[Hiring] Senior Forward Deployed Engineer @Infinity

Role Description

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.
• Implement thin product slices in a live codebase across frontend, backend, data, and integrations.
• Write tests, run realistic paths, inspect logs, and document what is proven, missing, or uncertain.
• 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.
• Carry ambiguous work end to end: discovery, build, demo, rollout, and follow-up.

Qualifications

• Experience shipping 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.
• Ability to talk to operators in plain language, then go back to the codebase and build the thing.
• Strong communication skills to explain what is safe, what is uncertain, and what happens next.

Requirements

• Product UI: TypeScript, React, Next.js, shadcn/Tailwind.
• Backend: Python (uv), Pydantic, Django/Django Ninja or FastAPI.
• 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.
• Cloud: Vercel, Cloudflare, AWS, GCP.
• Evidence discipline: naturally separate fact, inference, assumption, and risk.
• Product judgment: resist one-off customization unless the lesson clearly belongs outside core product.

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.

Benefits

• 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.

Company Description

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.