Note: The job is a remote job and is open to candidates in USA. Truss is a fintech company building banking and payments products for construction businesses. The Forward-Deployed AI Engineer will own production internal AI systems, including the AI harness and fraud/customer-support back office, while improving engineering environments, agent skills, repository contracts, quality loops, and AI-enabled development processes.
Responsibilities
- **Own the internal AI harness.** It exists. You maintain it, harden it, and keep building it full time. Evals, tool wiring, sandboxes, whatever makes agents reliable here
- **Own the AI back office.** Fraud and customer support already run on an AI-built back office. You extend it, keep it correct, and sit with ops when a case flow is wrong. This is production, not a demo
- **Make every engineer's environment actually work.** Cursor, agent runtimes, virtualenvs, VMs, secrets, language toolchains. When someone clones a repo, the agent can boot, test, and ship. You notice when it cannot
- **Own team skill sets.** Shared skills for our stack and our way of working. You keep them current. Stale skills are a bug you fix, not a wiki someone might read
- **Set the repos up for agents, not just humans.** Devcontainers or equivalent, task runners, test entrypoints, lint, fixtures, docs the model can follow. The factory has a contract
- **Build jobs that scrape the work.** Daily signal on what shipped, review quality, test health, agent usage, where we are slow or sloppy. Improve the factory. Do not build a vanity dashboard
- **Install process that sticks.** How we open PRs, how we review with agents, how we promote a skill, how we kill a bad one. Boring, enforced, light
- **Sit with the people who use it.** Engineers and ops. You watch a session or a case fail and fix the harness, the skill, or the back office. You do not throw a Notion page over the wall
Skills
- 6+ years as an engineer, shipping production software
- A harness, an eval framework, an agent/skill system, or a meaningful open-source contribution in this area
- You have set up other people's environments, not only your own
- You treat harnesses, skills, and the back office like production code: versioned, reviewed, deprecated when they rot
- Comfortable in Python/TypeScript or similar: CI, scrapers, MCP/tool servers, sandboxes, ops UIs
- Small-team operator
- Must meet the location / work-auth rules in Sanity Check
- Remote (US or Canada)
- TN is OK if you are Canadian
- We are not sponsoring other visas
- You have been a working engineer for at least six years
- We do expect you have shipped real software for a long time, and that the AI/agent work is the reason you want this job
- A harness, an eval loop, an agent skill pack, or a real open-source contribution we can click
- Proof we can click: a harness, an eval framework, an agent/skill system, or a meaningful open-source contribution in this area
- You have set up other people's environments, not only your own. Dotfiles-as-theater does not count. Repos that boot, tests that run, agents that have the tools they need
- You treat harnesses, skills, and the back office like production code: versioned, reviewed, deprecated when they rot. Comfortable in Python/TypeScript or similar: CI, scrapers, MCP/tool servers, sandboxes, ops UIs
- Must meet the location / work-auth rules in Sanity Check
- You have already run a shared Cursor / Claude Code / Codex (or similar) setup across a team
- Published evals, SWE-bench-style loops, or sandbox/VM runners
- Contributions to Hermes, Claude Code skills, Aider, Continue, OpenHands, or similar
- You have shipped AI into an ops/fraud/support workflow, not only coding agents
- You have opinions on skills vs memory vs evals, and scars to match
- Optional: 3-8 minute Loom walking through the harness or OSS work (no secrets)
Benefits
- Equity 0.25% – 0.50%.
- Remote in the US or Canada
- Real ownership of internal AI (harness + back office) and how the eng team uses it
- Medical/dental/vision
- 401(k)
- Reasonable PTO
- Equipment
- A small, sharp team. Zero bureaucracy. High leverage.
Company Overview