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Forward Deployed Engineer

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Earthly Technologies Inc.
Full Time position
Listed on 2026-09-12
Job specializations:
  • Software Development
    Backend Developer, AI Engineer (Applied/Software), DevOps
Salary/Wage Range or Industry Benchmark: 160000 - 210000 USD Yearly USD 160000.00 210000.00 YEAR
Job Description & How to Apply Below

Embed with the platform and engineering teams who adopt Earthly Lunar, get them live in production, and turn their hardest standards into enforced guardrails — writing real code the whole way.

About Earthly Lunar

Earthly Lunar is a guardrails engine for the AI era
. As engineering organizations scale — and AI accelerates how much code they ship — leaders lose the ability to hold every team to their standards for quality, security, and compliance. Lunar turns those standards into automated guardrails enforced across the whole software development lifecycle — as code is written, on every pull request, and at deploy — consistently across every repo and team.

Engineering leaders get back control and real-time visibility, and compliance evidence becomes a byproduct of enforcement. Whether code comes from a developer or an AI agent, Lunar makes sure it ships right.

We're an AI-native team backed by Innovation Endeavors and Work-Bench — with angels including Jeff Dean (Google's Chief Scientist), the CEOs of Datadog and Cockroach Labs, the founder of Sentry, and the creators of Elixir, Pandas, and Ruff/uv. We're trusted by enterprise teams across defense and large-scale SaaS, and growing fast.

The role

You're a hard-core engineer who happens to love working with customers. You'll work with the platform and engineering teams evaluating and adopting Lunar — before and after the sale — and own their success end to end: prove the fit, guide the deployment into their environment, then build alongside them to turn their real-world standards into automated, enforced guardrails. You own technical delivery for each account, from first call to guardrails running in production.

Lunar is a deeply technical product. Getting it deployed means Kubernetes, Helm, CI/CD, and a Git Hub App; getting value from it means writing collectors and policies — small programs (Bash/Python) that gather signals from across a customer's SDLC (Dockerfiles, K8s manifests, Terraform, SBOMs, CI runs, VCS and vendor APIs) and evaluate them against the customer's standards. That's the same work our library, lunar-lib, is built from — and you'll own and extend it.

The patterns you build in the field flow back into the product
, so every customer benefits from the last.

This is a hands‑on engineering role: you write and own production code, and success looks like a customer's custom guardrails live and enforcing across thousands of engineers within ~90 days.

What you'll do
  • Own each account's technical track end to end. From the technical evaluation before the deal closes, through install and first guardrails live, to expansion and long-term success — the whole arc is yours.
  • Be the technical partner in the sale. Be the credible engineer in the room before the deal closes — scope the fit, prove the value on the customer's real stack, and field the hardest technical questions.
  • Guide the install, hands‑on. Stand up the self‑hosted Lunar Hub with the customer's team — Helm chart on Kubernetes, Postgres, S3, the Git Hub App, the CI agent, and Grafana dashboards — and debug it live when their environment throws you a curveball.
  • Turn standards into guardrails. Sit with a platform team, understand a real requirement — a post‑incident action item, a compliance rule, an org convention — and write the collector and policy that enforces it across all their repos and pipelines.
  • Write production code daily. Bash, Python, SQL — parsing Dockerfiles and K8s manifests, wiring up Git Hub/Git Lab and vendor APIs, normalizing messy signals into clean posture data.
  • Feed the product. Generalize what you build with customers into lunar-lib so it ships to everyone.
  • Own the fix. When a deployment breaks, you diagnose and resolve it yourself rather than filing a ticket —…
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