Lead AI Engineer

Join Distyl as a Lead AI Engineer, where you will be a hands-on technical leader responsible for the architecture, execution, and delivery of critical production AI systems for large enterprise customers. You will lead and mentor a team of AI Engineers, design and implement AI systems, work directly with customer stakeholders, and operate and improve live AI systems. This role offers equity options, healthcare, and a collaborative work environment focused on personal and professional growth.

• Lead the architecture, execution, and delivery of critical production AI systems for large enterprise customers.
• Mentor and guide a team of AI Engineers, ensuring technical direction, code quality, and individual growth.
• Collaborate with customer stakeholders to ensure systems deliver real business value, and communicate clearly about system behavior and tradeoffs.
• Ownership mentality for AI systems. You take responsibility for whether an AI system delivers its intended value in production. You are comfortable making independent technical decisions across system design, evaluation, integration, and iteration
• Willingness to travel: Travel is typically 10–30%, depending on the project, customer needs, and your role on the engagement
• Technical leadership in teams. Management experience is not required, but you should have led engineers through technical decision-making, execution, mentorship, and delivery. Growth in this role includes taking on broader technical and leadership scope over time
• 5+ years of engineering experience, including experience as a tech lead or engineering lead on customer-facing or production AI projects
• AI-Native Working Style: You use AI tools daily to write and debug code, explore designs, analyze data, and automate repetitive work. You are curious about new model capabilities and techniques, and actively incorporate them into how you build and iterate on systems
• Strong solutions architecture fundamentals: You have experience with cloud systems, system integrations, API design, and data engineering. You can understand how an AI system fits into a broader enterprise ecosystem and operate as a peer to customer architecture and engineering teams