Mastercard is looking to transform Proof of Concept (PoC) notebooks into robust, production-ready AI microservices for their agentic use cases, ensuring scalability, efficiency, and seamless integration into their existing ecosystem.
Requirements
- Strong proficiency in Python.
- Extensive experience designing, developing, and deploying RESTful APIs and microservices.
- Proven experience scaling machine learning models from prototype to production, including familiarity with feature stores, model registries, and inference patterns.
- Solid understanding of the AI/ML lifecycle, from data preparation and model training to deployment and monitoring.
- Experience with cloud platforms and their relevant compute, storage, and AI/ML services.
- Proficiency with containerization technologies.
- Familiarity with CI/CD pipelines for automated testing and deployment of software and AI models.
Responsibilities
- Provide platform level support for agentic use cases, helping teams adopt standards, tooling, and governance that enable rapid development and deployment across the organization.
- Lead the end to end design and development of AI powered microservices, focusing on modularity, scalability, and reusability to support various business units and applications.
- Drive the transition of AI models from notebook based PoCs and experimental phases into hardened, production grade components and services, ensuring performance, reliability, and maintainability.
- Design and implement robust APIs for AI microservices, facilitating seamless integration with existing Mastercard platforms and external systems.
- Identify and address performance bottlenecks within AI microservices and their underlying infrastructure, optimizing for latency, throughput, and cost efficiency.
- Collaborate closely with data scientists, MLOps engineers, product owners, and external partners to translate business requirements into technical specifications for agentic AI services.
- Implement rigorous testing strategies, including unit, integration, and performance testing, to ensure the quality, accuracy, and stability of deployed AI microservices.
Other
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field. Master’s degree preferred.
- Minimum of 8+ years in software development, with at least 4 years focused on building and deploying AI/ML powered applications or microservices in production environments.
- Excellent communication, interpersonal, and stakeholder management skills, with the ability to effectively articulate complex technical concepts to both technical and non technical audiences.
- Proven ability to lead technical initiatives, drive cross functional projects, and influence outcomes within a fast paced environment.
- Mentor junior engineers on best practices for AI software development and scaling.
