Forward Deployed Engineer

Infinity Constellation

Forward Deployed Engineer at Labrynth developing AI-powered platforms to navigate regulations and provide certainty. Collaborating closely with customers to turn field work into production-quality solutions.

Posted 7/24/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in shipping production software with a focus on user impact, evidence-based decision-making, and effective communication with both technical and non-technical stakeholders. Proficient in implementing product features across frontend and backend technologies while maintaining a disciplined approach to evidence and product judgment.

Highest-signal resume keywords

TypeScriptReactNext.jsPythonPostgres

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Production Software ShippingUser Flow TracingTest WritingData MigrationTyped APIs

Soft Skills

Strong Communication SkillsProblem-SolvingCustomer Discovery

Tools & Technologies

DjangoFastAPIVercelCloudflareAWS

Industry Keywords

Evidence DisciplineProduct JudgmentAI SystemsBackground WorkersTenant Scoping

Tech Stack

Tools & technologies

AWSCloudDjangoGoogle Cloud PlatformJavaScriptNext.jsPostgresPythonReactTypeScript

About the role

Key responsibilities & impact

Run 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
Implement 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
Write tests, run realistic paths, inspect logs, and document what is proven, missing, or uncertain, so every customer demo is backed by evidence, not optimism
Explain tradeoffs, risks, and next steps to non-technical customers without overclaiming
Identify 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
Carry ambiguous work end to end: discovery, build, demo, rollout, and follow-up

Requirements

What you’ll need

You have personally shipped production software and can explain what you touched, how you verified it, and what changed for users
You are comfortable in messy customer settings where the first request is rarely the real problem
You can talk to operators in plain language, then go back to the codebase and build the thing
Product UI: TypeScript, React, Next.js, shadcn/Tailwind; you can trace a user flow, change a screen, and respect server/client boundaries
Backend: Python (uv), Pydantic, Django/Django Ninja or FastAPI, background workers, and typed APIs
Data and auth: Postgres, migrations, service roles, tenant scoping, and auditability
AI 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
Cloud: Vercel, Cloudflare, AWS, GCP; you can debug across deployment, env config, logs, and customer-facing behavior
Evidence discipline: you naturally separate fact, inference, assumption, and risk
Product judgment: you resist one-off customization unless the lesson clearly belongs outside core product
Strong communication skills: you can explain what is safe, what is uncertain, and what happens next

Benefits

Comp & perks

High-impact work at the intersection of AI and critical infrastructure regulation
Direct customer exposure and a seat at the table when we decide what to build
Small team with outsized influence; your field learning shapes the product roadmap
Modern AI-native development environment (Claude Code, Cursor, multi-model orchestration)
Remote-first
Competitive compensation