Applied AI Engineer

PerceptaNew York, NY
86d

About The Position

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 Mosaic product, consistently contributing new features, patterns, and abstractions.

Requirements

  • Excited about the potential for AI to transform businesses.
  • Ability to collaborate and generate ideas with teammates and partners.
  • Willingness to take extreme ownership of tasks and projects.
  • Ability to execute quickly while maintaining quality.
  • Motivated by understanding customer pain points and iterating with end users.

Nice To Haves

  • 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.

Responsibilities

  • Collaborate with customer stakeholders to define their long-term AI strategy and transformation roadmap.
  • Surface and prioritize specific AI applications that connect our ambition to measurable business value.
  • Rapidly build and deploy AI solutions that work in the wild, with real users and real data.
  • Contribute new features, patterns, and abstractions to the Mosaic product based on customer engagements.
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