Software Engineer, Applied AI
At a glance
Mid-level AI Engineering role at Lassie. San Francisco · full-time · no salary stated · we estimate $183,750–$246,250.
Lassie has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Build AI agents that complete the workflows keeping doctors’ offices running
- Work across agent design, data pipelines, evaluation and the infrastructure supporting reliable production systems
- Investigate live incidents and resolve them while keeping disruption to a minimum
- Create engineering tools and automation that make development faster and safer
- Design data schemas and pipelines for large datasets used in applied AI
What you bring
- You’re excited to build with frontier models
- You prioritize dependable, correct behavior over simply getting a feature to work
- You can troubleshoot and address issues in live production systems
- You’re comfortable with databases, caches, proxies and job orchestration systems
Who this fits
This mid-level engineering role suits someone who wants to work across the stack on applied AI systems. The hiring process includes team and founder conversations, followed by an office visit for a small project and team meetings.
From the employer
Our mission is to help small businesses run themselves. We’re starting with doctors’ offices, building autonomous systems that handle busywork and complete the workflows that keep the office moving every day. Our team is small, flat, and ambitious. We value craft, intellectual rigor, and direct communication.
About the role
We're hiring an engineer to build the AI agents that run doctor's offices.
These are production systems handling real money and real patient data for thousands of practices. You'll work across the full stack: agent architectures, data pipelines, evals, and the infrastructure that makes it all reliable.
You will be a great fit if you…
Are excited to work with frontier models
Engineer for reliability and correctness, not just functionality
Diagnose and resolve live production incidents with minimal disruption
Automate away repetitive work and build tooling that makes engineering faster and safer
Design schemas and pipelines for large-scale datasets to power applied AI
Are comfortable working across databases, caches, proxies, and job orchestration systems
Some things we've built
Data pipelines processing $1B+ in insurance claims
Systems that eliminate thousands of hours of paperwork every month
A sync engine backed by encrypted SQLite in the browser, enabling 100ms experiences for healthcare payments and patient ledgers
Technology we use
We invest heavily in productivity. Engineers should have the best tools for the job and the freedom to choose them.
Python (Django, Pydantic AI), Postgres, Redis
TypeScript, React, Tailwind
Google Cloud Platform, Vercel
Linear, Slack, Notion
Joining us
To start, you'll have a handful of conversations with our team and founders. If there is mutual excitement, we'll invite you to the office where you'll work on a small project and meet the team.