Manager, AI Engineering

Role overview

Product and engineering leadership

• Drive 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 roadmap, and engineering strategy.
• Guide decisions across coding, architecture, modeling, system design, and operational excellence.
• Partner across Product, Cloud, Architecture, and Customer teams to deliver end-to-end capabilities.
• Promote code quality, documentation, testing, CI/CD, observability, and production excellence; use data-driven feedback to improve quality, performance, and efficiency.
• Build a culture of ownership, innovation, accountability, and technical excellence; stay current with AI/ML and technology advances.

Required qualifications

• Bachelor’s degree in Computer Science or equivalent from a recognized institution.
• 11+ years of experience in large-scale product development, distributed systems, or AI/ML, managing teams and senior engineering talent.
• Strong 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

• Preferred: SQL/NoSQL data stores, data modeling, and messaging systems such as Kafka.
• Preferred: Kubernetes, containerization, and modern deployment practices.
• Preferred: AI productivity tools such as Claude or GitHub Copilot and UI technologies.
• Preferred: navigating ambiguity, stakeholder collaboration, mentoring senior engineers, and building scalable engineering organizations.
• Preferred: strong communication, interpersonal skills, and ability to thrive in evolving environments.

Company and culture