Senior Software Engineer II, AI Developer Foundations

SimplePractice

13h•$208,000 - $260,000

About The Position

Engineers on the AI Developer Foundations will build the tools that build the product. It's a new team that owns how AI gets used inside engineering, product, and design at SimplePractice: the conventions for using these tools, the context agents read before they touch our code, the bar generated work has to clear before a human spends time on it, and the training that makes AI a useful tool to all of engineering. This is a hands-on role reporting to the VP of Technology. You'll write code most days, mostly in and around a large Rails monolith, and you'll also write the conventions other engineers follow.

Requirements

BS/MS in Engineering, Computer Science, or related field, or equivalent experience
7+ years building production software and then maintaining it. You’ve shipped something, lived with the decisions, and found out whether a design decision held up
Strong problem-solving and communication skills; comfortable in fast-paced, cross-functional environments
Recent, direct Rails experience in a large codebase.
Ability to read unfamiliar application code quickly and judge whether what an agent produced in it is any good
LLM-backed systems you've shipped to users and kept running, past the point where better prompting stops helping
Experience building context or memory handling, and writing evals
Judgment about what belongs in code and what belongs in the model
Track record evaluating tools with evidence
Internal tools, platforms, conventions or workflows that other engineers chose to use.
CLI and harness-shaped software, and comfort connecting systems over APIs
Strong writing. Much of this role is getting other people to work differently, which happens through docs and worked examples rather than announcements
Comfort working outside engineering, explaining technical constraints to people who don't share your background and taking their pushback seriously

Nice To Haves

Agent harnesses, MCP servers, orchestration frameworks
Healthcare or another HIPAA-regulated environment
AWS, Terraform, Kubernetes, Docker
Experience on a platform or infrastructure team where the customers were other engineers
Having overbuilt a platform once before the workflows existed, and learning to spot the warning signs earlier

Responsibilities

Own the context layer agents read: rules files, docs conventions, grounding data, with CI and named owners keeping it current
Publish the standards for how we prompt coding agents, how we supply context, and what a spec needs to contain before it's worth handing to an agent
Define the review gates any AI-generated artifact clears before a human spends time on it, and get what reviewers catch flowing back into the conventions
Take the prototypes running today and turn the ones that hold up into supported workflows that run for someone other than their author
Evaluate harnesses, models and vendors against criteria and eval sets
Work the product-to-engineering handoff with PMs, designers and EMs
Teach. Documentation, worked examples, office hours, and time sitting with a squad while they work with the tools we build
Help us draw the boundaries for where an agent runs unattended, where a human signs off, and where we don't use one at all