Note: The job is a remote job and is open to candidates in USA. FICO is seeking a Lead Harness AI Engineer to join its engineering team in the emerging discipline of Harness Engineering. The role focuses on building and owning controls, feedback loops, guardrails, tooling, and observability that help AI coding agents produce reliable, maintainable, and production-grade software. The engineer will work end-to-end from problem to production while providing technical expertise and mentoring junior team members.
Responsibilities
- Design, develop, deploy, and support components of the harness — the guides, feedback loops, guardrails, and shared context that turn raw model capability into production-grade engineering. This is a hands-on role focused on systems and leverage, not hand-writing application code
- Build feedforward guides — agent instruction files, reusable skills, architectural rules, reference docs, and codemods — that help agents get it right the first time
- Build feedback sensors — custom linters, static analysis, structural and architecture-fitness tests, verification loops, and LLM-as-judge reviewers — that catch issues before they reach human reviewers
- Run the steering loop — when an agent repeats a mistake, engineer a control so it can't happen again — and help keep repository knowledge (docs, specs, context) legible to agents, fighting drift
- Contribute to quality gating and release criteria, and to LLM testing that ensures AI-generated output meets quality and safety thresholds
- Help improve observability into agent work and track the measures that matter — cost per merged PR, time-to-merge for agent-assisted PRs, review velocity relative to PR size, defect escape rate, and agent-PR survival rate
- Evaluate the stability, compatibility, scalability, interoperability, and performance of harness components
- Continually learn new techniques in agent-augmented engineering and serve as a source of technical expertise and mentor to junior team members
Skills
- Bachelor's/Master's in Computer Science or related disciplines, or relevant experience in software architecture, design, development, and testing
- Strong software engineering background; you've worked in large codebases and care about architecture, testing, and maintainability
- Comfortable building tooling across a modern stack — linters and static analysis, CI pipelines, containerized build/test environments, and instrumentation/observability — and familiar with agent instruction conventions such as AGENTS.md
- Hands-on experience with AI coding agents (e.g. Claude Code, Codex, or similar) and a feel for where they succeed and fail
- Experience with spec-driven development, context engineering, agent orchestration, fitness functions, and developer-platform work
- A systems mindset — you'd rather fix the environment than fix one output — and the ability to encode 'what good looks like' into mechanical, repeatable rules
- Judgement about when to reach for deterministic, computational controls (type checkers, linters, structural/architecture-fitness tests) versus inferential, LLM-based ones (AI code review, LLM-as-judge) — and an understanding of the cost, speed, and reliability trade-offs between them
- Clear communicator; able to articulate design with architects and discuss strategy and requirements with teams
Company Overview
Company H1B Sponsorship