{"id":1131186,"url":"https://alion.io/job/infinity-constellation-senior-forward-deployed-engineer-labrynth","title":"Senior Forward Deployed Engineer - Labrynth","company":{"id":6015,"name":"Infinity Constellation","domain":"infinity.com","url":"https://alion.io/company/infinity","size_band":null,"is_staffing_agency":false,"is_intermediary":true,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":73,"open_postings":19,"ghost_share":0.526,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":18,"computed_at":"2026-09-23T05:45:00Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","hiring_geo_confidence":"inferred","locations":["Warsaw, Poland","New York, United States"],"countries":["PL","US"],"hiring_countries":["US","PL"],"hiring_countries_total":2,"salary":{"min":140000,"max":180000,"currency":"USD","period":"year","gross":null,"usd_annual":180000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Cloudflare","optional":false},{"name":"Django","optional":false},{"name":"FastAPI","optional":false},{"name":"GCP","optional":false},{"name":"Next.js","optional":false},{"name":"OpenAI","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Pydantic","optional":false},{"name":"Pydantic AI","optional":false},{"name":"Python","optional":false},{"name":"React.js","optional":false},{"name":"shadcn/ui","optional":false},{"name":"Tailwind CSS","optional":false},{"name":"TypeScript","optional":false},{"name":"Vercel","optional":false},{"name":"Amazon CloudWatch","optional":true},{"name":"API Gateway","optional":true},{"name":"AWS Lambda","optional":true},{"name":"Claude Code","optional":true},{"name":"Cursor","optional":true},{"name":"GitHub","optional":true},{"name":"IAM","optional":true},{"name":"JavaScript","optional":true},{"name":"Least Privilege","optional":true},{"name":"Radix UI","optional":true}],"status":"live","first_seen_at":"2026-09-22T21:22:07Z","employer_posted_date":"2026-09-22","last_verified_at":"2026-09-23T22:56:28Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":1},"description":"About Labrynth\nLabrynth accelerates progress by streamlining regulatory complexity. We build AI-powered platforms that navigate complex regulations, generate audit-level documentation, and provide certainty, not shortcuts. Our technology serves clients across heavily regulated industries including energy, compliance, and government regulations.\nWe operate as a forward-deployed engineering organization: small, high-velocity teams embedded directly with clients to rapidly discover needs and ship production-quality solutions.\nAbout the Role\nWe are hiring a Forward Deployed Engineer to work directly with customers on regulated, operational workflows and turn that field work into a production product.\nFDEs sit close to the customer and close to the code. You will map real workflows, identify the first useful product slice, implement it, verify it, demo it truthfully, and help decide what should become a reusable platform. The work spans three modes:\nField: shadow operators, model decisions, find evidence sources, and understand where the workflow is slow, risky, or brittle.\n\nBuild: ship production slices across UI, API, data, permissions, tests, and deployment paths.\n\nProductize: turn customer-specific learning into primitives, configuration, evals, playbooks, or roadmap changes.\n\nWhat You'll Do\nRun customer discovery, workflow shadowing, and field notes with operators and decision owners, until you can name the users, states, evidence sources, exceptions, and the real operating constraint\n\nImplement thin product slices in a live codebase across frontend, backend, data, and integrations, where the happy path works, unsafe paths fail, and the behavior survives realistic data\n\nWrite tests, run realistic paths, inspect logs, and document what is proven, missing, or uncertain, so every customer demo is backed by evidence, not optimism\n\nExplain tradeoffs, risks, and next steps to non-technical customers without overclaiming\n\nIdentify reusable patterns from field work and feed them into product and engineering, so the next customer gets faster onboarding, safer workflows, or more reusable product\n\nCarry ambiguous work end to end: discovery, build, demo, rollout, and follow-up\n\nWhat We're Looking For\nWe don't need you to have used every tool in our stack. We need someone who can move safely across this kind of system and learn the missing pieces quickly.\nYou have personally shipped production software and can explain what you touched, how you verified it, and what changed for users\n\nYou are comfortable in messy customer settings where the first request is rarely the real problem\n\nYou can talk to operators in plain language, then go back to the codebase and build the thing\n\nProduct UI: TypeScript, React, Next.js, shadcn/Tailwind; you can trace a user flow, change a screen, and respect server/client boundaries\n\nBackend: Python (uv), Pydantic, Django/Django Ninja or FastAPI, background workers, and typed APIs\n\nData and auth: Postgres, migrations, service roles, tenant scoping, and auditability\n\nAI systems: pydantic-ai agents, typed outputs, evals, and provider choice across Gemini, OpenAI, and Bedrock; you use AI tools for leverage but never treat generated output or a clean demo as proof\n\nCloud: Vercel, Cloudflare, AWS, GCP; you can debug across deployment, env config, logs, and customer-facing behavior\n\nEvidence discipline: you naturally separate fact, inference, assumption, and risk\n\nProduct judgment: you resist one-off customization unless the lesson clearly belongs outside core product\n\nStrong communication skills: you can explain what is safe, what is uncertain, and what happens next\n\nNice to Have\nAWS experience (IAM, GitHub OIDC, Lambda, API Gateway, Secrets Manager, CloudWatch, least privilege);\n\nInfrastructure as code experience\n\nExperience in regulated industries (energy, compliance, government permitting, healthcare, finance)\n\nPrior forward deployed, solutions, or founding engineer experience\n\nWhat We Offer\nHigh-impact work at the intersection of AI and critical infrastructure regulation\n\nDirect customer exposure and a seat at the table when we decide what to build\n\nSmall team with outsized influence; your field learning shapes the product roadmap\n\nModern AI-native development environment (Claude Code, Cursor, multi-model orchestration)\n\nRemote-first\n\nCompetitive compensation\n\nValues We Hire For\nCharacter: integrity and trustworthiness above all\n\nCompetency: evoking trust and reliably delivering\n\nTogetherness: family-level support and alignment\n\nImpact: meaningful outcomes over activity\n\nCommitment: ownership and follow-through\n\nWhat’s In It For You\nLabrynth is committed to fair and competitive pay, ensuring that compensation reflects both market conditions and the value each team member brings.\nFor this position, the annual salary ranges by location are:\nSalary Range\n$140,000 - $180,000 USD\n*Offers also include bonus + equity\nCompensation is based on location, experience, skills, internal equity, and market conditions. For candidates outside the U.S., pay is aligned with local market conditions and cost of living. Your Talent Acquisition Partner will confirm the applicable compensation range and benefits during the interview process.\nEqual Opportunity Statement:\nWe’re an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or veteran status, or any other basis protected by law.","description_format":"text","description_chars":5492,"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":["Equity"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"},{"name":"New York","iso":null,"kind":"city"},{"name":"Poland","iso":"PL","kind":"country"},{"name":"Warsaw","iso":null,"kind":"city"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Venture Capital","Custom Software Development"],"lifecycle":[{"event":"open","at":"2026-09-23T03:18:26Z"}],"liveness":{"score":60,"band":"ok","label":"Likely open","p_open":1,"p_active":0.602,"p_room":1,"age_days":0,"expected_fill_days":18,"reasons":["conf:0","stale_co","win:early"],"computed_at":"2026-09-23T05:45:00Z"},"pay":{"stated_usd_annual":180000,"is_top_pay":false},"html_url":"https://alion.io/job/infinity-constellation-senior-forward-deployed-engineer-labrynth","json_url":"https://alion.io/job/infinity-constellation-senior-forward-deployed-engineer-labrynth.json","meta":{"generated_at":"2026-09-24T01:17:34Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers"}}