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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.
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
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
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
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
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
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