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 AI Engineer || Role Summary The AI Engineer is responsible for designing and delivering AI-powered solutions that improve engineering productivity and business workflows. This role requires a strong foundation in AI/ML concepts, with hands-on expertise in LLM systems, data preparation, and context design (including chunking) to build scalable, high-quality AI solutions. What You Will Do Lead AI-Driven Solution Development Identify and drive high-impact AI use cases across engineering and business workflows Design end-to-end AI solutions leveraging LLMs, orchestration, and automation Move rapidly from exploration to production-grade implementations Build LLM Solutions & Intelligent Agents Develop LLM-based applications including prompt frameworks, orchestration layers, and integrations Create and evolve AI-powered agents (e.g., Copilot-based or similar) for workflow automation and decision support Apply techniques such as retrieval-augmented approaches, context management, and prompt optimization Design Data, Context & Chunking Strategies (Critical) Structure and prepare data for LLM consumption, including effective chunking and context window optimization Design retrieval strategies that improve relevance, accuracy, and response quality Balance context size, latency, and cost while maintaining solution effectiveness Apply Strong AI/ML Foundations Understand and reason about model behavior, evaluation, bias, and limitations Tune and adapt prompts, context, and workflows instead of relying on model retraining Ensure responsible and effective use of AI through sound engineering practices Drive Engineering Productivity with AI Apply AI tools (e.g., Copilot and similar) to improve developer velocity and quality Build reusable patterns for AI-assisted coding, testing, and documentation Measure and scale productivity impact across teams Data & Application Engineering Build data pipelines and integrations to support AI workflows Develop APIs, services, and applications embedding AI capabilities Ensure solutions are scalable, maintainable, and integrated into real workflows What You Bring Strong foundation in AI/ML concepts, especially LLMs and modern AI systems Hands-on experience with: Prompt engineering and LLM orchestration frameworks Context design, chunking strategies, and retrieval techniques Working with structured and unstructured data for AI use cases Solid software engineering and system design experience Ability to build end-to-end AI solutions (data → context → LLM → application) Pragmatic mindset focused on quality, usability, and business impact Mastercard is a merit-based, 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. We hire the most qualified candidate for the role. 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 Accommo