# Staff AI Engineer - Agent Architecture & Behavior

**Company:** [Artisan](https://hotfix.jobs/companies/artisan)
**Location:** San Francisco, CA
**Role:** ML Engineering
**Salary:** $250k – $325k/yr
**Experience:** 7+ years
**Skills:** Python, TypeScript, Llm Tool Use, Multi-Agent Systems, Context Engineering, Browser Automation, Computer Automation, Asynchronous Services, State Machines, Concurrency, Distributed Systems, Reinforcement Learning, Sandboxed Execution, Observability, Inference Optimization
**Posted:** 2026-09-13

> Staff AI Engineer responsible for designing and shipping agent architecture, multi-agent coordination, reliable execution, memory, tooling, and evaluation systems. Requires substantial shipped agentic-system experience and strong software engineering skills in Python, TypeScript, or a comparable language.

## Job Description

## Responsibilities
- Design and implement agent execution loops, planning strategies, tool interfaces, verification, and system boundaries.
- Build multi-agent delegation, coordination, context sharing, result synthesis, concurrency handling, cancellation, and stale-result management.
- Develop resilient stateful workflows with checkpoints, recovery strategies, partial-failure handling, and human intervention.
- Improve retrieval, context construction, persistent state, memory, and reusable skill representation.
- Build evaluations, analyze task trajectories, and measure quality, reliability, latency, and cost improvements.
- Evaluate models and emerging techniques; make build-versus-buy decisions and replace tools when evidence changes.
- Set engineering standards, review architecture and design decisions, and provide technical leadership as an individual contributor.
- Partner with product and infrastructure engineers on production services, integrations, secure execution, and observability.

## Requirements
- Demonstrated experience building and shipping a substantial agentic system through production use or rigorous, reproducible open-source work.
- Deep practical experience with LLM tool use, planning, context engineering, evaluations, and multi-agent coordination or parallel agent/tool execution.
- Hands-on experience with browser or computer automation in an agentic system, including state observation, effect verification, and failure recovery.
- Strong software engineering skills in Python, TypeScript, or a comparable language.
- Experience with asynchronous services, state machines, persistence, concurrency, retries, and cancellation.
- Ability to distinguish model decisions from guarantees that must be enforced in code, including permissions, untrusted inputs, uncertain outcomes, and human approvals.
- Ability to design experiments, debug real system behavior, and explain measured improvements and remaining uncertainty.
- Ability to take ownership of ambiguous problems, collaborate effectively, and ship high-quality software.

## Nice-to-haves
- Agent memory and retrieval
- Skill acquisition
- Reinforcement learning or post-training
- Trajectory datasets
- Sandboxed execution
- Distributed systems
- Inference optimization
- Multimodal models
- Voice models

## Compensation
- Base salary: $250,000–$325,000 USD annually.
- Equity: 0.15%–0.30%.
- US visa sponsorship available.

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