Backend Engineer

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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