Manager, AI Engineering

Role overview

Responsibilities

• Lead design, architecture, development, evolution, delivery, and adoption of one or more AI products.
• Lead and develop engineering teams, including Staff and Senior Engineers.
• Shape product vision, technology roadmaps, and engineering strategy.
• Guide technical decisions across coding, architecture, modeling, system design, and operational excellence.
• Collaborate across Product, Cloud, Architecture, and Customer teams on end-to-end capabilities.
• Champion code quality, documentation, testing, CI/CD, observability, and production excellence.
• Use data-driven processes and feedback loops to improve product quality, performance, and engineering efficiency.
• Build a culture of ownership, innovation, accountability, and technical excellence.
• Stay current with emerging technologies, AI/ML advancements, and industry practices.

Required qualifications

• Bachelor’s degree in Computer Science or equivalent from a recognized institution.
• 11+ years in large-scale product development, distributed systems, or AI/ML, including management of teams and senior engineering talent.
• Problem-solving skills and familiarity with AI/ML technologies, including LLMs and agentic AI systems.
• Expertise in microservices, RESTful APIs, cloud technologies, SDLC, CI/CD, observability, and production operations.
• Experience building high-quality products in fast-paced technology environments.

Preferred qualifications

• SQL/NoSQL data stores, data modeling, and messaging systems such as Kafka.
• Kubernetes, containerization, and modern deployment practices.
• AI productivity tools such as Claude or GitHub Copilot, and UI technologies.
• Ability to navigate ambiguity, collaborate, drive alignment, mentor senior engineers, and build scalable engineering organizations.
• Strong communication, interpersonal skills, and a growth mindset.

About Teradata