Best suited to senior AI practitioners comfortable with healthcare domain complexities and hands-on workflow translation.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Pear Vc via Ashby
This job post is for our Toronto location. For our NYC location job post, go here https://jobs.ashbyhq.com/Pear-VC/489d22ab-558f-4702-975b-e44c4d413205.
Paxos Health https://www.paxoshealth.com is a Stanford-founded healthcare AI startup that has raised >$5M in venture capital. We have AI agents deployed in production and a healthy pipeline of customers.
Come build AI agents with us! Paxos Health is on a mission to help patients access the medical technologies their doctors prescribe. Too often, even when a physician decides a patient needs a healthcare product (cancer tests, genetic diagnostics, prosthetics, heart valves, neurostimulation devices, home medical equipment, etc.), health insurance companies deny coverage because the evidence, policy, and documentation requirements are complex and inconsistent. Patients don’t get treated, and breakthrough technologies struggle to reach the people they were built to help.
We help healthcare manufacturers fight for coverage patient-by-patient. Paxos uses LLMs to turn messy clinical records, payer rules, PDFs, portals, faxes, and reimbursement logic into rigorous prior authorizations and appeals to get patients covered. Before LLMs, this work was too difficult to use AI technology for, and human teams were forced to cut corners to get through all of the patient cases. But now, AI can help manufacturers meet increasingly complex insurer requirements and get more patients access to care.
Our progress so far:
- Five medtech and lab diagnostics companies as customers, with 40+ companies in pipeline
- $182K in recognized revenue, with line of sight to $1M ARR by late summer
- 9 of our last 10 demo calls came through referrals, word of mouth, or thought leadership
- Raised >$5M across two VC rounds, including our recently closed Seed
- Won the Stanford Impact Founder and IDIF fellowships. Check out the Stanford article about us https://www.gsb.stanford.edu/experience/news-history/haley-king-mba-24-addressing-gaps-us-health-insurance-coverage and Haley’s LOWkeynotes talk. https://www.youtube.com/watch?v=28azd1OqC9Y&ab_channel=StanfordGraduateSchoolofBusiness
So far, we've deployed LLMs for written documentation workflows and voice AI, and we want to expand those and build out computer-use agents as well.
ABOUT THE ROLE
Paxos Health https://www.paxoshealth.com/ is looking for a hands-on Founding Applied AI Lead to design and own the AI agents and workflows that make this possible. (Note that the job title itself is flexible based on candidate preferences.)
You'll be building the applied AI layer for a high-stakes healthcare workflow from the ground-up. You’ll sit at the intersection of product, engineering, AI, and customer implementation. You’ll translate messy manual workflows into reliable AI systems that are used in the real world, which includes prompt chains, structured-output schemas, evals, workflow specs, and implementation logic.
Our agents have to ingest long, inconsistent PDFs; extract facts from clinical records; map those facts to payer-specific medical necessity rules; cite evidence; generate structured outputs; handle edge cases; and fail safely when the evidence is incomplete. The challenge is turning probabilistic LLM behavior into reliable, auditable workflows that customers trust in production. We've succeeded with the customers we've had so far, and we want to scale our AI to many more.
This is not a traditional backend engineering role, but it is deeply hands-on. You should be comfortable prototyping, debugging, inspecting structured outputs, working with JSON/API-shaped data, testing workflows, and collaborating with engineering to turn prototypes into production behavior.
As an early employee, there is a significant opportunity to grow the scope of your role as our company expands. Because this is a founding role, you won’t just operate workflows; you’ll help define Paxos’s applied-AI system architecture.
RESPONSIBILITIES
- Design, improve, and own Paxos’s AI. This includes prompt chains, agent patterns, structured-output schemas, and eval harnesses that power customer implementations in documentation workflows, voice AI agents, and computer-use agents.
- Turn reimbursement complexity into testable workflow logic. Translate payer rules, document requirements, clinical evidence standards, and operational edge cases into clear AI system behavior.
- Ensure AI quality and reliability. Analyze failures, improve prompts and schemas, and build evals that catch issues before they reach production.
- Work directly with customers during implementation. Clarify requirements, understand edge cases, and translate what we learn into workflows and reusable Paxos capabilities.
- Document how the system works. Write workflow specs, test plans, prompt/eval documentation, and implementation notes that help the team build and improve faster.
- Guide our overall AI strategy, including voice AI, computer-use agents, automated prompt-writing, etc.
For example, you might turn a payer policy into a structured decision tree, design an eval set for appeal quality, create a reusable prompt pattern for extracting clinical evidence from records, debug why an AI workflow failed on a customer case, and write the implementation spec that engineering and ops use to deploy it.
What this role is not:
- This is not a people-management role at the outset. You’ll be hands-on and work closely with the whole team.
- This is not a 100% customer-facing role. You’ll work with customers, but much of your time will be spent optimizing the AI workflows and working with our team. The split will be ~75% AI agent ownership and ~25% customer-facing product development.
- This is not a pure software engineering role. (If the person we hire has a software engineering background, they can write some production code, but coding will not be a majority of the role.)
- This is not an AI research role. You’ll apply LLMs to real workflows, not train models or write research papers.
- This is not a large-company role with narrow responsibilities. You’ll work in a fast-moving startup where ownership matters more than rigid job boundaries.
REQUIREMENTS
We also welcome candidates with many more years of experience than these minimum requirements, and the role can scale up in scope and higher within the compensation range.
- Minimum 2+ years of work experience in any one of the following: forward-deployed engineering, technical implementation, AI operations, software engineering, software technical writing, technical customer success, or related work.
- AI-obsessed: you actively experiment with LLMs, and you believe AI will reshape how real-world operations work. You use AI daily, build side projects/automations/agents, experiment with new models/tools quickly, and have strong opinions from actual usage. We care about this much more than pedigree.
- Communication skills: strong English written and verbal communication.
- Extreme detail-orientation: you notice edge cases, inconsistencies, missing requirements, and quality issues that others overlook.
- Customer-facing: comfortable interacting directly with enterprise customers.
- High ownership: comfortable operating in a fast-moving startup environment where processes are still being built.
- Based near New York City or Toronto, or willing to relocate. This is an in-person / hybrid (minimum 3 days per week in the office) role with the Paxos team.
NICE TO HAVE
None of the below qualifications are strictly required.
- You have built LLM agents, automations, prompt chains, or AI workflows for work, side projects, or your own productivity.
- You have experience writing technical specs, implementation docs, workflow documentation, test plans, or customer-facing technical materials.
- You have worked with structured data, JSON, APIs, low-code tools, workflow builders, or lightweight scripting.
- You have designed or mainta
Source: Pear Vc careers (Ashby)