Own and operate the full-stack application surfaces of a live patient-facing product: embeddable React/TypeScript widget, clinician portal, and Python service layer. Advise and make architectural decisions, integrate AI Intake features, ship versioned shared surfaces, keep dependencies current, and mentor junior engineers while partnering closely with AI/ML teammates to coordinate application and model work.
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The national pay range for this role is $145,000.00 - $185,000.00 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.At Fabric, we believe that a diverse workforce is essential to our success. We are an equal opportunity employer and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, veteran status, or any other legally protected characteristic. We actively encourage individuals from all backgrounds to apply.
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At Fabric Health, we are powering boundless care by solving healthcare’s biggest challenge: clinical capacity. We aren’t here to disrupt healthcare; we’re here to fix it. We unify the care journey from intake to treatment, using intelligent automation to remove administrative burdens and make care delivery 2-10x more efficient. Our technology empowers clinicians to move faster and focus on what matters most: the patient.
We are a mission-driven team of brilliant minds trusted by leading organizations including Intermountain Health, OSF HealthCare, SSM Health, and MUSC Health. Our vision is backed by premier investors such as Thrive Capital, GV (Google Ventures), General Catalyst, and Salesforce Ventures. We move quickly for good reason, listen deeply to solve big challenges, and build products with the same care and quality we’d want for our own loved ones.
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There is a live, patient-facing clinical product running today: an embeddable widget patients talk to, a portal clinicians read, and a Python service layer stitching the two together. Much of it was built quickly by a small number of people, and realistically, parts of it need a durable owner before they need new features. That is the job. You will own the application surfaces of this product end to end, advise on and make the full-stack architectural decisions that shape it, and go deep enough into the system to independently find what needs shoring up and where it should go next.
The widget and portal are TypeScript and React; most of what sits behind them is Python. The team's flagship product, AI Intake, is an agent-based system, but a great deal of critical application work supports it: encounter plumbing, data flow, integration against someone else's platform, and every surface a new customer touches. There is generally one of those in flight and another right behind it. Alongside the customer-facing application sits a growing set of internal tools your own team and clinicians depend on, and you will own both, working shoulder to shoulder with the AI engineers so the application and the models move together rather than past each other. You will also mentor engineers earlier in their careers, starting with the entry-level engineer who sits beneath this seat.
This is a small, high-trust team that does much of its thinking in writing and backs every change with test coverage, because a system with this many moving parts depends on it. We lean hard on AI coding tools and keep reworking how we build around them, and you would have a real voice in what we try next. Expect to ramp fast. In your first month, you will have gotten deep enough into the widget, the portal, and the service layer to be the second name on any of them, shipped meaningful changes to each, and formed a working relationship with the data scientists whose work yours carries. By three months, you own whichever integration or platform initiative the team is carrying, and you are the reviewer we route application-side design decisions through. By six months, you have delivered something end to end that people outside the team depend on, and you have brought an engineer earlier in their career far enough along that they own surfaces of their own.
As a Staff Application Engineer on the Applied AI team, you will be the durable owner of every application surface the product touches, from the code patients interact with to the tools clinicians rely on. Your primary responsibilities will include:
- Owning the application surfaces of a live, patient-facing clinical product end to end: the embeddable widget patients talk to, the clinician portal, and the Python service layer between them.
- Owning and advising on full-stack architectural decisions, going deep enough into the system to independently identify key areas for improvement and future directions of development.
- Building and operating the application work that supports AI Intake: encounter plumbing, data flow, integration against partner platforms, and every surface a new customer touches, with one such initiative typically in flight and another behind it.
- Owning the growing set of internal tools your team and clinicians depend on, right alongside the customer-facing application.
- Partnering closely with the AI/ML engineers who own the conversation pipeline, prompts, evaluation, and clinical-safety layer, keeping the application and model work well coordinated and moving together.
- Shipping and versioning shared surfaces that other teams consume as a dependency, and protecting those consumers from expensive breaking changes.
- Keeping dependencies current and operating what you build, so maintenance stays a habit rather than becoming a quarterly crisis.
- Mentoring engineers earlier in their careers, starting with the entry-level engineer on the team, and making other people's work easier through clear written thinking and reliable review.
- You are a builder who stays: You are drawn to systems you can own and live with, not just ship and hand off, and you take real satisfaction in making something quickly-built durable.
- You care about the patient on the other end: This is a live clinical product with real safety stakes, and you want your work to matter to the people using it.
- You are a strong full-stack engineer with range: You are fluent from a React widget down through a Python service and its data layer, and you make sound architectural calls across all of it.
- You are a genuine partner to data scientists: You know enough about LLM application development to speak the language of prompts, evaluation, and latency and cost tradeoffs, without needing to own the models yourself.
- You think in dependencies and blast radius: You understand why breaking changes are expensive and you design shared surfaces with the teams that consume them in mind.
- You make other people better: You write clearly, you mentor generously, and you treat "making other people's work easier" as core to the role, not a side effect.
- You want to design the models and the prompts. This role partners with the people who do that; it does not do it, and we would rather it did not.
- You prefer greenfield builds you hand off, over inheriting and shoring up systems other people started quickly.
- You would rather specialize narrowly in the frontend or the backend than own the full stack and the architecture across it.
- You see keeping dependencies current, operating what you ship, and mentoring less-experienced engineers as overhead rather than part of the job.
- You are looking for a large, heavily-structured team; this is a small, high-trust group where you will own broad surface area with real autonomy.
- Substantial experience shipping and operating production full-stack web software, including architecture you owned and then had to live with. Successful candidates will have 8+ years of professional experience, including at least 1 year at a staff level.
- Depth in TypeScript and React, with fluency in a modern server-rendered framework. We use Next.js.
- Strong Python and experience with an async web framework, plus the data layer around it: relational schema design, migrations, and caching.
- Experience building something other teams consumed as a versioned dependency, whether a widget, an SDK, or a component library. You know why breaking changes are expensive.
- Comfort operating what you build, and the discipline to keep dependencies current so they never become a quarterly crisis.
- Enough fluency with LLM application development to be a real partner to data scientists: prompts, evaluation, and the latency and cost tradeoffs. You don't need to be the person designing the models or the prompts, and we'd rather you weren't.
- Clear written communication and a genuine appetite for mentoring. Much of this role is making other people's work easier.
- Healthcare experience, particularly anything involving PHI, HIPAA, clinical workflows, or a patient-facing surface with real safety stakes.
- Agent or workflow orchestration frameworks such as LangGraph.
- Accessibility and internationalization designed in from the start.
- AWS, especially Bedrock, and infrastructure-as-code.
- Eval tooling such as Braintrust or LangSmith, or something equivalent you built yourself.
- Having been the first or second engineer on a greenfield product, and having later had to live in it.
The national pay range for this role is $145,000.00 - $185,000.00 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.At Fabric, we believe that a diverse workforce is essential to our success. We are an equal opportunity employer and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, veteran status, or any other legally protected characteristic. We actively encourage individuals from all backgrounds to apply.
Fabric Health is aware of scammers attempting to impersonate employers. To ensure that any recruiting contact you receive is legitimate, please adhere to the following:
- Verify the Domain: Official recruitment emails will only come from addresses ending in @fabrichealth.com or @gem.com. No other domain names are legitimate.
- Official Interview Tools: We use Gem for our recruitment process and Google Meet for all video interviews. Google Meet is always the platform used for your first interview; you will never be sent a Zoom link to set up or conduct an initial interview. All interviews are conducted via video unless specifically stated by our team as an audio call. We never conduct interviews via chat, social media, Skype, or WhatsApp.
- Zoom Usage: Zoom is utilized only for specific meetings set directly by our team for purposes outside of the standard interview process (e.g., coordination or onboarding discussions). It is never the first link you will receive from us.
- Authorized Contact & Texting: Fabric will only contact you if you have submitted an application or if you are connected to a current employee who shared your information with us. We will only send text messages if you have provided explicit authorization and consent, either through your application or while communicating directly with our team. If you have not explicitly authorized us to reach out, treat any SMS or unsolicited outreach as fraudulent and do not respond.
- Sensitive Data: We will never ask you for sensitive personal or financial documents (ID, banking info, SSN) during the application, interview, or candidacy stages. All sensitive data is handled through secure internal systems post-offer.
- Verify the Team: You can reference LinkedIn to verify members of our recruiting team; however, please remain vigilant as scammers may create fraudulent profiles. Always cross-reference the sender's email domain with our official @fabrichealth.com address.
If you question the validity of a contact or receive a suspicious message, do not click any links. Please submit a report via this link: https://forms.gle/N1AGAiXcAL2W57H9A
Please note: The security inbox is for reporting fraudulent activity only. Do not email this address for application status updates or to share application materials, as these will not be reviewed. Applications are only accepted and reviewed if submitted through our official application portal, and no application status information will be provided via the security email.
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