Director - development engineer
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 Director - AI Development Engineer Overview The Director – AI Development Engineering leads the end-to-end delivery of AI use cases within the AI Center of Excellence. Acting as the technical face of each initiative, this role partners with business stakeholders, data and platform teams, and compliance functions to translate strategy into scalable, secure solutions. The Director builds and manages a high-performing engineering team, delivering AI systems using both low-code and pro-code platforms. Success is measured by business value realization, solution adoption, quality, and speed to market. The Role- Own and execute a multi-quarter roadmap for AI capabilities across diverse use cases.
- Lead engineering teams delivering AI solutions using low-code (Copilot Studio, Power Platform) and pro-code (Databricks, Azure, AWS) platforms.
- Act as technical liaison with business sponsors; drive discovery, requirements, and solution design.
- Provide executive-level updates on progress, risks, and value, influence decisions with data.
- Architect solutions aligned with enterprise standards; promote reuse via reference architectures and shared components.
- Implement enterprise-grade SDLC and MLOps practices: CI/CD, automated testing, model registry, version control.
- Ensure reliability through monitoring, observability, and incident response for models, pipelines, and applications.
- Integrate AI systems with enterprise data platforms, APIs, identity, and security controls.
- Guide teams on LLM and classical ML patterns (e.g., RAG, evaluation, guardrails); balance low-code and pro-code approaches.
- Embed Responsible AI, privacy, and model risk management throughout the delivery lifecycle.
- Hire, mentor, and retain top engineering talent; manage vendors and foster a learning culture.
- Define and track OKRs; continuously improve velocity, deployment frequency, and change failure rates.
- Bachelor’s or Master’s in Computer Science, Engineering, or related field; advanced degrees (MS/PhD or MBA) preferred.
- Proven leadership in delivering enterprise-scale AI/ML solutions across software, data, and platform engineering.
- Hands-on experience with low-code tools (Power Platform, Copilot Studio) and pro-code environments (Databricks, AWS, Azure).
- Deep expertise in MLOps/LLMOps: CI/CD, automated testing, model/version registry, evaluation frameworks, and guardrails.
- Strong understanding of enterprise architecture (APIs, microservices, event-driven systems) and data platforms (Delta Lake, feature stores).
- Skilled in cloud infrastructure (Azure, AWS), containerization (Docker, Kubernetes), and observability (logs, metrics, tracing).
- Experience with Responsible AI, identity and access management, data protection, and integration with vector databases and enterprise apps.
- Effective communicator and strategic leader with experience in regulated environments, stakeholder alignment, and team development.
- Abide by Mastercard’s security policies and practices;
- Ensure the confidentiality and integrity of the information being accessed;
- Report any suspected information security violation or breach, and
- Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.
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