{"id":2824145,"url":"https://alion.io/job/levelup-labs-forward-deployed-staff-engineering","title":"Forward Deployed Staff - Engineering","company":{"id":4429628,"name":"Levelup Labs","domain":"leveluplabs.com","url":"https://alion.io/company/levelup-labs","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Solutions","role_family":"Solutions","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"inferred_payroll_markers","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":104000,"max_usd":223000,"period":"year","method":"global_role_seniority_cell","sample_n":1519},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"JavaScript","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rust","optional":false},{"name":"TypeScript","optional":false}],"status":"live","first_seen_at":"2026-10-18T17:52:57Z","employer_posted_date":null,"last_verified_at":"2026-10-18T17:52:57Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"The RoleAs Forward Deployed Staff - Engineering, you'll be embedded with client teams building production-grade AI systems. This is a hands-on engineering role where you'll design, build, and ship AI products and internal tools that solve real business problems.\nThe \"Forward Deployed\" Philosophy:Everyone at LevelUp Labs is a generalist. You'll be expected to contribute across engineering, training, and content when needed. However, this role has a spike in engineering and implementation—you're someone who loves building production systems, debugging hard problems, and shipping code that works at scale.\nWhat \"spike\" means: You can teach and create content, but your edge is in building. You're the person others go to when the system is broken, when the architecture needs rethinking, or when something needs to actually ship.\nWhat You'll DoBuild\nDesign and implement production-grade AI systems alongside client engineering teams\n\nBuild LLM-powered applications: RAG systems, agents, evaluation frameworks, etc.\n\nOwn technical architecture decisions and trade-offs\n\nWrite code that's maintainable, tested, documented, and built to last\n\nDebug complex issues across the stack\n\nEmbed\nWork directly with client engineering teams as a peer, not an outside consultant\n\nUnderstand client constraints, existing systems, and organizational context\n\nCommunicate progress and challenges to both technical and non-technical stakeholders\n\nTransfer knowledge to client teams—leave them better than you found them\n\nLearn & Share\nDistill learnings from implementations into patterns we can reuse\n\nContribute to our courses, documentation, and internal tooling\n\nStay current with AI developments—evaluate what actually works in production\n\nParticipate in technical discussions and code reviews\n\nWhat We're Looking ForMust HaveEngineering\n2+ years building production software systems\n\nStrong programming skills (Python required; experience with TypeScript/JavaScript, Go, or Rust a plus)\n\nDeep experience with AI/ML systems: LLMs, RAG, agents, fine-tuning, evaluations\n\nStrong understanding of software engineering best practices (testing, CI/CD, observability, documentation)\n\nExperience with cloud platforms (AWS, GCP, or Azure)\n\nProduction Mindset\nYou've shipped systems that handle real traffic and real users\n\nYou think about failure modes, edge cases, and operational concerns\n\nYou know the difference between demo code and production code\n\nYou've been paged at 2am and fixed something that was broken\n\nCommunication\nCan explain technical decisions to non-technical stakeholders\n\nComfortable presenting architecture and progress to client leadership\n\nClear written communication (documentation, design docs, async updates)\n\nCan work effectively with client teams across different cultures and timezones\n\nMindset\nSelf-directed—you don't need someone telling you what to do next\n\nComfortable with ambiguity and rapidly changing requirements\n\nEgo-free: you'll do whatever needs doing to ship\n\nStrong opinions, loosely held\n\nNice to Have\nExperience with enterprise clients (understanding their constraints and pace)\n\nPrior consulting or client-facing engineering experience\n\nContributions to open source projects\n\nBackground with observability and evaluation frameworks for AI\n\nExperience leading technical projects or mentoring engineers\n\nWhat You'll Get\nCompetitive compensation (base + performance bonuses + outcome-based bonus per engagement)\n\nWork on challenging problems with leading companies\n\nLearn from a team with 30+ enterprise implementations and published AI research\n\nFlexibility: remote-first, async-friendly\n\nDirect impact: you're building real systems, not maintaining legacy code\n\nGrowth: as an early team member, you'll shape our engineering culture\n\nOriginally posted on Himalayas","description_format":"text","description_chars":3794,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-18T20:28:00Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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