Technical Lead Manager, Forward Deployed Engineering

Key Responsibilities

• Lead a pod of elite, AI-native full-stack engineers with a bias to action to rapidly build and deploy end-to-end AI systems, owning the full arc from problem framing to MVP to deployed workflow
• Define and own the end-to-end technical vision and architecture for the team's solutions, understanding that a running system beats the cleanest architecture diagram
• Champion production discipline for enterprise by establishing and enforcing best practices in context engineering, evaluation, and operational readiness
• Mandate rigorous testing, including golden sets, regression harnesses, and red-teaming, and set the standard for secure, observable, and auditable code
• Provide hands-on leadership and mentorship to a team of engineers, coaching them through complex challenges while actively contributing to the build
• Foster a culture of high talent density where every member raises the bar and enable them to deliver quality at speed
• Lead working sessions and facilitate collaboration across client stakeholders from engineers to the C-suite and cross-functional teams to design creative AI systems
• Drive delivery in a fast-paced, outcome-accountable environment, operating in two-to-six-week cycles with direct client feedback
• Lead working sessions, earn client trust, manage risks, surface constraints early, and ensure every deliverable is ready for scale or run in production
• Champion the use of modern development accelerators such as Claude Code, Lovable, Cursor, and others where policy permits, to increase capacity of delivery, increase quality, and deliver faster

Requirements

• Minimum seven years of recent experience shipping end-to-end production secure software systems, with a focus on data, machine learning, and AI-native applications
• Bachelor's degree from an accredited college or university in a science or engineering field
• Proven ability to lead, manage, and mentor high-performing technical teams, with at least three years of experience in a hands-on leadership role
• Deep, hands-on knowledge of modern AI technologies and methodologies with demonstrated experience leading teams in designing and implementing advanced AI systems
• Excellent problem-solving, collaboration, and communication skills with the ability to thrive in ambiguous environments
• Demonstrate prior experience with real work via a portfolio, a GitHub repository, or a structured walk-through of a system they have designed and shipped

Qualifications

• Domestic travel may be required
• Must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future