The posting
About the Role You will help lead application development for a live, patient-facing clinical product: an embeddable widget, a clinician portal, and the Python service layer between them. Because some of the system was built rapidly by a small team, parts of it need a durable owner to shore up the foundations before pushing new features. You will own these application surfaces end-to-end, advise on full-stack architectural decisions, and dive deep into the system to independently identify what needs improvement and what we should tackle next.
You will work alongside our AI engineers to support Fabric’s flagship AI Intake system, ensuring the application layer and the machine learning models evolve in lockstep. This is a small, high-trust team that leans heavily on AI coding tools, spec-driven development, and effective test coverage. You will operate with real autonomy, shipping critical encounter plumbing and internal tools while still interacting regularly with other engineers and cross-functional partners.
What You'll Do As a Staff Software Engineer, you are the durable owner of the application surfaces our patients and clinicians rely on. Your ramp-up and core responsibilities include:
Your First Six Months: Month 1: Dive into the widget, portal, and service layer to become an owner of all of them, shipping meaningful changes and forming a tight working relationship with our other engineers and partners. Month 3: Take full ownership of a major integration or platform initiative and step into the role of primary reviewer for all application-side design decisions. Month 6: Deliver an end-to-end system that external teams depend on, and mentor potential junior engineers to the point where they independently own technical surfaces of their own.
Ongoing Architectural & Application Ownership: Build the AI Plumbing: Operate the critical application work that supports AI Intake, including encounter data flow, integration against partner platforms, and every surface a new customer touches (typically managing one in flight and another right behind it). Own Internal Tooling: Manage and scale the growing set of internal tools that your own team and our clinicians depend on. Drive Full-Stack Architecture: Advise on and make foundational architectural decisions, going deep enough into the system to independently identify what needs shoring up and where development should head next. Partner with AI Engineers: Keep the application layer tightly coordinated with the AI/ML engineers who own the conversation pipeline, prompts, and clinical-safety layer. Protect Shared Surfaces: Ship and version components that other teams consume as a dependency, explicitly protecting those consumers from expensive breaking changes. Maintain Operational Excellence: Keep dependencies current and operate what you build so maintenance stays a daily habit rather than a quarterly crisis.
Why You Might Be a Good Fit You are drawn to systems you can own and live with, taking real satisfaction in making quickly built foundations durable rather than just shipping and handing them off. You care deeply about the patient on the other end, understanding the real safety stakes of a live clinical product and wanting your work to matter. You are a fluent full-stack engineer who moves easily from a React widget down through a Python service and its data layer, making sound architectural calls across the entire stack. You are comfortable with agentic coding tools and spec-driven development practices. You act as a genuine partner to data scientists, knowing enough about LLM application development to speak the language of prompts, evaluation, and latency tradeoffs without needing to own the models yourself. You think in dependencies and blast radius, understanding why breaking changes are expensive and designing shared surfaces with consuming teams in mind. You write clearly, mentor generously, and treat making other people's work easier as a core part of the job.
This Might Not Be The Right Fit If... You want to design the models and prompts yourself (this role strictly partners with the people who do that). You prefer greenfield builds that you hand off, rather than inheriting and shoring up systems other people started quickly. You prefer to specialize narrowly in the frontend or backend rather than owning the full stack architecture. You view keeping dependencies current, operating what you ship, and mentoring junior engineers as overhead.
Your Qualifications 6+ years of professional full-stack web software experience, including at least 1 year operating at a Staff level and living with architecture you built. Depth in TypeScript and React, with fluency in a modern server-rendered framework (we use Next.js). Strong Python experience with an async web framework, plus the surrounding data layer (relational schema design, migrations, caching). Experience building versioned dependencies consumed by other teams (widgets, SDKs, or component libraries). Fluency with LLM application development to effectively partner with data scientists on prompts, evaluations, and cost tradeoffs.
Bonus Points Healthcare experience involving PHI, HIPAA, clinical workflows, or patient-facing surfaces with real safety stakes. Familiarity with agent or workflow orchestration frameworks like LangGraph. Experience designing for accessibility and internationalization from the start. AWS background (especially Bedrock) and infrastructure-as-code. Eval tooling experience (Braintrust, LangSmith, or custom-built equivalents). Having been the first or second engineer on a greenfield product and having to live with it.
The national pay range for this role is $150,000.00 - $190,000.00 per year. Actual compensation will be determined by factors such as the candidate's geographic market, experience, skills, and qualifications. Certain roles may also be eligible for additional compensation, including a comprehensive benefits package such as medical, dental, vision, unlimited PTO, and a 401(k) plan, stock options and bonuses. If your compensation requirement is greater than our posted range, please still consider applying; a determination can be made based on unique qualifications. Expected compensation ranges for this role may change over time.
