Lead AI Software Engineer- AI Enablement

Lead AI Software Engineer- AI Enablement

The Mastercard Cloud Team, in Mastercard's ONE division, owns and drives cloud usage and adoption for the company. The team has a unique opportunity to drive cloud patterns, standards, and best practices across all of Mastercard and their M&A's. The cloud team has a unique opportunity to be at the forefront of an evolving landscape of technology at Mastercard and help shape the future of development, deployment and more!

This cloud engineering role is focused on building a holistic platform for Generative AI Large Language Models (LLMs).

The Role:

• Design, configure, and implement a Gen. AI platform, including MLOps/LLMOps for Gen. AI LLMs, both commercial and open source
• Ensure alignment to appropriate patterns and standards for cloud integration and automation
• Identify opportunities for reuse and Improved efficiency
• Engage with IT and Business parters, product owners and stakeholders to create meaningful roadmaps to ensure the most Important work Is prioritized
• Champion all Mastercards engineering principles
• Actively participate as a member of the Software Engineering Guild sharing your knowledge, best practices, ideas, and passion for technology
• Help Identify and drive meaningful behavior changing metrics

All About You:

• Years of professional lead software engineering experience is required with deep expertise in AWS and Azure, including AI/GenAI services (SageMaker, Bedrock, AgentCore Azure ML, Microsoft Foundry) and commercial/open source foundation models.
• Strong cloud architecture skills: services, access controls, automation, integrations, and security in regulated environments.
• Solid understanding of MCP protocol, and deployment of MCP servers at scale
• Solid understanding of AI Agents, and deployment of agents at scale, managing context window size, security controls, A2A protocol.
• Extensive GenAI/LLM experience: model evaluation, governance, tuning, API patterns, orchestration, agents, RAG, prompt engineering, chunking, embeddings, vector stores, model hubs, and fine tuned/open source models.
• Experience with AI/data platforms (Databricks, Iceberg, S3, watsonx, or similar) and GenAI developer tools (GitHub Copilot, Amazon Q, Claude).
• Solid background in AI/ML, data science, and analytics.
• Strong SRE mindset with experience building resilient, observable, automated cloud solutions.
• Proficient in web service design, containerization, ephemeral architectures, and Kubernetes (native and managed).
• Proven ability to deliver solutions in complex multi domain environments and clearly communicate technical concepts.
• Experience mentoring engineers through pairing, code reviews, and design reviews.
• Skilled in cloud native modernization and migration from legacy systems.
• Effective in navigating large organizations; strong written and verbal communication.
• Deep understanding of Agile/Scrum, Waterfall, and full SDLC processes.
• Advocates for standard software patterns, reuse of common libraries, open source contribution, and strong performance engineering practices.
• Familiar with development productivity metrics and methods to improve velocity, quality, and release frequency.
• Proficient in CDK, Bicep, and Terraform
• Confident in public speaking, presentation, and ability to articulate complex topic to wide audience.