Forward Deployed AI Engineer - Lead

What We Are Looking For

Lead Forward Deployed AI Engineers are hands-on technical leaders who own the architecture, execution, and delivery of critical production AI systems for large enterprise customers. They make technical decisions, lead project delivery, coach engineers, and partner closely with customer stakeholders and Distyl’s AI strategy team to ensure systems deliver real business value.

This role is for engineers who want ownership over production outcomes: shaping system architecture, leading technical execution, working directly with customers, and improving AI systems under real-world constraints.

Key Responsibilities

• Lead and mentor a team of Forward Deployed AI Engineers—owning technical direction, code quality, execution standards, and individual growth
• Design and implement AI systems that combine models, agents, retrieval, evaluation, and execution into coherent, production-ready systems aligned with real business outcomes
• Work directly with customer stakeholders, often in high-visibility settings, and communicate clearly about system behavior, tradeoffs, limitations, and paths to improvement
• Operate and improve live AI systems by measuring behavior, identifying failure modes, debugging issues, and rapidly iterating on quality, reliability, and usefulness
• Integrate AI systems into customer data platforms, APIs, and existing applications. Make pragmatic system design decisions that balance speed, robustness, maintainability, and long-term operability
• Take accountability for outcomes in production and adapt systems as requirements evolve

Who You Are

• 5+ years of engineering experience, including experience as a tech lead or engineering lead on customer-facing or production AI projects
• 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
• 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
• 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
• 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
• Willingness to travel: Travel is typically 10–30%, depending on the project, customer needs, and your role on the engagement