AI Agents Engineer — Remote, Equity

People in AI; United States; Remote; USD 230,000 - 275,000; Full time

Job summary

People In AI is building an early-stage applied AI company focused on enterprise workflows. We are hiring a role to own production AI agents end-to-end, from customer dialogue through architecture, deployment, and production support, with deep collaboration across backend, AI, data, and product teams.

You will work remotely from the USA, enabling direct customer impact, highly visible ownership, and the ability to shape the agent infrastructure and autonomous workflow execution for real

Qualifications

• Experience building production AI agents in a company.
• End-to-end ownership of systems that reach real users.
• Strong backend software engineering fundamentals.
• Experience with LLMs, agents, orchestration, or AI-driven workflows.
• Ability to discuss architecture decisions, failure modes, debugging, reliability, and production tradeoffs.

Responsibilities

• Build and own production AI agents used in real enterprise workflows.
• Take customer problems from initial scope through architecture, implementation, deployment, and iteration.
• Integrate agents with enterprise systems, APIs, operational data, and existing workflows.
• Work with fragmented and overlapping data sources to create usable business context.
• Design reliable backend systems supporting production agent execution.
• Diagnose agent failures, reliability issues, and production behaviour.

Skills

Production AI agents

End-to-end ownership

Backend fundamentals

LLMs & AI workflows

Architecture discussions

Tools

APIs

Orchestration

Job description

People In AI is building an early-stage applied AI company focused on enterprise workflows. We are hiring a role to own production AI agents end-to-end, from customer dialogue through architecture, deployment, and production support, with deep collaboration across backend, AI, data, and product teams.

You will work remotely from the USA, enabling direct customer impact, highly visible ownership, and the ability to shape the agent infrastructure and autonomous workflow execution for real