Member of Technical Staff, Software Engineering, Mosaic Reporting

Cognita Imaging•Palo Alto, CA

20h•Hybrid

About The Position

Cognita's mission is to increase the world's access to healthcare. Radiology is (1) the first-line diagnostic specialty, (2) facing a worsening global workforce shortage, and (3) highly digitized, making it uniquely positioned for AI to have an enormous impact. Stage one of Cognita is focused on expanding access to radiology at scale. Our founding team met at Stanford, where they laid the groundwork for applying comprehensive AI to radiology. Building on that foundation, Cognita develops vision-language models that read radiology studies the way radiologists do, interpreting the full study in clinical context, and generating draft results that make radiologists more efficient and accurate. In partnership with Radiology Partners, the largest radiology practice in the world, Cognita's models are trained and validated on one of the world's largest real-world radiology datasets. About the Role As a Member of Technical Staff in Software Engineering, you will build the full-stack systems behind Mosaic Reporting, Cognita's AI-native, real-time radiology reporting product, part of MosaicOS. As a radiologist dictates, the system extracts statements from natural speech and places them into the correct section of the report in real time. Findings, impressions, macros, and edits are all driven by natural dictation rather than templated clicking, so the report comes together as the radiologist reads, with their eyes never leaving the image. This experience is powered by Cognita's proprietary real-time reporting technology. Mosaic Reporting is already deployed across thousands of radiologists at Radiology Partners and is proven in production. Your work focuses on the next chapter: scaling and improving the system as it rolls out more broadly across Radiology Partners and to external customers, work that sits directly in the critical path of patient care. You'll be one of the first hires dedicated to transforming reporting into a revolutionary product, and you'll work closely with our clinical AI teams to continuously improve the product experience for the radiologists who use it on every study. You'll report to the Reporting product lead and partner across engineering, ML, and clinical teams to take the product from "works at scale" to "built to scale."

Requirements

Strong experience building full-stack systems in production.
Attention to detail and an eye for product design
Experience designing and operating cloud-based services, ideally on AWS.
Comfort building and owning API-driven, data-intensive systems.
Experience working with distributed systems and production reliability concerns.
Familiarity with a modern backend stack such as: AWS (e.g., EC2, S3, ECS/EKS, IAM, CloudWatch) Python backend services (e.g. FastAPI, Flask, or similar) PostgreSQL or similar relational databases
Strong ownership mindset and good systems judgment.

Nice To Haves

Experience with real-time and/or low-latency systems (streaming, WebSocket/WebRTC, SSE, or similar) is a strong plus.
Experience with report generation, structured text pipelines, or document workflows.
Familiarity with LLM inference pipelines or AI-powered products
Experience working in healthcare or other regulated environments, and handling PHI / building to HIPAA requirements
Radiology or medical imaging domain knowledge (modalities, reporting workflows, structured reporting).
Hands-on with speech-to-text or low-latency audio streaming pipelines
React / Next.js performance and state architecture

Responsibilities

Iterate on the frontend and backend services that power Mosaic Reporting.
Improve our reporting system that transforms model outputs and radiologist voice dictation into accurate, structured radiology reports in real time.
Develop workflows for VLM-based pixel-to-text report drafting, editing, resident workflows and clinician sign-off.
Help scale and harden the real-time streaming dictation pipeline so the system stays efficient and reliable as the load and the team grow.
Work with large volumes of structured and unstructured data, including imaging metadata and model outputs.
Ensure platform services are reliable, secure, low-latency, and scalable as the product expands across Radiology Partners and to external customers.
Collaborate closely with clinical AI, ML training, evaluation, and infrastructure teams to integrate inference into production reporting workflows and improve product quality.
Own services end-to-end, from design and implementation through deployment and operation.