AI Engineer - AI Agents

Hatch engineering culture is driven by speed, ownership, and impact. We're a small, ambitious team building AI that transforms how service businesses grow, and we move fast. Engineers own problems end to end, ship to production early, and work across a modern stack (Elixir, Python, Go, React + TypeScript) on problems that directly shape the customer experience. At the end of the day, we're here to build something that matters, grow as engineers, and do it together.

As part of the AI agents team, you'll work at the intersection of classic product engineering and AI - building the underlying systems that let our AI agents reason, act, and improve. Your work has a direct, measurable line to customer revenue.

This opportunity requires you to be located in the United States.

We'd love to have you apply, even if you don't feel you meet every single requirement in this posting. At Hatch, we're looking for great people, not just those who simply check off all the boxes.

What You'll Do:

• Design, build, and own the systems that power our Voice AI and Text AI agents - handling voice calls, SMS, and email conversations end-to-end across every customer touchpoint.
• Craft system-level prompts that shape agent behavior, reliability, and outcomes, with a deep understanding of how prompt structure translates into real-world performance.
• Develop tool-calling integrations so agents can take reliable, real-world actions - booking appointments, looking up customer data and warm-transferring to humans - safely and predictably.
• Build LLM-as-a-judge evaluations and AI observability - telemetry, traces, and quality dashboards - to measure agent performance, catch regressions, and continuously raise the bar on reliability.
• Partner closely with product and design - bring a sharp product sense to every feature, balancing user needs, business goals, and technical trade-offs.
• Apply industry-standard engineering practices: Thorough code review, automated testing, CI/CD, progressive delivery with feature flags and A/B experimentation, observability, and clear technical documentation.
• Mentor and guide junior engineers, fostering a culture of learning and technical excellence.

What it Takes to Succeed:

• Hands-on experience building with LLMs in production - prompt engineering, tool/function calling, evaluation frameworks, or agent orchestration.
• Solid backend experience in one or more of Elixir, Go, Python, or a comparable server-side language, with the curiosity and adaptability to pick up new languages and frameworks as our stack evolves.
• Comfort working across the stack, from data model and LLM/agent logic to APIs and (where needed) UI.
• A track record of leading projects from spec to launch alongside multiple contributors.
• Deep sense of ownership and bias for action - you take ambiguous problems from start to finish, work across team boundaries to unblock yourself, and stay accountable through delivery.
• Clear communication skills and the ability to collaborate effectively with technical and non-technical stakeholders.
• Eager to keep up with the ever-changing landscape of AI capabilities - actively exploring new models, tools, and techniques, and thoughtfully applying them to your work and to the product.