About the Role
As our Applied AI Engineer for Internal Tools, you will build the AI-powered systems and agentic workflows that ai& runs on internally. We are an AI company and our own operations, tooling, and workflows should be the best demonstration of what AI can do. Your job is to make that true.
You will work across every function in the company — engineering, finance, operations, data center, and HR — identifying where AI can remove friction, automate manual work, and make teams meaningfully more productive. You will build internal tools, deploy agents, integrate our own models and infrastructure into internal workflows, and continuously raise the bar on how effectively ai& uses the technology it builds.
This is a high-impact, high-visibility role. The tools you build are used by everyone in the company every day.
Responsibilities
- Internal AI Tool Development: Design and build AI-powered internal tools that make ai& teams more productive. This covers everything from internal dashboards and automation scripts to fully agentic workflows that run autonomously.
- Agentic Workflow Deployment: Identify manual, repetitive, or slow internal processes and replace them with agentic AI workflows. Deploy and maintain agents that handle internal tasks across operations, finance, engineering, and beyond.
- Model & Infrastructure Integration: Integrate ai&'s own models and inference infrastructure into internal tooling. We should be running on our own stack wherever possible and you are the person who makes that happen.
- Cross-Functional Needs Assessment: Work closely with every team to understand their workflows, identify friction points, and prioritize the AI interventions that will have the biggest impact.
- Evaluation & Iteration: Build evaluation frameworks for internal tools. Measure whether the tools you ship are actually making teams faster and better, and iterate continuously based on real usage feedback.
- Documentation & Enablement: Ensure every internal tool is documented well enough that teams can use it without hand-holding. Run internal demos and onboarding sessions when needed.
Requirements
- Applied AI Engineering Experience: You have built production AI-powered tools and agentic workflows. You know how to take a model capability and turn it into something a non-technical person can use reliably every day.
- Full-Stack Competence: Comfortable building across backend services, APIs, and simple frontend interfaces. You can own a tool end to end without needing to hand off every piece.
- Agentic Framework Fluency: Hands-on experience with agentic frameworks and tool-use patterns. You have built systems where models take actions, not just generate text.
- Cross-Functional Empathy: You understand what different business functions need from tooling. You can sit with a finance team, understand their workflow, and build something that actually fits how they work.
- Bias for Impact: You prioritize ruthlessly. You build what will make the biggest difference and you ship it fast enough that people actually use it.
- Great Team Spirit: A mission-driven approach to engineering, valuing clear communication, hands-on execution, and collective success over individual silos.