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 Senior AI Engineer – Foundry R&D, Singapore 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. Senior AI Engineer – Foundry R&D, Singapore What you'll do - Develop backend services for AI features: Build and maintain backend components and APIs for generative AI use cases. Create scalable microservices in Java or Python to expose AI capabilities, handle requests, and integrate model outputs into applications. - Integrate generative AI technologies: Work with data science and ML teams to productionize models and connect them to the platform. Build service interfaces, manage data formats, integrate external APIs, and implement supporting data flows such as caching or context retrieval. - Ensure performance and reliability: Own service quality by writing tests, profiling performance, and resolving bottlenecks. Set up monitoring and alerts, improve logging, and diagnose production issues to ensure uptime and stability. - Collaborate cross‑functionally: Work in an agile team with product, design, and data science. Participate in design discussions, refine requirements, and iterate quickly based on feedback. Help shape technical decisions for AI‑powered features. - Mentor and uphold best practices: Guide junior engineers through code reviews and knowledge sharing. Promote clean coding, maintainability, testing discipline, and improvements to tools and processes. What you'll bring - Strong backend engineering experience: 5+ years building backend systems and APIs. Experience with Java (Spring Boot) or Python and familiarity with scalable, thread‑safe server‑side development. - AI engineering expertise: Practical experience integrating generative AI capabilities into backend systems. Comfortable working with LLM APIs (e.g. OpenAI, Anthropic), building RAG pipelines, working with vector databases and embeddings, and using agentic frameworks such as LangChain or LlamaIndex to orchestrate AI workflows. - API and database proficiency: Skilled in designing RESTful APIs, managing authentication, and structuring data. Strong SQL knowledge and experience with relational and NoSQL databases, caching, and data‑intensive flows. - Quality‑focused and detail‑oriented: Strong testing habits, including unit and integration tests. Familiar with error handling, logging, edge cases, and building resilient AI‑related services. - Problem‑solving and adaptability: Able to debug complex systems, isolate issues, and adapt quickly to evolving requirements in an R&D environment. - Collaboration and communication: Ability to work with technical and non‑technical teams, communicate requirements clearly, and contribute actively to design and planning. Required skills - Education and background: Bachelor's degree in Computer Science or related field. 5+ years of backend or full‑stack engineering in agile teams, with experience delivering complex products. - Back‑end programming mastery: Expertise in Java, Python, or Go, and related frameworks such as Spring Boot or FastAPI. Strong Git workflows, scripting skills, and understanding of concurrency or async development. - Web services and microservices: Experience building and consuming REST services and working in microservice architectures. Familiar with message queues, API gateways, and tools like Swagger or Postman. - Database and data management: Strong SQL and schema design skills, use of indexes, query optimization, and ORM familiarity. Experience with NoSQL or caching technologies for performance‑heavy applications. - Cloud and CI/CD: Experience deploying services on AWS, GCP, or Azure, using containers, serverless or orchestration tools, and CI/CD pipelines to automate builds, tests, and deployments. - AI services and frameworks: Working knowledge of generative AI concepts including LLMs, embeddings, vector search, and prompt engineering. Hands-on experience with AI APIs or SDKs (e.g. OpenAI, Anthropic) and familiarity with agentic orchestration tools such as LangChain or LlamaIndex. - Testing and monitoring: Experience wri