Software Engineer, AI Agents

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

Compensation: $230,000 - $275,000 base + equity

Location: Remote, USA

Join an early-stage applied AI company building the infrastructure and agent layer required to automate complex enterprise knowledge work. The company is already seeing exceptional commercial traction and is now expanding a very small engineering team behind that growth.

The Mission

The company is building AI systems that can understand how businesses actually operate. That means connecting fragmented enterprise systems, working through messy operational data, creating a unified business context layer, and deploying agents directly into real workflows.

The Role

You will take ambiguous business problems from initial customer conversation through architecture and production deployment. You'll work directly with customers to understand their objectives, inspect source systems and data, determine what is technically possible, and build a working V1. At the same time, you'll contribute to the core platform and help solve harder technical problems around agent infrastructure, enterprise data, ontology generation, and autonomous workflow execution.

What You'll Do

• 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 unexpected production behaviour.

What You'll Bring

• Meaningful experience personally building production AI agents inside a company.
• Clear end-to-end ownership of systems that reached real users or business workflows.
• Strong backend software engineering fundamentals.
• Experience working with LLMs, agents, orchestration, tools, APIs, or AI-driven workflows.
• Ability to discuss architecture decisions, failure modes, debugging, reliability, and production tradeoffs in depth.
• Comfort working across backend engineering, AI, data, infrastructure, and product.

Why Join?

• Join at a rare stage where commercial traction has arrived before the organization has meaningfully scaled.
• Take significantly more technical and customer ownership than you would in a traditional engineering role.
• Work directly with founders on hard AI and enterprise infrastructure problems.
• Build systems that solve measurable business problems rather than isolated demos or proofs of concept.
• Contribute to both customer-facing AI deployments and the underlying platform powering them.
• Gain unusually broad exposure across technology, customers, product, and commercial decision-making.

About People In AI

We partner with AI-first startups, scale-ups, and enterprise organizations to connect exceptional engineers with opportunities to build production AI systems, intelligent platforms, and the next generation of enterprise AI.