Backend Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Salary

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401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source

Seniority

Mid From the posting source

Work mode

Hybrid From the posting source

In-office days

2 days From the posting source

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Backend Engineer San Francisco | Hybrid | Remote 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're experiencing explosive growth across both commercial health systems and federal healthcare, with our ambient documentation platform scaling rapidly to thousands of clinicians across hundreds of specialties. We're at an inflection point where cutting-edge AI meets real clinical impact, giving clinicians hours back each day to focus on what matters most - their patients. Position Overview We are seeking a Backend Engineer to design, build, and scale the core infrastructure powering Knowtex's AI-driven clinical documentation platform. You will work closely with Applied ML, Integrations, and Frontend teams to develop reliable, secure, and high-performance backend systems that support real-time voice AI workflows across enterprise healthcare environments. This role is critical to ensuring scalability, reliability, and compliance as we expand across commercial and federal healthcare systems. Key Responsibilities - Design and implement scalable backend services and APIs - Build and maintain microservices supporting AI-driven clinical workflows - Develop and optimize data pipelines for real-time processing - Collaborate with ML engineers to productionize model inference systems - Design secure, compliant data architectures (HIPAA-aware systems) - Improve system reliability, observability, and performance - Participate in architecture reviews and technical design discussions - Contribute to CI/CD pipelines and deployment automation - Support integration efforts with EHR systems and third-party platforms Required Qualifications - 3-6+

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