Lead Software Engineer, Neuroimaging Platform

About us NeuroScope is an early-stage company building software that turns neuroimaging data into quantitative insights for researchers and clinicians. We are building a cloud-native production image analysis platform to serve customers. We are a small team of scientists and builders, and every hire shapes the product and the company. About the role We are looking for a lead engineer to own our cloud platform end to end. You will design, build and run the AWS systems that ingest, process and deliver neuroimaging data (MRI and PET), and you will lead integration with hospital imaging systems (PACS). Because customers use the platform, keeping it reliable and secure will be a core part of your work. This is a hands-on role where you will make key architecture decisions, keep production reliable and secure, and turn research methods into production services. You will work closely with our scientists and with outside regulatory advisors. Employment type: Full-time Location: [Remote] Reports to: CEO Responsibilities Design and evolve a cloud-native architecture on AWS for secure, scalable neuroimaging ingestion, processing, storage and delivery. Define and manage all infrastructure as code (Terraform or AWS CDK), with environments that can be reproduced and audited. Build and maintain CI/CD pipelines and automated tests, including regression tests against reference outputs, for application code, infrastructure and container images. Run production: monitoring, alerting, logging, backup and disaster recovery, incident response, customer-reported issues and cost management. Build and operate containerized workflows on AWS (such as ECS, Batch, Step Functions, Lambda and S3) that convert, quality-check and analyze scans and generate reports. Package third-party scientific tools and in-house algorithms as versioned, reproducible Docker images. Design and implement integration with hospital PACS and other clinical systems, using DICOM networking and DICOMweb. Build the web applications that clinicians and researchers use to upload studies, track processing, and review results and reports, from front-end interfaces to back-end APIs. Apply strong security practice for protected health information: DICOM de-identification, identity and access management, encryption, network isolation, secrets management and audit logging. Take algorithms and ML models from research prototypes to tested, versioned production services, including GPU workloads. Implement software-lifecycle practices for regulated medical software, such as requirements traceability, verification and change control, working with our regulatory advisors. Write clear technical documentation, and explain architecture trade-offs and risks to non-engineering colleagues. Required qualifications 5+ years of software engineering experience, including at least 3 years building and running production systems on AWS. Deep hands-on experience with core AWS services: compute (EC2, ECS or EKS, Lambda), storage (S3, EBS), networking (VPC), IAM, and observability (CloudWatch). Strong infrastructure-as-code skills with Terraform or AWS CDK, including module design, state management and multiple environments. Strong Python skills, including scientific libraries such as NumPy and Matplotlib, plus Bash scripting. Linux systems administration, including Nginx or similar reverse proxies, TLS certificates, DNS and firewalls. Production experience with Docker, Docker Compose and container orchestration, including image registries and multi-architecture builds. Working knowledge of PostgreSQL, including schema changes, backup and restore, and version upgrades. Full-stack web development experience: back-end APIs plus front-end interfaces in a modern framework such as React with TypeScript. Experience building CI/CD pipelines, for example with GitHub Actions or AWS CodePipeline. Disciplined engineering practice: Git, code review, and automated unit and integration tests. Experience securing systems that handle sensitive data, such as healthcare or financial data. Proven ability to own systems independently: set priorities, make sound architecture decisions and document them. Bachelor's degree in computer science, engineering or a related field, or equivalent experience. Preferred qualifications Experience with medical imaging standards and data, such as DICOM, DICOMweb and NIfTI, for both MRI and PET. PACS or clinical system integration experience, such as DICOM C-STORE and C-FIND, HL7 or FHIR, or work with hospital IT teams. Experience building software under HIPAA, or a medical device quality system such as IEC 62304, ISO 13485 or FDA 21 CFR Part 820. Experience running scientific or ML workloads in production, including GPU computers. Nice to have AWS certification, such as Solutions Architect or DevOps Engineer. Experience with XNAT, which we use for DICOM ingestion, including its REST API, Container Service and Java/Tomcat deployment. Familiarity with neuroimaging tools and methods, such as dcm2niix, BIDS, MRIQC, FreeSurfer or FSL for MRI, and PET processing such as motion correction, MRI co-registration and SUVR quantification.