Cloud Engineering Leader for Generative AI Platforms

1 week ago

Tampa, Florida, United States MasterCard Full time

Company Overview

We connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible.

Salary Range: $198,000 - $317,000 USD (New York City), $165,000 - $264,000 USD (O'Fallon, Missouri)

Job Description:

The Mastercard Cloud Team, within the ONE division, drives cloud usage and adoption for the company. As a key member of this team, you will play a critical role in shaping the future of development, deployment, and more.

This cloud engineering position focuses on building a holistic platform for Generative AI Large Language Models (LLMs).

Key Responsibilities:

  • 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 partners, product owners, and stakeholders to create meaningful roadmaps to ensure prioritized work
  • Champion all Mastercard's 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

Required Skills and Qualifications:

To succeed in this role, you will need:

  • A deep understanding of cloud providers, especially AWS and Azure
  • Experience with AI and GenAI-related cloud services, such as AWS SageMaker, AWS Bedrock, Azure ML
  • Knowledge of common commercial Foundational Models from OpenAI, Anthropic, etc., and open-source LLM models deployed in the cloud
  • Familiarity with services, access controls, integration, and automation
  • GenAI LLM Platform Experience: model evaluation, API patterns, implementations, governance, retrieval augmented generation, orchestration, prompt libraries, agents, tools/functions, prompt/tuning, chunking methods, vector stores/DBs/embeddings, foundational LLM models, model hubs, fine-tuned models
  • Ai-related Data Platforms experience
  • GenAI Code Assistants and Developer Experience
  • Deep AI/ML experience with data science, data analytics
  • Solid understanding of cloud security in highly regulated market segments and countries
  • Solid experience with site reliability engineering mindset and creating solutions 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 ephemeral 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-experienced engineers through pair programming, code reviews, design reviews, etc.
  • Deep knowledge in migration from legacy technologies and mindset to 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 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 helps teams remove blockers and continuously improve code velocity, quality, and release frequency
  • Experienced with Python, Java, and other programming languages

Benefits:

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.

Corporate Security Responsibility:

All activities involving access to Mastercard assets, information, and networks come with inherent risk to the organization. Every person working for, or on behalf of, Mastercard is responsible for information security and must abide by Mastercard's security policies and practices, ensuring confidentiality and integrity of the information being accessed, reporting suspected information security violations or breaches, and completing periodic mandatory security trainings.

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