Harness Engineer, Director  

Overview

In this role you lead the new Harness Engineering team to make AI-assisted software production reliable at scale. You design and build the environment that steers AI agents toward correct, maintainable output, reducing the need for manual rework. You’ll drive governance, quality gates, and observability while shaping cross‑functional practices across the organization. This position blends hands‑on engineering with strategic leadership to accelerate responsible AI-powered development. You’ll evangelize the harness approach and mentor a distributed engineering team to raise the bar for AI-enabled engineering.

Pay / Benefits

• inclusive culture
• professional development opportunities
• competitive compensation
• work-life balance
• employee resource groups
• social events

Responsibilities

• Design and evolve the harness, guides, feedback loops, guardrails, and shared context for production-grade output
• Build and maintain feedforward guides, architectural rules, reference docs, and codemods to improve agent accuracy
• Develop feedback sensors, linters, tests, verification loops, and LLM-as-judge reviewers to catch issues automatically
• Own region AI governance: set authority boundaries, establish LLM testing infrastructure, ensure QA thresholds before release
• Define cross-organizational QA and quality-gating standards across teams and product areas
• Manage the steering loop at scale to prevent repeating classes of mistakes and treat docs/context as the system of record
• Determine where controls run in the production path for fast pre-commit checks and deeper post-integration checks
• Establish observability into agent work and track metrics like time-to-merge, defect escape rate, and PR survival rate
• Lead and develop a geographically distributed team, partner with stakeholders to attract talent and measure performance
• Collaborate with engineering leaders and product management to ensure harness alignment with roadmaps and advocates for internal enablement and thought leadership

Key requirements

• Strong software engineering background with hands-on experience in large codebases
• Experience with AI coding agents (e.g., Claude Code, Codex)
• Experience building engineering tooling: linters, CI/CD, containerized environments, observability
• Experience with spec-driven development, context engineering, agent orchestration, and fitness functions
• Systems mindset to encode good practices and automate controls
• Experience owning AI governance and cross-organizational quality standards
• Knowledge of security concerns for autonomous agents, prompt injection, sandboxing, and audit trails
• Experience managing geographically distributed engineering teams and driving organizational change
• Excellent communication skills across teams
• Bachelor’s/Master’s in Computer Science or related field, or equivalent experience

• consensus-building
• strong communication
• leadership of distributed teams
• AI coding agents (Claude Code, Codex)
• linters and static analysis
• CI/CD pipelines

…