Engineering Manager – Applied AI
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.
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.
Qualifications
- Technical leader who still codes: You enjoy reviewing PRs, debating architecture, and jumping into difficult technical problems.
- 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.
Additional Requirements
- Ability to work extended hours and weekends as necessary.
Pay
The base salary range for this role is $220,000-$300,000 annually.
Benefits
- In addition to base salary, for full-time hires, you may also be eligible for long-term incentives, in the form of stock options, and access to medical, vision & dental coverage as well as access to a 401(k) retirement plan.