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Knowtex

Integration Engineer

Location
San Francisco, CA, US
Arrangement
Hybrid
Employment type
Full-time
Posted
4 September 2026 (27 days ago)

Checked 26 days agoApplications go to the employer, never to RoleSprint

About this role

ABOUT KNOWTEX

Knowtex is building the future of voice AI operating systems for clinicians, transforming how healthcare documentation happens at the point of care. Founded by Stanford AI scientists with deep clinical experience, we are experiencing rapid growth across both commercial health systems and federal healthcare, with our ambient documentation platform scaling to thousands of clinicians across hundreds of specialties.

We are at an inflection point where advances in AI can fundamentally change how clinicians interact with technology, giving them more time to focus on what matters most: their patients.

POSITION OVERVIEW

Knowtex is seeking an Integration Engineer to own and scale our healthcare system integrations.

This role will focus on internalizing critical EMR integrations, reducing reliance on external vendors, and building scalable, secure, and reliable system-to-system interoperability across commercial and federal customers.

You will be responsible for designing, implementing, and maintaining integrations with EMR/EHR platforms, working across modern API-based systems as well as legacy workflows.

This is a high-impact role with direct visibility into production healthcare environments and strategic importance as integrations become a core competency at Knowtex.

KEY RESPONSIBILITIES

- Design, build, and maintain integrations with EMR/EHR platforms across API-based and legacy systems

- Internalize and replace third-party integration dependencies where appropriate

- Develop scalable, secure, and reliable healthcare data pipelines

- Build data validation, transformation, and normalization layers across heterogeneous healthcare systems

- Monitor integration health, troubleshoot production issues, and implement observability best practices

- Collaborate with product, clinical, and AI teams to translate workflow requirements into technical integration designs

- Contribute to long-term integration architecture strategy as Knowtex expands across specialties and health systems

REQUIRED QUALIFICATIONS

- 5+ years of software engineering experience, ideally in healthcare

- Experience integrating with third-party APIs and external systems

- Strong backend development experience with Python, Node.js, or similar technologies

- Experience working with AWS services

- Solid understanding of REST APIs, authentication flows, and distributed systems

- Experience working with structured healthcare data

PREFERRED QUALIFICATIONS

- Experience integrating with EMR/EHR systems

- Familiarity with healthcare interoperability standards such as FHIR and HL7

- Experience designing idempotent, fault-tolerant integration workflows

- Familiarity with HIPAA-compliant environments

TECHNICAL ENVIRONMENT

- AWS

- Python and Node.js / TypeScript

- React frontend for internal tools and integration dashboards

- Event-driven and asynchronous processing architectures

COMPENSATION & BENEFITS

- Competitive salary

- Meaningful equity compensation

- Unlimited PTO

- Premium health, dental, and vision coverage

- 401(k) plan

- Work model: Hybrid In-person (Monday, Tuesday, Wednesday in office in SF)

Work location

  • San Francisco, CA, US

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About this listing

Published on Ashby under the board identifier Knowtex, which is the name the employer’s own job board carries. RoleSprint has not verified the company’s registered or trading name, so it is shown exactly as published rather than tidied up.

RoleSprint is not the employer and not a recruiter. Applications are made on the employer’s own site and never reach us; what RoleSprint does is help you decide whether a role is worth your time and prepare for it if it is.

Published 4 September 2026, last checked 26 days ago. A posting stops being advertised here 90 days after the employer published it, and one the employer takes down is marked closed rather than quietly removed.

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