We’re on a mission to change the future of clinical research. At Perceptive, we help the
biopharmaceutical industry bring medical treatments to the market, faster.
Our mission is to change the world but to do this, we need people like you.
Key Responsibilities:
Supporting Activities
Cloud-Native SaaS Architecture Design
- Implement scalable, multi-tenant SaaS components using cloud-native services.
- Design and develop microservices for medical imaging data processing and AI workloads.
- Implement auto-scaling and load balancing features for medical imaging datasets.
- Develop API endpoints and service integrations with clinical trial systems.
- Support platform scalability for concurrent clinical trials and imaging workflows.
AI-Driven Medical Imaging Platform Development
- Implement AI/ML model integrations for medical image analysis, including genAI, computer vision and deep learning algorithms.
- Develop systems for real-time and batch processing of medical imaging data (DICOM, NIfTI, etc.).
- Implement DICOM-compliant data processing pipelines.
- Develop efficient DICOM image preprocessing workflows for AI model preparation.
- Support AI model deployment and monitoring in production environments.
Medical Image Viewer Integration & Workflow Design
- Develop integration components for third-party medical imaging viewers (OHIF, Cornerstone.js, or proprietary systems).
- Implement APIs and SDK components for clinical trial management system integration.
- Develop collaboration features for multi-site clinical trials.
- Create visualization components for AI-generated insights and annotations.
- Ensure responsive design implementation for various devices and browsers.
Security & Compliance Implementation
- Implement security features compliant with FDA 21 CFR Part 11, GxP, and medical device regulations.
- Develop audit trails, electronic signatures, and data integrity controls.
- Implement encryption, role-based access control, and authentication features.
- Support disaster recovery and backup solutions for clinical trial data.
Database & Data Management
- Implement high-performance database solutions for DICOM metadata storage and retrieval and AI model outputs.
- Develop solutions for the storage, analysis, access, and movement of large-scale medical imaging datasets.
- Implement data processing pipelines for large-scale DICOM datasets.
- Develop real-time data streaming components for live DICOM image analysis.
- Implement data governance features ensuring data quality and privacy protection.
Performance Optimization & Monitoring
- Implement monitoring and observability components for SaaS platform performance.
- Optimize system performance for medical imaging file processing and transfer.
- Implement caching strategies and CDN integration for global access.
- Develop automated alerting and performance monitoring features.
- Support SLA compliance and platform reliability initiatives.
Technical Development & Support
- Contribute to technology stack decisions for medical imaging and AI workloads.
- Support adoption of emerging technologies in medical imaging and AI/ML.
- Participate in code reviews and maintain development best practices.
- Support coding standards, development processes, and quality assurance.
- Collaborate in technical architecture reviews and system design decisions.
Innovation
- Take an active interest in emerging technologies in medical imaging, AI/ML, and cloud computing.
- Monitor the market to gather intelligence on emerging technologies.
- Share knowledge and insights with others.
Other
- Carryout any other reasonable duties as requested.
Functional Competencies (Technical knowledge/Skills):
- Knowledge of containerization and serverless architectures
- Knowledge of message queuing systems for high-throughput medical data processing
- Knowledge of DICOM networking protocols (DICOM C-STORE, C-FIND, C-MOVE) and DICOMweb services
- Knowledge of security frameworks, encryption, and identity management solutions
- Understanding of medical imaging modalities (CT, MRI, X-Ray, PET, Ultrasound) and clinical workflows
- Knowledge of clinical trial processes, regulatory requirements, and quality management systems
- Familiarity with AI applications in medical imaging (computer-aided diagnosis, image segmentation, etc.)
- Good technical communication skills with ability to work effectively in cross-functional teams
- Ability to communicate technical concepts to clinical and business stakeholders
- Ability to balance technical requirements with business objectives
- Understanding of DICOM standard implementation, including DICOM conformance statements and IHE integration profiles
- Understanding of medical imaging modalities (CT, MRI, X-Ray, PET, Ultrasound) and their specific DICOM implementations
- Knowledge of clinical trial processes, regulatory requirements, and quality management systems
- Familiarity with AI applications in medical imaging using DICOM datasets
Behavior Competencies:
- Accountability
- Adaptability
- Customer focus
- Robust
- Decision Making
- Business Acumen
- Results orientation
- Time Management
- Willingness to learn
- Team collaboration
Experience, Education and Certifications:
- Substantial post-qualification software development experience with a strong track record of delivering solutions in medical imaging or healthcare technology
- Experience developing cloud-native applications and SaaS components
- Experience with AI/ML integration in production environments, preferably in medical imaging
- Experience with regulated software development (FDA, GxP, ISO 13485) processes
- Background in medical imaging file formats, processing libraries, and viewer integrations
- Experience with clinical trial management systems or electronic data capture (EDC) platform.
- Solid expertise in cloud platforms with a strong understanding of serverless and scalable architectures, modern cloud-native services, and integration with AI/ML services
- Proficiency in developing RESTful APIs, GraphQL, and real-time communication protocols
- Experience with medical imaging standards (DICOM, HL7 FHIR) and DICOM processing libraries (pydicom, DCMTK, GDCM)
- Experience with DICOM standard implementation, including DICOM parsing libraries and tag manipulation
- Exposure to AI/ML solutions within imaging platforms, as well as MLOps practices
- Experience in database design for both relational and NoSQL systems
- Experience with medical image viewer technologies and PACS integration
- Experience working in regulated environments
- Experience with DICOM image processing workflows, anonymization techniques, and metadata preservation
- Experience with medical image viewer technologies, PACS integration, and DICOM routing workflows
- Proficiency in Java, Python, or C# for backend development
