Lead Software Engineer
Confirmed on the employer's own hiring board on Oct 8, 2026. First seen by Alion on Jun 21, 2026.
Join Mastercard's Program Modernization team as a Lead Software Engineer. In this role, you will drive transformation and modernization across technology, risk, and service operations. You will design and deliver innovative, data-driven solutions that fulfill assurance obligations and regulatory requirements. Your focus will be on building intelligent, production-ready systems leveraging large language models (LLMs) and modern cloud/data platforms. You will collaborate cross-functionally with product, engineering, and data teams, and ensure solutions adhere to Mastercard's standards for data governance, security, compliance, and operational excellence.
Missions
- Concevoir, développer et livrer des solutions alimentées par l'IA en utilisant des architectures modernes, y compris les systèmes basés sur des modèles de langage (LLM) et la génération augmentée par récupération (RAG).
- Collaborer de manière transversale avec les équipes produit, d'ingénierie et de données pour traduire les besoins commerciaux en solutions habilitées par l'IA.
- Assurer que les solutions respectent les normes de Mastercard en matière de gouvernance des données, de sécurité, de conformité et d'excellence opérationnelle.
Profil recherché
- Strong experience with cloud platforms, particularly AWS, and familiarity with Cloudera and Databricks ecosystems- Excellent communication and stakeholder engagement skills
- Commitment to continuous learning and staying current with emerging AI technologies
- Demonstrated ownership and accountability for end-to-end delivery
- Proven experience (10 to 15 years) in software engineering, with strong focus on AI/ML and distributed systems
- Expertise in designing knowledge bases with vector search and working with embedding models
- Ability to operate effectively in a collaborative, fast-paced environment
- Strong problem-solving and analytical thinking
- Experience with Angular or similar frontend frameworks for building user-facing AI applications
- Hands-on experience with LLM frameworks (e.g., LangChain) and building RAG-based systems
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related discipline
- Solid understanding of system design, APIs, and microservices architecture
- Strong proficiency in Python, with experience building scalable backend systems
- Experience with Model Context Protocol (MCP) or similar AI orchestration frameworks
- Experience with vector databases such as PGVector, GraphDB
- Familiarity with MLOps practices, including CI/CD pipelines, monitoring, and lifecycle management
- Knowledge of containerization and orchestration (Docker, Kubernetes)
- Experience working in highly regulated, large-scale enterprise environments