Who we are

Percepta’s mission is to transform critical institutions with applied AI. We care that industries that power the world (e.g. healthcare, manufacturing, energy) benefit from frontier technology.

To make that happen, we embed with industry-leading customers to drive AI transformation. We bring together:

• Forward-deployed expertise in engineering, product, and research

• Mosaic, our in-house toolkit for rapidly deploying agentic workflows

• Strategic partnerships with Anthropic, McKinsey, AWS, companies within the General Catalyst portfolio, and more

Our team is a quickly growing group of Applied AI Engineers, Embedded Product Managers, and Researchers motivated by diffusing the promise of AI into improvements we can feel in our day-to-day lives.

Percepta is a direct partnership with General Catalyst, a global transformation and investment company.

About the role

We’re hiring Applied AI Engineers who will work directly inside our health system, provider, and health plan partners—embedded with nurses, physicians, access teams, revenue cycle staff, IT, and operations—to build and ship AI-powered clinical and operational applications that change how care is delivered and how these organizations run.

This is not a typical engineering role. You’ll be forward-deployed into care environments, working through legacy systems, fragmented data, and high-stakes operational workflows. You will build production-grade AI agents and automation that reduce administrative burden, unlock capacity, strengthen documentation, support staffing and scheduling, and ultimately improve experiences for thousands of patients and frontline staff: foundational work for the future of U.S. healthcare delivery.

Our Applied AI Engineers:

Shape the direction for AI in hospital and payer operations

Work with executives, service-line leads, clinical operators, revenue cycle directors, and informatics teams to understand constraints, uncover bottlenecks, and translate domain knowledge into high-impact AI applications across patient flow, documentation, scheduling, staffing, quality, revenue, and supply chain.

Ship AI systems into production across complex healthcare environments

Design and deploy agentic workflows that sit on top of EHR, ERP, RCM, workforce, and payer data. Build end-to-end systems that operate within operational constraints—nurses documenting, schedulers triaging, analysts validating—and iterate quickly based on frontline feedback.

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.

Additionally, candidates who thrive in this role typically bring:

Strong product instincts shaped by operational complexity

You know how to build for clinicians, operators, schedulers, and revenue cycle teams — and understand how small design choices drive or break adoption.

Forward-deployed comfort

You’re energized by working on-site, partnering shoulder-to-shoulder with care teams, validating assumptions in live workflows, and iterating quickly.

Experience with healthcare data and infrastructure

You’ve built systems using some combination of: EHR databases, ERP platforms, RCM/claims systems, Workforce management systems using integrations and technologies such as:

• FHIR, HL7v2, CCDAs, SFTP file drops

• Databricks and similar systems

• SQL + Python service integrations

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.