{"id":3272827,"url":"https://alion.io/job/saigroup-full-stack-engineer-medical-imaging-web-platform-3d-viewer","title":"Full Stack Engineer – Medical Imaging Web Platform & 3D Viewer","company":{"id":687301,"name":"SAIGroup","domain":"saigroup.ai","url":"https://alion.io/company/saigroup","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":86,"open_postings":9,"ghost_share":0,"stale_share":0.556,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-29T05:49:05Z"}},"role":"Backend","role_family":"Backend","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India","Palo Alto, United States"],"countries":["IN","US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"DICOM","optional":false},{"name":"Docker","optional":false},{"name":"FastAPI","optional":false},{"name":"FDA 510(k)","optional":false},{"name":"Git","optional":false},{"name":"HIPAA","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"IEC 62304","optional":false},{"name":"Keycloak","optional":false},{"name":"Kubernetes","optional":false},{"name":"Node JS","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"React.js","optional":false},{"name":"Rest API","optional":false},{"name":"TypeScript","optional":false},{"name":"FHIR","optional":true},{"name":"GDPR","optional":true},{"name":"GLSL","optional":true},{"name":"HL7","optional":true},{"name":"ISO 13485","optional":true},{"name":"JavaScript","optional":true},{"name":"LLM","optional":true},{"name":"WebGPU","optional":true},{"name":"WGSL","optional":true}],"status":"live","first_seen_at":"2026-10-26T10:29:41Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-10-29T13:14:17Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"About the Role\nWe are building a cloud-native, AI-assisted radiology platform for CT and MRI. The product has two equally important components: a browser-based 3D viewer (Cornerstone3D / VTK.js) and the web application surrounding it, covering worklists, study management, clinical workflows, user and access management, and an agentic AI assistant.\nThe product is being developed as a regulated medical device, with a target of FDA 510(k) clearance.\nAs a Full Stack Engineer on the imaging team, you will split your time between the application and the viewer. You will build the web application and its backend services, and work on the 3D viewer where AI results and clinician workflows come together.\nYou will collaborate closely with radiologists, ML engineers, product, QA, and our US-based engineering team.\nKey Responsibilities\n Web Application and User Workflows\nBuild and own the React/TypeScript web application, including study worklists, search and filtering, study and series management, case assignment, review and approval queues, and reporting screens.\nDesign and implement clean, fast, accessible UIs for clinical users, including the interface for the agentic AI assistant, with chat, suggested actions, and review of proposed actions.\nImplement authentication and role-based access control (OIDC/SSO, Keycloak, or similar), user and tenant administration, and audit-log views.\nBuild real-time and long-running workflow experiences, including job status, progress indicators, notifications, and retries for processing and AI pipelines.\nManage application state, API integration, and caching to keep large worklists and studies responsive.\nCreate annotation, labeling, and quality-review tools that capture clinician feedback in a structured format.\n Viewer and Rendering\nExtend and maintain the web-based 3D viewer (Cornerstone3D / VTK.js) with DICOMweb integration (QIDO-RS, WADO-RS, STOW-RS).\nImplement volume rendering, surface rendering, and MIP/MinIP for CT and MRI, including transfer function presets and controls.\nBuild multiplanar reconstruction (MPR), oblique, curved, and straight reformats with synchronized crosshairs and cross-reference navigation.\nDevelop interactive tools for measurements, annotations, clipping, cropping, and segmentation editing, including brush, threshold, and region-growing tools.\nOptimize viewer performance for large, multi-series studies through progressive and streaming loading, GPU memory budgeting, web workers, and caching.\n Advanced Clinical Workflows\nBuild vessel segmentation and reconstruction workflows, including centerline extraction and curved planar reformation (CPR) views.\nDevelop procedure-planning features such as landmark placement, device sizing, and trajectory planning.\nAI Integration\nIntegrate the viewer with AI services for segmentation, detection, and the agentic AI assistant through secure, well-defined APIs.\nRead and write AI outputs as standard DICOM objects, including DICOM-SEG, Structured Reports such as TID 1500, and RT Structure Sets, and display them as editable overlays.\nBuild human-in-the-loop workflows where clinicians review, edit, accept, or reject AI results, with provenance tracking and an audit trail of every change.\nEnsure AI-generated content is clearly distinguishable from clinician-entered content in the UI.\n Backend and Platform\nDesign and build backend services and REST APIs using Python/FastAPI or Node.js for study management, workflow orchestration, users, and AI results.\nModel and manage data in PostgreSQL and object storage (S3), and build pipelines for ingesting, indexing, and serving large imaging datasets.\nIntegrate with PACS/VNA and DICOM sources using DICOMweb, Orthanc, or similar technologies, and with workflow engines such as Temporal.\nDeploy and operate services in containers on AWS and Kubernetes alongside the platform team, with logging, monitoring, and CI/CD.\n Quality and Compliance\nDevelop software under IEC 62304, including traceable requirements, unit, integration and end-to-end tests, and code reviews.\nContribute design and verification documentation to support regulatory submissions.\nHandle protected health information (PHI) securely and follow HIPAA-aligned engineering practices.\nRequired Qualifications\n4+ years of professional full stack development experience, with a track record of shipping production web applications end to end.\nStrong TypeScript and React skills, including state management, component design, and browser performance optimization involving rendering, memory, and web workers.\nSolid backend experience with Python (FastAPI preferred) or Node.js, REST API design, authentication and authorization (OAuth2/OIDC, RBAC), and PostgreSQL.\nExperience with Docker, Git, CI/CD, and automated testing, including unit, integration, and end-to-end testing.\nHands-on experience with Cornerstone3D/Cornerstone.js, OHIF, VTK.js, or comparable imaging stacks such as ITK, 3D Slicer, or WebGL volume rendering. At least 1-2 years in medical imaging or 3D visualization is a strong plus.\nWorking knowledge of DICOM, including the data model, key tags, and patient coordinate systems, as well as DICOMweb and PACS.\nComfort with 3D concepts, including transforms, meshes, volume rendering, and MPR geometry.\nExperience consuming ML/AI model outputs in a production application.\nPreferred Qualifications\nExperience with vessel analysis, centerline/CPR, or surgical/interventional planning software.\nContributions to open-source imaging projects such as Cornerstone3D, OHIF, VTK.js, dcmjs, or similar.\nWebGL/WebGPU and GLSL/WGSL shader programming experience.\nFamiliarity with MONAI, nnU-Net, TotalSegmentator, or MedSAM, including prompt-based and interactive segmentation.\nExperience with DICOM tooling such as Orthanc, dcm4che, pydicom, highdicom, or dcmjs.\nBackground in regulated environments, including IEC 62304, ISO 13485, FDA 510(k), CE-MDR, and HIPAA/GDPR, with an understanding of requirements for AI-enabled medical devices.\nFamiliarity with HL7 FHIR, Kubernetes, AWS, Keycloak, and workflow engines such as Temporal.\nExperience building LLM- or agent-based user experiences, including chat UIs, tool-use review, and streaming responses.\nWhat We Offer\nA focused team building AI-enabled clinical imaging software designed to improve patient care.\nReal ownership of core application and viewer features in a product progressing toward FDA clearance.\nClose collaboration with radiologists, imaging experts, and AI engineers.\nCompetitive salary and benefits.\nFlexible work arrangements and support for professional development.","description_format":"text","description_chars":6596,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Flexible schedule","Professional 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