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Artificial Intelligence, Software, Data Analytics

Member of Technical Staff (full-time, Updated)

San Francisco, California, United StatesOnsiteFull TimeStaff$100,000–$225,000 /yrPosted 2 months agoHidden Gem · YC Startup

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Role summary

Trellis is seeking a Member of Technical Staff to build and deploy AI agents that automate healthcare billing and reimbursements. This role involves designing and implementing agentic frameworks for healthcare decision-making, building 24/7 AI workers to process healthcare data, and developing production-grade AI systems. The ideal candidate will have experience in full-stack development, expertise in languages like Python or Go, and proficiency with ML/NLP libraries. Experience with databases (Postgres), data/ML infrastructure, and cloud platforms is also valued. This is a full-time role with real impact at scale in the AI in healthcare space.

## Trellis builds and deploys computer use agents to get patients access to life-saving medicine.

**Our self-improving AI agents process billions of dollars worth of therapies annually with patients in all fifty states.** We do this by automating document intake, prior authorizations, and appeals at scale to streamline operations and accelerate care. We classify medical referrals, understand chart notes, and automate contract and reimbursement search to provide patients with accurate coverage determinations and cost responsibility. Think of us as the Stripe of healthcare billing and reimbursements.

Trellis is a spinout from Stanford AI Lab and is backed by leading investors including YC, General Catalyst, Telesoft Partners, and executives at Google and Salesforce.

### **🧍🏻‍♂️Why work with us**

* **Real impact at massive scale**: We serve patients in all fifty states and are scaling to hundreds of healthcare locations. You'll directly see the number of patients who received treatment because of the agents you built.
* **Work with industry experts**: Apply your AI alongside healthcare operations leaders who have overseen 50+ healthcare locations, gaining deep domain expertise while building cutting-edge technology.
* **Be at the forefront of AI in healthcare**: Build production-grade agentic systems that make critical healthcare decisions, backed by robust evaluation frameworks.
* **Direct customer engagement**: Work closely with F500 customers and the founding team. You'll wear multiple hats from technical architecture to customer success.
* **Extreme ownership**: Own key parts of Trellis's technical infrastructure and have opportunities to launch new initiatives that process billions in healthcare transactions.
* **World-class team**: Join team members who have won international physics olympiads, published economics research, were founding engineers at unicorn startups, and taught AI classes to hundreds of Stanford graduate students.
* **Incredible growth and traction**: We've **grown revenue 10x** in the past few months alone and have **XX% market share in** the specialty healthcare markets we serve.

## **What you'll build**

* **Agentic frameworks for healthcare decision-making**: Design and implement AI systems that autonomously navigate complex reimbursement logic and prior authorization workflows.
* **24/7 AI co-workers**: Build and deploy long-running agent workers that triage and process healthcare data around the clock, functioning as reliable digital teammates for care teams.
* **Production-grade AI systems**: Develop your agents within our comprehensive evaluation suite, ensuring production-ready performance from day one.

## **Requirements**

* Experience architecting, developing, and testing full-stack code end-to-end
* Expertise in programming languages such as Python, Go and ML/NLP libraries such as PyTorch, TensorFlow, Transformers
* Being proactive and a fast-learner with bias for action
* Experience working with relational and non-relational databases, especially Postgres
* Experience with data and ML infrastructure
* Open source contributions and projects are a big plus
* Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes) is a plus
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