Director of Engineering

Lazer Technologies is a remote-first digital product studio that builds and scales digital products for startups, enterprises, and major brands. The Director of Engineering will co-own an AI engineering team of approximately 30 forward deployed engineers, leading people development, performance management, staffing, hiring, and engagement health. The role also provides technical leadership on AI-powered full-stack applications, architecture, evaluation strategy, client engagements, and pre-sales activities.

Responsibilities:

• Co-own the AI engineering team of roughly 30 forward deployed engineers alongside existing engineering leaders
• Own the health and happiness of the team through regular 1:1s, catching disengagement, burnout, and bench frustration before they become resignations
• Run performance reviews against our FDE rubric, which weighs consulting skills as equally important as technical skills
• Level up the team as Forward Deployed Engineers through training sessions, playbooks, checklists, pairing, and internal writeups
• Define and maintain the baseline AI competency every engineer on the team is held to, and keep it current as tooling changes
• Codify what our best engineers do instinctively into shared, documented practice, and distill field learnings back into reusable patterns
• Track engagement health across the portfolio, surfacing delivery risk, uncovered areas, and deteriorating client relationships early
• Review architectures and pressure-test approaches so they hold up to scrutiny from a client CTO or architecture review board
• Provide project and technical guidance on evaluation strategy, instrumentation, and how we prove impact
• Step onto engagements as technical lead when a project needs it
• Partner with talent on sourcing, run hiring manager screens, calibrate interviewers, and own the technical bar for the team
• Staff engagements by matching engineers to projects on skill, growth, and client fit, and manage workload so utilization and development stay in balance
• Support scoping and pre-sales conversations where technical credibility matters, and act as senior escalation point for clients and partners

Requirements:

• 10+ years of engineering experience with 3+ years directly managing senior engineers, including hiring, performance management, and the difficult conversations that come with both
• Experience leading teams of 15+ engineers, ideally spread across multiple concurrent projects or engagements
• Still hands-on technically: you can read an architecture, spot the flaw, and propose a better approach
• Strong full stack depth with TypeScript, React, Node.js, Python or Go
• Proven experience building and shipping production agentic applications, including orchestration and tool-calling patterns
• Confidence setting up evaluation harnesses and testing infrastructure around agentic applications, run against real prompts and business metrics
• Familiarity with MLOps or LLMOps practices, including monitoring, guardrails, and human-in-the-loop design
• Comfort working with at least one major cloud provider (GCP, AWS, Azure)
• AI-native in your own daily practice, with grounded opinions on coding agents, harnesses, and workflows that you can teach credibly to other engineers
• Previous experience in consulting, agency, or forward deployed engineering roles, with the ability to manage client expectations and timelines
• A track record of developing people deliberately through training programs, onboarding paths, or mentorship structures that outlasted your direct involvement
• Comfort operating in ambiguity, making calls without waiting for permission, and creating clarity for the people around you
• Exceptional communication skills across executives, staff engineers, and written updates, and the instinct to hold your team to the same standard
• Enterprise depth in financial services, healthcare, or retail, including how security, legal, and compliance review actually work
• Experience scaling a forward deployed engineering, solutions engineering, or professional services team
• Experience running AI enablement or developer productivity programs for an engineering org
• Background as a founder, CTO, or early engineer at a venture-backed startup
• Experience fine-tuning LLMs using open-source models or closed-source services
• Familiarity with Kubernetes and container orchestration
• Experience designing scalable data pipelines or data lakes
• Relevant certifications, open-source contributions, or technical publications