Engineering Manager – Applied AI

General Matter•Los Angeles, CA

1d•$220,000 - $300,000

About The Position

General Matter is seeking an Engineering Manager for Applied AI to lead a team focused on making existing engineering workflows significantly faster using modern AI. This role involves embedding with engineering teams across the company to identify bottlenecks, build tools, and challenge conventional assumptions in the nuclear industry. The goal is to define what AI-first engineering looks like in this sector, impacting areas like nuclear licensing, safety analysis, and design criteria. This is an opportunity to reinvent engineering workflows and contribute to a mission-driven company aiming to make nuclear energy the most affordable and abundant source of baseload power.

Requirements

7+ years of professional software engineering or applied AI experience.
2+ years of experience managing, mentoring, or growing software or applied AI engineers.
Demonstrated experience building and shipping software using LLMs, AI agents, or other modern AI techniques.
Strong software engineering fundamentals and proficiency in Python.
BS or higher in engineering, physics, chemistry, applied math, computer science, or a related technical field.

Nice To Haves

Technical leader who still codes: You enjoy reviewing PRs, debating architecture, and jumping into difficult technical problems. This is not a role you can do from a distance.
AI fluency: You have hands-on experience with technologies such as LLMs, RAG, tool-use architectures, and AI agents, and think critically about where AI can create meaningful leverage.
Strong engineering judgment: You can quickly understand technical problems across disciplines and evaluate whether your team’s approach is sound without needing to be the domain expert.
Workflow-oriented mindset: You’re excited by finding ways to fundamentally improve how engineering teams work, rather than simply adding AI to existing processes.
Builds high-agency teams: You hire and develop engineers who take ownership, move quickly, and solve problems without waiting for a detailed roadmap or specification.
Experience scaling small teams: You’ve helped a high-context engineering team add structure and process while preserving speed, autonomy, and technical quality

Responsibilities

Lead and grow the Applied AI team: Hire, develop, and retain engineers while setting a high technical bar.
Own technical direction and prioritization: Identify the highest-leverage engineering problems and decide where the team should invest its time.
Stay hands-on: Review architecture, solve difficult technical problems, and contribute to implementation when appropriate.
Partner with engineering teams across General Matter: Work directly with licensing, safety, design, manufacturing, and other technical teams to understand their workflows and identify opportunities for AI-driven leverage.
Build scalable engineering practices: Establish the processes for project selection, prototyping, evaluation, and production handoff that allow the team to grow without losing speed.
Represent Applied AI across the company: Communicate technical direction, progress, and tradeoffs to company leadership and cross-functional partners.