The Role As Forward Deployed Staff - Growth, you'll drive how LevelUp Labs reaches and engages the market. This is a hands-on growth role—you'll create content, manage community, build partnerships, and support sales. Like all Forward Deployed roles, you're a generalist who does whatever it takes to move the needle. The "Forward Deployed" Philosophy: Everyone at LevelUp Labs is a generalist. You'll be expected to contribute across growth, content, community, and even support client engagements when needed. However, this role has a spike in growth and go-to-market—you're someone who understands how to build an audience, create compelling content, and drive pipeline, while still being technically literate enough to work with our AI-focused clients. What "spike" means: You can contribute across all areas, but your edge is in understanding what makes people pay attention, engage, and convert. You think in funnels, content loops, and distribution. You'll manage the content creation flywheel—from idea to published piece to engagement.

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