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- System1
- Lead AI Product Engineer - AI Agents & Emerging Products
Lead AI Product Engineer - AI Agents & Emerging Products
AI Tools
Tech Stack
Agent Workflow
Build and operate multi-agent systems. Design agent orchestration layers (planners, supervisors, evaluators). Implement agentic coding workflows where agents generate code, run tests, create diffs/PRs autonomously.
About the Role
System1 is building the next generation of AI Agent-powered consumer products, and we're looking for a Lead AI Product Engineer to help lead the effort. You'll design, build, and operate our most ambitious AI agent systems from early prototypes through production, owning core architecture, reliability, and performance as these products scale.
This role sits at the intersection of multi-agent orchestration, agentic coding, and production engineering, offering the opportunity to work on cutting-edge AI while directly influencing real-world product outcomes and business performance.
What You'll Do:
- Build and operate multi-agent systems that plan, coordinate, and execute tasks across multiple tools and services, to solve real user problems at scale.
- Implement agentic coding workflows, where agents generate code, run tests, create diffs or PRs, and iterate autonomously within guardrails.
- Design agent orchestration layers (planners, supervisors, evaluators) to manage task decomposition, retries, and long-running execution.
- Instrument and monitor agent behavior across success, failure, latency, cost, and human overrides.
What You'll Bring:
- Strong experience building LLM-powered systems in production, including prompt engineering, structured outputs, tool/function calling, and agentic coding workflows.
- Solid backend engineering skills with Python and/or Node.js, designing APIs, async services, and background workers.
- Experience designing multi-step, agent-driven execution loops (plan -> act -> evaluate -> retry).
- Comfort with distributed systems primitives (queues, pub/sub, durable state, rate limiting, concurrency controls).
- Experience with RAG architectures, vector databases, and persistent memory strategies.
- Exposure to emerging agent protocols (e.g., x402 payment flows, MCP).