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+ years of experience in backend software engineering
Prior experience working with AWS
Strong proficiency in Python or similar backend languages
Experience designing and building RESTful APIs
Experience working with relational and/or NoSQL databases
Understanding of distributed systems and scalability concepts
Strong debugging and problem-solving skills
Preferred Qualifications
Experience in healthcare technology or regulated environments
Experience working with ML-enabled systems or model inference APIs
In-depth knowledge of AWS services (Lambda, ECS, S3, RDS, DynamoDB, etc.)
Experience integrating with third-party APIs or EHR systems
Knowledge of CI/CD pipelines and infrastructure-as-code tools
Technical Environment
Python-based backend services
AWS cloud infrastructure (including GovCloud environments)
ML-enabled application platforms
CI/CD pipelines and containerized services
Observability tools (CloudWatch, Sentry)
Compensation & Benefits
Meaningful equity compensation
Unlimited PTO
Premium health, dental, and vision coverage
401(k) plan
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