Teams at Mastercard

Leads Mastercard’s global AI Engineering organization, overseeing enterprise AI product delivery from design through production and adoption. Builds reusable AI assets, agentic AI solutions, orchestration patterns, and workflow automation while ensuring reliability, scalability, security, governance, compliance, and operational excellence. Partners across technology, product, risk, and business teams to deliver measurable outcomes. Develops engineering leaders and high-performing global teams in a regulated enterprise environment.

Leads major cross-department software initiatives from scoping through delivery, establishes technical roadmaps, evaluates technologies through proofs of concept, and guides strategic decisions. Oversees quality assurance, compliance, documentation, standards, and secure software delivery. Mentors teams, manages stakeholders and vendors, supports process improvement, and drives measurable productivity gains. Requires strong software engineering expertise, Java/Spring or Python coding, AWS, Databricks or Snowflake, and experience applying AI in software design.

Architect and lead enterprise AI infrastructure supporting LLM training and inference, machine learning, agentic AI, and production platforms. The role covers HPC, GPUs, rack-scale systems, private and hybrid cloud, Kubernetes, networking, storage, observability, security, reliability, governance, and automation. Responsibilities include solving complex scalability and performance challenges, defining engineering standards, evaluating emerging technologies, leading cross-functional initiatives, and mentoring engineers in a regulated environment.