Principal AI Engineer
Salary not listed • Gurgaon, India • Full-time
Posted 10d ago
About the job
AI Solutions, part of Mastercard’s AI & Data organization, scales AI across the enterprise, moving use cases beyond pilots into trusted, production-grade capabilities embedded in Mastercard’s platforms and products. Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. You will be joining a team of AI and data engineers working on innovative AI and ML fraud solutions. Our innovative cross-channel AI solutions are applied in Fortune 500 companies in industries such as fin-tech and payments processing. We are pursuing a highly motivated individual with strong problem-solving skills to take on the challenge of structuring and engineering data and cutting-edge AI model evaluation and reporting processes. This role will be reporting to the VP of AI Engineering for AI Solutions.
Responsibilities
- Lead the architecture, design, and implementation of enterprise AI and agentic systems, ensuring scalability, reliability, and security.
- Build and manage AI-ready data products, retrieval pipelines, vector data stores, and knowledge systems that power AI solutions.
- Develop and standardize agent engineering capabilities, including orchestration, tool integration, memory management, and multi-agent workflows.
- Establish AI observability, evaluation, and AgenticOps practices, including tracing, monitoring, and performance measurement of AI systems.
- Partner with Data Science, Data Engineering, and Product teams to accelerate the delivery and operationalization of AI solutions across the enterprise.
Requirements
- Deep expertise in Data Engineering, AI Engineering, or Machine Learning platforms, with a proven track record of delivering production-grade AI solutions at scale.
- Strong understanding of modern AI architectures, including retrieval-augmented generation (RAG), vector databases, agent frameworks, orchestration patterns, and LLM-powered applications.
- Experienced in designing and building scalable data pipelines, data products, APIs, and distributed systems that support AI and analytics workloads.
- Demonstrated technical leadership with the ability to influence architecture decisions, mentor engineers, and drive the adoption of engineering best practices across teams.
- Passionate about solving complex business problems through innovation, with a pragmatic approach to balancing speed, quality, security, and operational excellence.
- Proven ability to translate emerging AI capabilities into enterprise-scale platforms, reusable services, and measurable business outcomes.
- Undergraduate degree in CS, or a STEM related field.
- Prior experience in payment fraud detection modeling.
- PhD/Master’s in CS, Data Science, Machine Learning, AI or a related STEM field (nice to have).
- Experience in data engineering and model building in PySpark using Spark ML on petabyte scale data (nice to have).
- Understands and implements methods to evaluate own work and others for bias, inaccuracy, and error (nice to have).
- Enjoys working with error-prone, messy, disparate, unstructured data (nice to have).