Senior Forward Deployed Engineer - Labrynth

Constella Care; New York (NY); Remote; USD 140,000 - 180,000; Full time

Benefits offered by this job

Remote-first

Bonus + equity

Competitive pay

Job summary

Labrynth is seeking a Forward Deployed Engineer to work directly with customers on regulated, operational workflows and turn field work into a production product.

You will shadow operators, implement thin product slices across frontend, backend, data, and integrations, and document what is proven or uncertain to ensure solid demos.

The role offers remote-first collaboration, competitive USD salary, and bonus/equity, with opportunities to shape product strategy for regulated industries.

Qualifications

• Shipped production software and can explain what you touched, how you verified it, and what changed for users.
• Comfortable in messy customer settings where the first request is rarely the real problem.
• Able to talk to operators in plain language, then go back to the codebase and build the thing.
• Experience with modern frontend tech (TypeScript, React, Next.js, shadcn/Tailwind)
• Backend experience with Python (uv, Django/Django Ninja or FastAPI) and typed APIs
• Data and auth experience with Postgres, migrations, service roles, tenant scoping, auditability
• Experience with AI systems (pydantic-ai agents, evals, provider choice) across Gemini, OpenAI, Bedrock
• Cloud experience across Vercel, Cloudflare, AWS, GCP
• Evidence discipline, separating fact, inference, and risk
• Product judgment to avoid unnecessary customizations and keep core product in mind
• Strong communication skills to explain safety, uncertainty, and next steps

Responsibilities

• Run customer discovery, workflow shadowing, and field notes to name users, states, evidence sources, exceptions, and constraints
• Implement thin product slices in a live codebase across frontend, backend, data, and integrations
• Write tests, inspect logs, and document what is proven, missing, or uncertain for credible customer demos
• Explain tradeoffs, risks, and next steps to non-technical customers
• Identify reusable patterns from field work and feed them into product and engineering
• Carry ambiguous work end to end: discovery, build, demo, rollout, and follow-up

Skills

Frontend engineering

Backend engineering

Data systems

AI systems

Cloud platforms

Communication skills

Product judgment

Evidence discipline

Tools

Postgres

Django

FastAPI

Pydantic

Vercel

Cloudflare

AWS

GCP

OpenAI

Job description

About Labrynth

Labrynth 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.

We operate as a forward-deployed engineering organization: small, high-velocity teams embedded directly with clients to rapidly discover needs and ship production-quality solutions.

About the Role

We are hiring a Forward Deployed Engineer to work directly with customers on regulated, operational workflows and turn that field work into a production product.

FDEs 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:

• Field: shadow operators, model decisions, find evidence sources, and understand where the workflow is slow, risky, or brittle.

• Build: ship production slices across UI, API, data, permissions, tests, and deployment paths.

• Productize: turn customer-specific learning into primitives, configuration, evals, playbooks, or roadmap changes.

What You'll Do

• 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

What We're Looking For

We 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.

• 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

Nice to Have

• AWS experience (IAM, GitHub OIDC, Lambda, API Gateway, Secrets Manager, CloudWatch, least privilege);

• Infrastructure as code experience

• Experience in regulated industries (energy, compliance, government permitting, healthcare, finance)

• Prior forward deployed, solutions, or founding engineer experience

What We Offer

• 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

Values We Hire For

• Character: integrity and trustworthiness above all

• Competency: evoking trust and reliably delivering

• Togetherness: family-level support and alignment

• Impact: meaningful outcomes over activity

• Commitment: ownership and follow-through

What’s In It For You

Labrynth is committed to fair and competitive pay, ensuring that compensation reflects both market conditions and the value each team member brings.

For this position, the annual salary ranges by location are:

Salary Range

$140,000 - $180,000 USD

*Offers also include bonus + equity

Compensation 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.

Equal Opportunity Statement:

We’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.