Principal Azure Gen AI Engineer

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Principal Azure Gen AI Engineer

*Overview*
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).

*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*
• Deep understanding of cloud providers Azure, especially:
o Experience with AI and GenAI-related cloud services, especially: Azure ML. This should include common commercial Foundational Models (FM) from OpenAI, Anthropic, etc, as well as open-source LLM models deployed in the cloud.
o Services, Access controls, Integration and Automation….etc.

• GenAI LLM Platform Experience:
o Model Evaluation
o Model API patterns and implementations
o Model Governance
o Retrieval Augmented Generation
o Orchestration
o Prompt Libraries
o Agents
o Tools/Functions
o Prompt/Tuning
o Chunking Methods
o Vector Stores/DBs/Embeddings
o Foundational LLM Models (commercial and open source)
o Model Hubs
o Fine-Tuned Models
• AI-related Data Platforms (i.e. DataBricks, IBM watsonx, or similar)
• GenAI Code Assistants and Developer Experience (i.e. GitHub Copilot, AWS Code Whisperer, etc.)
• Deep AI/ML experience with data science, data analytics, etc.
• Solid understandig of cloud security In highly regulated market segments and countries.
• Solid experience with site reliability engineering mindset and creating solutions that are resilient, supportable and observable at all layers of the stack
• Deep understanding of automation using various tools
• Deep understanding of observability In a cloud environment
• Proficient In web service design, standards, best practices and Implementation
• Deep understanding of containerization and designing ephemiral solutions
• Solid understanding of pure kubernetes and cloud provider based managed services kubernetes
• Proven track record of delivering solutions to complex, multi-domain environments
• Ability to articulate complex designs and solutions to people with varying levels of technical aptitude
• Experienced in guiding less experienceed engineers with the use of pair programming, code reviews, design reviews…etc.
• Deep knowledge in migration from legacy technologies and mindset to the best In class solutions for the cloud
• Self-Driven and able to navigate complex organizational environments
• Strong communication skills both written and verbal
• Strong understanding of different project management methodologies Including waterfall and Agile/Scrum
• Strong understanding of all phases of the SDLC process from design to deployment.
• Enthusiastically engages engineers across Technology organizations to promote standard software patterns and reuse of common libraries and services with experience leading open-source development efforts
• Champions performance engineering practices to ensure that performance meets (or exceeds) expectations; educates stakeholders on performance testing processes, methodology, performance and scalability metrics, capacity modeling techniques, and testing approaches
• Understands software development productivity metrics (e.g., code churn, commit size, commits/story) and help teams to remove blockers and continuously improve code velocity, quality, and release frequency
• Experienced with Python, Java, and other programming languages
#AI

Mastercard is an inclusive equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• Abide by Mastercard’s security policies and practices;

• Ensure the confidentiality and integrity of the information being accessed;

• Report any suspected information security violation or breach, and

• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary based on location, experience and other qualifications for the role and may be eligible for an annual bonus or commissions depending on the role. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance), flexible spending account and health savings account, paid leaves (including 16 weeks new parent leave, up to 20 paid days bereavement leave), 10 annual paid sick days, 10 or more annual paid vacation days based on level, 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, eligibility for tuition reimbursement, gender-inclusive benefits and many more.