Senior Software Engineer
Posted Updated
- The Program Modernization team at MasterCard drives transformation and champions modernization across technology, risk, and service operations. We establish the foundation for scalable programs, resilient systems and control governance that empowers transformation
- The mission of the Technology Modernization team is to enable all the Mastercard programs across the organization to thrive in an evolving regulatory environment by fostering a culture of strong technology controls and effective execution
- The team designs and delivers innovative, data-driven solutions that fulfill assurance obligations and regulatory requirements by proactively identifying risks, build real-time tools that leverage technology to continuously test and monitor the control environment
- These capabilities enables audit-ready compliance portal for inventorying, managing, testing, and evidencing technology controls
- Mastercard is committed to driving innovation through advanced technologies and data-driven insights. We are seeking a Senior Engineer to design and deliver scalable, enterprise-grade AI solutions that enhance our digital capabilities and customer experiences
- This role will focus on building intelligent, production-ready systems leveraging large language models (LLMs), knowledge bases with vector search, and modern cloud/data platforms, while ensuring alignment with Mastercard’s standards for security, performance, and reliability
- Design, develop, and deliver AI-powered solutions leveraging modern architectures, including LLM-based systems and retrieval-augmented generation (RAG)
- Build and maintain enterprise knowledge bases with vector search capabilities, enabling semantic search and intelligent information retrieval
- Develop LLM-driven applications using frameworks such as LangChain, including prompt engineering, chaining, and orchestration patterns
- Implement and integrate solutions leveraging Model Context Protocols (MCP) or equivalent model interaction frameworks
- Architect scalable and secure solutions across cloud and data ecosystems, including AWS, Cloudera, and Databricks
- Collaborate cross-functionally with product, engineering, and data teams to translate business needs into AI-enabled solutions
- Develop and maintain robust APIs and microservices to support AI applications and front-end integrations
- Ensure solutions adhere to Mastercard’s standards for data governance, security, compliance, and operational excellence
- Monitor and optimize model performance, reliability, and scalability in production environments
- Contribute to technical design discussions, mentor junior engineers, and promote engineering best practices
- Ability to operate effectively in a collaborative, fast-paced environment
- Demonstrated ownership and accountability for end-to-end delivery
- Solid understanding of system design, APIs, and microservices architecture
- Experience with Angular or similar frontend frameworks for building user-facing AI applications
- Expertise in designing knowledge bases with vector search and working with embedding models
- Excellent communication and stakeholder engagement skills
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related discipline
- Hands-on experience with LLM frameworks (e.g., LangChain) and building RAG-based systems
- Strong problem-solving and analytical thinking
- Strong proficiency in Python, with experience building scalable backend systems
- Strong experience with cloud platforms, particularly AWS, and familiarity with Cloudera and Databricks ecosystems
- Proven experience (8–12 years) in software engineering, with strong focus on AI/ML and distributed systems
- Commitment to continuous learning and staying current with emerging AI technologies
- Familiarity with MLOps practices, including CI/CD pipelines, monitoring, and lifecycle management
- Experience with Model Context Protocol (MCP) or similar AI orchestration frameworks
- Experience with vector databases such as PGVector, GraphDB
- Knowledge of containerization and orchestration (Docker, Kubernetes)
- Experience working in highly regulated, large-scale enterprise environments