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