Forward Deployed Staff - Education

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. 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

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

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