---
title: 'Applied AI Software Engineer at Canvasmedical'
canonical: 'https://feeny.ai/job/applied-ai-software-engineer-canvasmedical-san-francisco-a96xabdp0jnz'
type: 'job'
last_seen: '2026-09-09'
---

# Applied AI Software Engineer at Canvasmedical

- **Company:** Canvasmedical
- **Location:** San Francisco, CA
- **Compensation:** $300k–$400k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2025-06-04
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.lever.co/canvasmedical/188bcb78-cf6d-4ceb-a6de-f5b0556bc8df

## Job description

Canvas Medical is the electronic medical records (EMR) and payments development platform for healthcare. We build modern, elegant front- and back-end tooling to enable new ways for developers and clinicians to collaborate to solve healthcare’s toughest challenges. Canvas is institutionally backed by some of the greatest technology investors in the world (funded notable health tech companies such as GoodRx, Oscar Health, and Hims & Hers Health).

## The Role

We’re hiring an Applied AI Software Engineer to lead evaluations for agents in development and the post-deployment fleet of agents operating in Canvas to automate work for our customers. You will help develop agents in Canvas using state of the art foundation model inference and fine-tuning APIs along with our server-side SDK. The server-side SDK provides extensive tools and virtually all the context necessary for excellent agent performance. You’ll be responsible for designing and running rigorous evaluation experiments that measure performance, safety, and reliability across a wide variety of clinical, operational, and financial use cases.

This role is ideal for someone with deep experience evaluating LLM-based agents at scale. You’ll create high-fidelity unit evals and end-to-end evaluations, define expert-determined ground truth outcomes, and manage iterations across model variants, prompts, tool use, and context window configurations. Your work will directly inform model selection, fine-tuning, and go/no-go decisions for AI features used in production settings. You’ll collaborate with product, ML engineering, and clinical informatics teams to ensure that Canvas's AI agents are not only capable, but trustworthy and robust under real-world healthcare constraints. You will also work with technical product marketers and developer advocates to help our broader developer community and the broader market understand the uniquely differentiated value of agents in Canvas.

## Who You Are

- You have extensive hands-on experience evaluating LLM-based systems, including multi-agent architectures and prompt-based pipelines.
- You are deeply familiar with foundation model APIs (OpenAI, Claude, Gemini, etc.) and how to systematically benchmark agent performance using those models in applied settings.
- You care about correctness and reproducibility and have built or contributed to frameworks for automated evals, annotation pipelines, and experiment tracking.
- You bring structure to ambiguity and know how to define “correctness” in complex, nuanced domains.
- You are comfortable collaborating across engineering, product, and clinical subject matter experts.
- You are not afraid of complexity and are energized by the rigor required in healthcare deployments.

## What You’ll Do

- Design and execute large-scale evaluation plans for LLM-based agents performing clinical documentation, scheduling, billing, communications, and general workflow automation tasks.
- Build end-to-end test harnesses that validate model behavior under different configurations (prompt templates, context sources, tool availability, etc.).
- Partner with clinicians to define accurate expected outcomes (gold standard) for performance comparisons in domains of clinical consequence, and partner with other subject matter experts in other non-clinical domains.
- Run and replicate experiments across multiple models, parameters, and interaction types to determine optimal configurations.
- Deploy and maintain ongoing sampling for post-deployment governance of agent fleets.
- Analyze results and summarize tradeoffs in clarity for product and engineering stakeholders, as well as for technical stakeholders among our customers and the broader market.
- Take ownership over internal eval tooling and infrastructure, ensuring speed, rigor, and reproducibility.
- Identify and recommend candidates for reinforcement fine-tuning or retrieval augmentation based on gaps identified in evals.

What Success Looks Like at 90 Days

- An expanded set of robust evaluation suites exists for all major AI features currently in development and in production.
- We have well-defined correctness criteria for each workflow and a reliable source of expert-determined outcome objects.
- Product and engineering teams have integrated your evaluation tools into their daily workflows.
- Evaluation results are clearly documented and reproducible, enabling trust in the performance trajectory.
- Your have effectively engaged your marketing counterparts to translate your work into key messages to the market and to Canvas customers.

## Qualifications

- 5+ years of experience in applied machine learning or AI engineering, with a focus on evaluation and benchmarking.
- Proficiency with foundation model APIs and experience orchestrating complex agent behaviors via prompts or tools.
- Experience designing and running high-throughput evaluation pipelines, ideally including human-in-the-loop or expert-labeled benchmarks.
- Superlative Python engineering skills and familiarity with experiment management tools and data engineering toolsets in general including, yes, SQL and database management.
- Familiarity with clinical or healthcare data is a strong plus.
- Experience with reinforcement fine-tuning, model monitoring, or RLHF is a plus.
- Research shows that women and other minority groups might avoid applying if they don’t meet 100% of the qualifications. We encourage you to apply even if you don’t meet everything listed in the job posting.

Canvas Medical provides equal employment opportunities to all employees and applicants for employment without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

## About Canvasmedical

## Company Overview
- **One-liner**: Canvas Medical provides an AI-powered, programmable electronic medical records (EMR) and healthcare platform that enables clinics and care delivery organizations to launch new patient experiences, automate workflows, and orchestrate care services and payments.
- **Entity Type**: Private (Series B, $44M total funding)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2015
- **Founders**: Andrew Hines

## Core Business
- **Primary industry**: Healthcare IT & Services
- **Target customers**: B2B – Ambulatory clinics (primary care, urgent care, specialty), direct-to-consumer telehealth startups, large health plans (payer-provider collaborations), and established medical groups.
- **Mission or purpose**: To give care teams superpowers with software [canvasmedical.com](https://www.canvasmedical.com/careers).

## Products & Services
- **Canvas Platform (Programmable EMR)**: A core electronic medical record system with pre-built workflows for primary care, weight loss, longevity, cardiovascular, mental health, chronic care management, and urgent care. Includes native FHIR integration and a developer toolkit (API, SDK) for extensibility.
- **Hyperscribe (AI Clinical Copilot)**: An AI agent designed to automate complex clinical, operational, and financial workflows end-to-end, providing comprehensive patient context.
- **Canvas Payments & Patient Engagement**: Integrated tools for patient-side scheduling, messaging, payments, and medical records, also available as an open-source initiative.

## Market Standing
- **Valuation**: Not publicly disclosed.
- **Key Metrics**: Annual Revenue of **$6M** [LinkedIn](https://www.linkedin.com/company/canvas-medical). Total Funding of **$44M**.
- **Notable Investors/Partners**: Upfront Ventures (Seed lead), IA Ventures and Inspired Capital Partners (Series A lead), M13 (Series B lead).
- **Growth Signals**: Headcount grew **+10.3% YoY** to 27 employees [LinkedIn](https://www.linkedin.com/company/canvas-medical). Active job postings increased **+250% in the last year** (7 open roles). Released first AI product (Clinical Copilot / Hyperscribe) and an open-source patient engagement suite. Achieved ONC certification for meaningful use requirements.

## Competitive Advantages
- **Deeply Programmable & Extensible**: Offers a true Programmable EMR with an API-first approach, SDK, and plugin architecture, allowing customers to build custom workflows instead of conforming to rigid software.
- **Unified Architecture**: A "single source of truth" centered on the patient record, which integrates clinical, operational, and financial data in one deep unified architecture.
- **AI-Native Automation**: The Hyperscribe AI agent automates end-to-end workflows, going beyond basic charting to handle complex financial and operational tasks.
- **Experienced Leadership**: Founding team includes deep expertise in healthcare (CTO Andrew Hines’ background as a data scientist), software engineering (Beau Gunderson, author of widely downloaded open-source tools), and go-to-market (CEO Adam Farren, former Chief Growth Officer).

## Strategic Focus
- **AI Productization**: Scaling the Hyperscribe clinical co-pilot and AI agents to automate increasingly complex clinical and administrative tasks.
- **Platform Expansion**: Continuing to build out the developer tooling (CPA agent powered by Claude Code) and plugin ecosystem to make the platform more customizable for different care models (weight loss, longevity, mental health).
- **Market Diversification**: Winning clients from small telehealth startups to large health plans (e.g., 40-million-member health plans), indicating an ambition to serve the entire care delivery spectrum.
- **Patient Engagement & Payments**: Deepening the integrated patient experience and payment orchestration capabilities to enable "new patient experiences and business models."

## Why Work Here
- **Remote-First & Distributed**: Engineering and Operations roles are listed as fully remote, with a distributed team across the US and Portugal [lever.co](https://jobs.lever.co/canvasmedical).
- **High-Impact Mission**: Directly working on software intended to "accelerate everyday medicine" and improve the lives of clinicians and patients.
- **Engineering Culture**: Led by Chief Engineering Officer Beau Gunderson (27 years of experience, author of widely used open-source software), the team focuses on developer tooling, open-source projects, and building a platform from the ground up.
- **Growth Stage**: The company is past the bootstrapping phase but still small (27 employees) and actively scaling its engineering, product, and go-to-market teams (7 open positions as of the latest data, with 250% YoY growth in job postings).
- **Total Compensation & Culture**: On a 5-review scale, compensation is rated **4.0/5**, with work-life balance at **3.3/5**. Culture and career growth are listed as **1.5/5** and **2.6/5** respectively, suggesting a demanding startup environment with high compensation but potential intensity [LinkedIn](https://www.linkedin.com/company/canvas-medical).

## Sources
1. [canvasmedical.com (About Page)](https://www.canvasmedical.com/about)
2. [canvasmedical.com (Main Site)](https://www.canvasmedical.com/)
3. [canvasmedical.com (Careers Page)](https://www.canvasmedical.com/careers)
4. [LinkedIn Company Profile](https://www.linkedin.com/company/canvas-medical)
5. [jobs.lever.co (Canvas Medical)](https://jobs.lever.co/canvasmedical)

## Other roles at Canvasmedical

- [Applied AI Operations Lead](https://feeny.ai/job/applied-ai-operations-lead-canvasmedical-san-francisco-enmsjcq0yxe6) — San Francisco, CA
- [Solutions Consultant](https://feeny.ai/job/solutions-consultant-canvasmedical-san-francisco-6bm60cnwnzza) — San Francisco, CA
- [Solutions Engineer](https://feeny.ai/job/solutions-engineer-canvasmedical-san-francisco-vbjchnxby9xp) — San Francisco, CA
- [Developer Advocate](https://feeny.ai/job/developer-advocate-canvasmedical-san-francisco-5z8at94hk3jy) — San Francisco, CA
- [Account Executive](https://feeny.ai/job/account-executive-canvasmedical-san-francisco-x2vrqc1vv05f) — San Francisco, CA
- [Applied AI Software Engineer](https://feeny.ai/job/applied-ai-software-engineer-blossom-health-new-york-bb95kcqp6z0t) — New York, NY
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