Applied AI Engineer

Summary

Percepta is on a mission to transform critical institutions with applied AI, collaborating with industry-leading customers to drive AI transformation. The Applied AI Engineer will work directly with customer executives to define and deliver impactful AI systems, focusing on building production-grade AI agents and workflows that create significant business value.

Responsibilities

• 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

Skills

• 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
• 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

Qualifications

Must Haves

• 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

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, balancing craft, ownership, and speed