Staff AI Systems Engineer - Autonomous Agents (Remote)

People in AI; United States; Remote; USD 400,000 - 500,000; Full time

Benefits offered by this job

Fully remote across the United States

Equity + bonus

Job summary

People In AI is seeking a highly capable Member of Technical Staff to drive the next generation of AI agent systems. This high-ownership role focuses on core AI capabilities, multi-agent architectures, and scalable infrastructure, at the intersection of applied AI and production-grade software engineering.

You will own ambitious technical projects from concept through production, shape the platform architecture, and tackle open-ended challenges in enterprise AI across a fully remote US-based

Qualifications

• Extensive software engineering background with production-grade delivery.
• Experience building AI agents or multi-agent systems in production.
• Strong understanding of agent orchestration, distributed systems and scalable architecture.
• Experience owning and delivering complex technical products end to end.

Responsibilities

• Design and build advanced multi-agent systems, agent runtimes, and orchestration frameworks.
• Develop new capabilities for autonomous agent generation, reasoning, and execution.
• Architect scalable infrastructure supporting complex enterprise AI workflows.
• Own ambitious technical projects from concept through production.
• Shape the technical roadmap and core platform architecture.
• Solve challenging, open-ended problems in applied AI.

Skills

Software engineering

AI agents

Distributed systems

Technical judgment

Startup environment

Tools

Agent runtimes

Orchestration frameworks

Job description

People In AI is seeking a highly capable Member of Technical Staff to drive the next generation of AI agent systems. This high-ownership role focuses on core AI capabilities, multi-agent architectures, and scalable infrastructure, at the intersection of applied AI and production-grade software engineering.

You will own ambitious technical projects from concept through production, shape the platform architecture, and tackle open-ended challenges in enterprise AI across a fully remote US-based