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Salary: USD 140,000 - 180,000 / annual
Labrynth is an AI-powered platform company that helps organizations navigate regulatory complexity in heavily regulated industries (energy, compliance, government). The company operates as a forward-deployed engineering organization with small, high-velocity teams embedded directly with clients.
As a Senior Forward Deployed Engineer, you will work directly with customers on regulated, operational workflows and translate field insights into production-quality solutions. The role spans three core modes:
Field Work: Shadow operators and decision-makers to understand real workflows, identify bottlenecks, and locate evidence sources. Map user states, exceptions, and operating constraints through direct observation and field notes.
Building: Ship production-quality slices across the full stack—UI (TypeScript/React/Next.js), backend (Python/FastAPI/Django), data (Postgres), and integrations. Write tests, validate against realistic data paths, and ensure unsafe paths fail safely.
Productization: Extract reusable patterns from customer-specific work and feed them back into product and engineering roadmap. Turn one-off solutions into configurable primitives, evals, and playbooks that accelerate future customer onboarding.
You will own ambiguous work end-to-end: discovery, implementation, verification, demo, rollout, and follow-up. You'll explain technical tradeoffs and risks to non-technical stakeholders in plain language, always backing claims with evidence rather than optimism.
The role requires comfort in messy customer environments where the stated problem is rarely the real one. You'll move fluidly between customer conversations and the codebase, building the thing after understanding the actual need.
Key Qualifications:
- Proven track record shipping production software; can articulate what you built, how you verified it, and the user impact
- Proficiency across the full stack: TypeScript/React/Next.js for UI; Python (uv), Pydantic, FastAPI/Django for backend; Postgres for data and auth; experience with AI systems (pydantic-ai agents, typed outputs, evals, multi-model orchestration across Gemini/OpenAI/Bedrock)
- Cloud deployment experience (Vercel, Cloudflare, AWS, GCP); ability to debug across deployment, environment config, logs, and customer-facing behavior
- Strong evidence discipline: naturally separate fact, inference, assumption, and risk
- Product judgment: resist one-off customization unless the lesson belongs in core product
- Excellent communication skills; can explain what is safe, uncertain, and what comes next
Nice to Have:
- AWS expertise (IAM, GitHub OIDC, Lambda, API Gateway, Secrets Manager, CloudWatch, least privilege)
- Infrastructure-as-code experience
- Background in regulated industries (energy, compliance, government permitting, healthcare, finance)
- Prior forward-deployed, solutions, or founding engineer experience
