About this role
Summary: This role combines engineering, teaching, and content creation within a forward-deployed model. You will build production AI systems, deliver technical training, and create educational content while collaborating closely with client engineering teams.
The Role
As Forward Deployed Staff - Education, you'll work across the full spectrum of what we do: building production AI systems, delivering technical training, and creating educational content. This is not a siloed role—you'll move fluidly between implementation, teaching, and content creation based on what's needed.
The "Forward Deployed" Philosophy:
Everyone at LevelUp Labs is a generalist. You'll be expected to contribute across engineering, training, content, and client work. However, this role has a spike in education and curriculum development—you're someone who loves teaching and creating learning experiences, while still being a strong engineer.
What "spike" means: You can do all three, but your edge is in making complex things learnable. You're the person who builds something and immediately thinks about how to teach it to others.
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What You'll Do
### Build
- Design and implement production-grade AI systems alongside client engineering teams
- Build LLM-powered applications: RAG systems, agents, evaluation frameworks, etc.
- Own technical architecture decisions and trade-offs
- Write code that's maintainable, tested, documented, and built to last
- Debug complex issues across the stack
### Embed
- Work directly with client engineering teams as a peer, not an outside consultant
- Understand client constraints, existing systems, and organizational context
- Communicate progress and challenges to both technical and non-technical stakeholders
- Transfer knowledge to client teams—leave them better than you found them
### Learn & Share
- Distill learnings from implementations into patterns we can reuse
- Contribute to our courses, documentation, and internal tooling
- Stay current with AI developments—evaluate what actually works in production
- Participate in technical discussions and code reviews
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What We're Looking For
### Must Have
Engineering
- 2+ years building production software systems
- Strong programming skills (Python required; experience with TypeScript/JavaScript, Go, or Rust a plus)
- Deep experience with AI/ML systems: LLMs, RAG, agents, fine-tuning, evaluations
- Strong understanding of software engineering best practices (testing, CI/CD, observability, documentation)
- Experience with cloud platforms (AWS, GCP, or Azure)
Production Mindset
- You've shipped systems that handle real traffic and real users
- You think about failure modes, edge cases, and operational concerns
- You know the difference between demo code and production code
- You've been paged at 2am and fixed something that was broken
Communication
- Can explain technical decisions to non-technical stakeholders
- Comfortable presenting architecture and progress to client leadership
- Clear written communication (documentation, design docs, async updates)
- Can work effectively with client teams across different cultures and timezones
Mindset
- Self-directed—you don't need someone telling you what to do next
- Comfortable with ambiguity and rapidly changing requirements
- Ego-free: you'll do whatever needs doing to ship
- Strong opinions, loosely held
### Nice to Have
- Experience with enterprise clients (understanding their constraints and pace)
- Prior consulting or client-facing engineering experience
- Contributions to open source projects
- Background with observability and evaluation frameworks for AI
- Experience leading technical projects or mentoring engineers
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What You'll Get
- Competitive compensation (base + performance bonuses + outcome-based bonus per engagement)
- Work on challenging problems with leading companies
- Learn from a team with 30+ enterprise implementations and published AI research
- Flexibility: remote-first, async-friendly
- Direct impact: you're building real systems, not maintaining legacy code
- Growth: as an early team member, you'll shape our engineering culture