Senior Software Engineer II, AI Developer Foundations

SimplePractice is improving access to quality care by equipping health and wellness clinicians with essential tools for their private practice. The Senior Software Engineer II, AI Developer Foundations will build tools for AI integration within engineering, product, and design, ensuring effective use of AI in the development process.

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

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
• 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