such as Splunk, Dynatrace, Grafana, Prometheus, OpenShift Kubernetes, Docker, and Helm.
Strong hands-on experience with Python; GoLang is a plus.
Customer-focused mindset with a commitment to delivering simple, valuable solutions.
Driven by a clear mission to prioritize customer needs.
Continuously monitor market trends and competitors to inform strategy.
Proactively engage with customers to understand their challenges and identify impactful solutions.
Seek complementary products or services to enhance customer outcomes.
Identify resource gaps and propose sustainable, team-benefiting solutions.
Communicate technical concepts clearly and concisely.
Confident and precise communicator, capable of articulating vision and strategy to diverse stakeholders.
Solution-oriented approach to problem-solving.

Responsibilities

Lead DevOps initiatives in on-prem environments.
Design, deploy, and manage scalable AI infrastructure using Kubernetes for reliable orchestration of large language models and related services.
Develop proof-of-concept solutions for advanced AI use cases, including model context protocols (MCPs), LLMs, retrieval-augmented generation (RAG), and agentic workflows.
Partner with security and governance teams to ensure AI solutions comply with enterprise policies, regulatory standards, and privacy best practices.
Collaborate with infrastructure and platform teams to optimize cloud resources for scalable, efficient, and cost-effective AI workloads.
Work directly with customer teams to gather requirements, deliver innovative solutions, and provide ongoing technical support throughout the AI product lifecycle.

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

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