Application Architect, Perceptive Imaging

Design, document, and communicate scalable, multi-tenant SaaS architectures using cloud-native services, selecting technology components and design patterns.

Architect and document microservices-based systems optimized for medical imaging data processing and AI workloads.

Analyse requirements and produce specifications to ensure solutions will have appropriate auto-scaling, load balancing, and distributed computing strategies for handling large medical imaging datasets.

Design and document secure API-first services for seamless integration with clinical trial systems.

Ensure platform scalability to support multiple concurrent clinical trials and imaging workflows.

Document design decisions and low-level designs following the C4 model.

Define the integration approach of AI/ML models for medical image analysis, including genAI, agentic ai, computer vision and deep learning algorithms.

Create low-level designs which enable the real-time and batch processing of medical imaging data (DICOM, NIfTI, etc.).

Scope and design efficient DICOM image pre-processing workflows.

Architect integration layers for third-party medical imaging viewers (OHIF, Cornerstone.js, or proprietary systems).

Design and agree APIs and SDKs for seamless integration with existing clinical trial management systems.

Ensure designs are cross-platform compatible and will provide a responsive design for various devices and browsers.

Design systems compliant with FDA 21 CFR Part 11, GxP, HIPAA, and international medical device regulations.

Create strategies and designs which will lead to the implementation of comprehensive audit trails, electronic signatures, and data integrity controls.

Architect security frameworks including encryption at rest and in transit, role-based access control, and secure authentication.

Design disaster recovery and business continuity solutions for critical clinical trial data.

Ensure compliance with medical data privacy regulations across multiple jurisdictions.

Design high-performance database architectures optimized for medical imaging metadata and AI model outputs.

Perform analysis of business features to create and maintain both logical and physical data models.

Design solutions which enable the storage, analysis, access, and movement of large-scale medical imaging datasets.

Design efficient data partitioning and indexing strategies for multi-dimensional medical data.

Architect real-time data streaming solutions for live imaging analysis.

Implement data governance frameworks ensuring data quality and lineage tracking.

Design comprehensive monitoring and observability strategies for SaaS platform performance.

Optimize system performance for large medical imaging secure file processing and transfer.

Establish SLAs and implement automated alerting systems for platform reliability.

Engage in technical decisions on technology stack selection for medical imaging and AI workloads, in collaboration with Solution Architect.

Mentor team members to foster their professional, technical, and domain growth and development.

Ensure development is in line with design via code reviews, inspection and discussion.

Join technical architecture reviews and provide guidance on complex system design decisions.

Lead by example, demonstrating strong technical leadership skills and fostering a collaborative and innovative team environment.

Drive adoption of 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.

Work collaboratively with relevant stakeholders.

Mentor engineering teams on best practice in cloud architecture and security and medical imaging standards.

Continuously evaluating new technologies and recommending improvements to enhance the platform’s architecture and capabilities.

Deep 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 designing and implementing APIs (e.g. RESTful, GraphQL) and real-time communication protocols

Experience with medical imaging standards (DICOM, HL7 FHIR) and specialized DICOM processing libraries (pydicom, DCMTK, GDCM)

Extensive experience with DICOM standard implementation, including DICOM parsing libraries, tag manipulation, and compliance validation

Expertise in database design for both relational and NoSQL systems

Comprehensive experience in DevOps methodologies, including CI/CD pipeline automation and infrastructure as code

Strong background in software testing, validation, and quality assurance for regulated medical systems

Experience with medical image viewer technologies and PACS integration

Familiarity with AI applications in medical imaging (computer-aided diagnosis, image segmentation, etc.)

Experience leading cross-functional teams in regulated environments

Deep and wide-ranging post-qualification architecture development expertise, with leadership in complex projects involving medical imaging or healthcare technology

Proven experience designing and developing cloud-native SaaS platforms at enterprise scale

Demonstrated experience with AI/ML integration in production environments, preferably in medical imaging

Experience with regulated software development (FDA, GxP, ISO 13485) and validation processes

Strong background in medical imaging file formats, processing libraries, and viewer integrations

Experience with clinical trial management systems and electronic data capture (EDC) platforms

Experience with DICOM image processing workflows, anonymization techniques, and metadata preservation

Experience with medical image viewer technologies, PACS integration, and DICOM routing workflows

Familiarity with AI applications in medical imaging (computer-aided diagnosis, image segmentation, etc.) using DICOM datasets

Advanced proficiency in Java, Python, or C# for backend development

Experience with modern frontend frameworks (React, Angular) for medical imaging applications

Hands-on experience with cloud services: compute, storage, databases, AI/ML services, and monitoring tools

Experience with CI/CD pipelines, infrastructure as code, and DevOps practices

Experience with monitoring and observability tools

Proficiency in developing and deploying microservices architectures in cloud-based environments

Bachelor's Degree (Master's or PhD’s preferred) in Computer Science, Biomedical Engineering, Software Engineering, or related technical discipline

Additional certifications in cloud platforms (or be prepared to gain qualifications)

Medical device software development training or certification preferred

English: Fluent

Come as you are. We're proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, colour, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.