What are the responsibilities and job description for the Applied AI Engineer position at Eagle?
Who we are
Eagle is an AI holding company with a simple mission: bolster American resilience by creating the next-gen engineering services firm.
Today American infrastructure faces no shortage of challenges — from natural disaster risk and climate change to outright age and deterioration.
The problem is that the way we design infrastructure is stuck in the past.
Engineers today spend most of their time bogged down in documentation, clunky CAD software, and manual workflows — acting more like back-office admin than inventive builders.
We’re on a mission to change that.
We’re acquiring and partnering with the best engineering design firms — civil, structural, environmental, MEP, and more — to embed AI at the core of their operations and create the engineering firm of the future.
About the role
We’re hiring Applied AI Engineers who will work directly with customer executives, operators, and technical teams to define and deliver high-impact AI systems. We don't build prototypes or laboratory projects- you’ll design, build, and ship production-grade AI agents and workflows that drive millions in business value for customers.
Our Applied AI Engineers:
- Shape the AI vision: Collaborate with customer stakeholders to define their long-term AI strategy and transformation roadmap.
- Identify high-leverage use cases: Work backwards from the long-term vision to surface and prioritize specific AI applications that connect our ambition to measurable business value.
- Ship real products: Rapidly build and deploy AI solutions that work in the wild, with real users and real data.
- Advance our core product: Encode the lessons from our customer engagements in our Eagle platform, consistently contributing new features, patterns, and abstractions.
What we’re looking for
- AI-nativeness: You're excited about the potential for AI to transform businesses and want to play a hands-on role in bringing frontier technology into critical institutions.
- Being generative and collaborative: You love constantly jamming on new “what if” ideas with teammates and partners.
- Extreme ownership: You’re willing to jump in and love being the one on the hook. You aren’t going to wait to be pointed at a task—you’re going to identify what you think we should do next, and then do it.
- Execution excellence and speed: You can build stuff in messy environments and know how to get code written and shipped quickly. You can hold the balance of speed and quality and know when to push the pace vs. when to slow down.
- Customer-obsession and respect: You’re motivated by understanding customer pain points and iterating directly with end users to deliver wins quickly.
Bonus if you have
- Hands-on experience with LLM tooling (LangGraph, Mastra, Agents SDK, etc).
- Built and deployed production LLM-powered systems (tool use, RAG pipelines, multi-step agents, human-in-the-loop, etc).
- Strong technical foundations in Python/TypeScript, cloud deployment (AWS/GCP/Azure) and DevOps tooling.
- Prior startup or founding engineer experience, balancing craft, ownership, and speed.