Init Intelligence — Senior/Staff Applied AI Engineer, Agent Harness
OtherApplied Ai Engineer
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Quick Summary
Key Responsibilities
execution loop, tool-use strategies, context construction,
Technical Tools
OtherApplied Ai Engineer
Responsibilities
~1 min read- →Own the core agent harness: execution loop, tool-use strategies, context construction, and model-facing experimentation
- →Shape agent behavior across real customer workflows and long-horizon tasks
- →Own the line between runtime model decisions and deterministic, compiled execution
- →Build and run evals against replicas of real customer environments — reliable enough to gate a release
- →Diagnose production failures and attribute them to the right layer (model, prompt, tool contract, environment state, retry logic), then harden the system
- →Extend computer-use to systems that have no API, with real production guarantees (isolated per-task sandbox, model-blind credential handling, full action recording, killable sessions)
- →Build the feedback loops and data systems that feed better real-task data into eval and training
Tech stack: Python or TypeScript, modern AI tooling, agent-harness / execution-loop engineering, evals, sandboxed (microVM) execution, computer-use / browser automation.
Requirements
~1 min read- Hands-on experience building with agent frameworks or tool-using LLM systems
- Strong programming ability in Python or TypeScript, and fluency with current AI tooling
- Practical experience across model evaluation, fine-tuning, and/or prompt design
- Comfortable owning systems end-to-end and debugging across the full stack
- Frame problems around systems and real user outcomes, not just model benchmarks
- Genuinely enjoy chasing down messy real-world failures and turning them into durable fixes
- Motivated to work at the layer where model capability becomes dependable product
- Able to work on-site in San Francisco, Monday–Friday, at startup pace
Nice to Have
~1 min read- A standout signal of excellence somewhere — leading a meaningful team at a high-growth company, top competitive-programming results, or elite achievement in a craft, sport, or game
- A CS or engineering degree from a top program, or equivalent genuinely exceptional experience
- Time at a strong company on a high-caliber, directly relevant team (agents / AI infrastructure)
- A track record of shipping agents that actually hold up in production
- High agency — former founders, broad scope, comfort operating amid real ambiguity
- Experience building computer-use or browser-automation agents
- Familiarity with virtualization and sandboxed execution environments, and scaling them
- Published AI research at top conferences
- Shipped systems where correctness had to survive partial failure (idempotency, resumability, compensating actions)
- Integrated enterprise SaaS APIs (identity providers, directory services, ticketing, ERPs)
- Comfort working with large, messy datasets or production logs
- Early-engineer experience in a seat where you also talked to customers
What We Offer
~1 min read✓Ground-floor ownership of the core agent harness at a well-backed, security-focused AI startup
✓A meaningful equity stake (1%–2%) at the seed stage
✓Hard, real engineering — production-grade evals, isolated execution, and computer-use on systems with no API, not throwaway demos
✓Small founding team, broad scope, and direct impact on what ships
- Location — San Francisco, CA
- Work policy — On-site, Monday–Friday, startup intensity
- Compensation — $200,000–$300,000 + 1%–2% equity
- Visa sponsorship — Available (H-1B, O-1, OPT)
- Employment type — Full-time
- Benefits — Meals in office, health insurance, unlimited PTO
Location & Eligibility
Where is the job
San Francisco, United States
On-site at the office
Who can apply
US
About this job
- Who can apply
- United States
- Posted
- 88 days ago
Listing Details
- First seen
- August 11, 2026
- Last seen
- September 2, 2026
Posting Health
- Days active
- 88
- Repost count
- 0
- Trust Level
- 19%
- Scored at
- November 7, 2026
Signal breakdown
freshnesssource trustcontent trustemployer trust
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