Forward Deployed - 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 Level Up 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.

• 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

• Must Have Engineering 2+ years building production software systems
• Strong programming skills (Python required; experience with Type Script/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

• 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

Originally posted on Himalayas