Trellis helps healthcare providers treat more patients faster—while eliminating pre-service paperwork.

We do this by automating document intake, prior authorizations, and appeals at scale to streamline operations and accelerate care.

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.

The Role

Forward Deployed Engineers (FDEs) at Trellis work directly with healthcare providers, pharmaceutical companies, and diagnostic labs to understand their most pressing operational challenges and implement AI-powered solutions that transform patient care. Our customers trust Trellis for mission-critical healthcare operations, and projects often start with complex questions like "How do we reduce prior authorization denial rates while accelerating patient access to life-saving treatments?" or "How can we streamline our drug program enrollment process to get patients the medications they need faster?"

🧍🏻‍♂️Why work with us

• Be at the forefront of what's possible in AI and Healthcare data.
• Work on the most important problem of our time—with direct, measurable impact.
• You will work closely with the F500 customers and the founding team. You will get to wear multiple hats from sales and marketing to recruiting.
• Extreme ownership: you will own key part of Trellis business operations and have the opportunities to start new initiatives.
• Be a part of a world-class team (e.g., team members have previously won the international physics olympiad, published economics research, were a founding engineer at Unicorn Startup, and taught AI classes to hundreds of Stanford graduate students).

Requirements

• Core Responsibilities: As an FDE, your role combines the technical depth of a senior engineer with the strategic thinking of a healthcare consultant. You'll work in small, autonomous teams with direct access to leadership and own end-to-end delivery of high-impact projects. Your day might include:
  • Technical Implementation: Architecting and building custom AI workflows, integrating with EHR systems, and developing healthcare-specific data pipelines
  • Customer Collaboration: Working directly with clinical teams, operations managers, and C-suite executives to understand workflows and optimize outcomes
  • Data Engineering: Processing and structuring complex healthcare data, from clinical notes to insurance guidelines to lab results
  • Product Development: Building custom interfaces and tools that seamlessly integrate into existing healthcare workflows
  • Strategic Planning: Establishing implementation roadmaps and success metrics for large-scale healthcare transformation projects