We鈥檙e 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.
Apart from job satisfaction, we can offer you:
HEALTH:
- Medical plan for you and your dependents.
- Personal Accident Insurance
- Life Insurance
- Critical illness cover
WEALTH:
- Salary structure and Flexi basket
- Provident fund of 12%
- Gratuity scheme
YOURSELF: Internal growth and development programs & trainings
Job Summary:
As Principle Software Quality and Test Engineer, Medical Imaging, you will lead the planning, implementation, and continuous improvement of software quality engineering practices to ensure that all software developed for regulated life sciences products complies with applicable standards (e.g., FDA 21 CFR Part 11, ISO 13485, IEC 62304) and delivers safe, effective, and reliable performance. In this role, you must understand the project technically & functionally and implement the test approach defined in the test plan documents. You must also understand the system validation activities, functional and technical aspects of the work and implement the test approach defined with an understanding of how it changes throughout the software development lifecycle (SDLC)
Key Accountabilities
Quality Architecture &Test Strategy
- Design and implement comprehensive quality architectures for multi-tenant SaaS medical imaging platforms
- Architect scalable test automation frameworks optimized for medical imaging workflows and AI/ML validation as requested.
- Establish quality gates and testing strategies across microservices-based systems 路 Design API testing strategies for seamless integration with clinical trial systems 路 Develop comprehensive test strategies that scale across multiple concurrent clinical trials and imaging workflows.
AI/ML Testing & Validation
- Lead the design and implementation of testing frameworks for AI/ML models in medical image analysis, including genAI, agentic AI, computer vision, and deep learning algorithms
- Design and implement validation strategies for real-time and batch processing of medical imaging data (DICOM, NIfTI, etc.)
- Develop comprehensive test approaches for DICOM-compliant data processing pipelines
- Architect performance and accuracy testing for DICOM image preprocessing workflows
- Design monitoring and validation frameworks for AI models in production environments 路 Implement data quality validation for AI training and inference pipelines
Medical Imaging Test Infrastructure
- Architect and implement comprehensive testing solutions for third-party medical imaging viewer integrations (OHIF, Cornerstone.js, or proprietary systems) Design and implement automated testing for APIs and SDKs integrated with clinical trial management systems
- Develop test frameworks for real-time collaboration features across multi-site clinical trials
- Create automated validation for AI-generated insights and annotations 路 Ensure test coverage for cross-platform compatibility across various devices and browsers
- Design test data management strategies for medical imaging workflows
Regulatory Compliance & Security Testing
- Design and implement comprehensive test strategies for FDA 21 CFR Part 11, GxP, HIPAA, GDPR, and international medical device regulations compliance
- Architect automated validation frameworks for audit trails, electronic signatures, and data integrity controls
- Design security testing frameworks including encryption validation, role-based access control testing, and authentication/authorization verification
- Develop disaster recovery and business continuity testing strategies for critical clinical trial data
- Ensure test coverage for medical data privacy regulations across multiple jurisdiction
- Lead CSV (Computer System Validation) activities and maintain validation documentation
Database & Data Quality Testing
- Design comprehensive test strategies for medical imaging metadata and AI model output validation
- Implement automated testing for large-scale medical imaging data storage, retrieval, and processing
- Design data integrity and consistency testing across multi-dimensional medical data
- Architect performance testing for real-time data streaming in live imaging analysis
- Implement data quality validation frameworks and lineage tracking verification
Performance & Scale Testing
- Design and implement comprehensive performance testing frameworks for SaaS platform scalability
- Architect load and stress testing strategies for large medical imaging file processing and secure transfer
- Implement performance validation for caching strategies and CDN solutions across global clinical trial sites
- Design SLA validation frameworks and automated performance regression testing
- Establish performance benchmarks and monitoring for platform reliability
Test Automation & DevOps
- Lead the design and implementation of modern test automation frameworks and CI/CD pipeline integration
- Architect test infrastructure using containerization and serverless technologies
- Implement shift-left testing practices and test-driven development methodologies
- Design and implement continuous testing strategies for automated deployment pipelines
- Establish test observability and reporting frameworks
- Implement infrastructure-as-code for test environments
Technical Leadership
- Engage in technical decisions on test tooling and quality engineering technology stack selection, in collaboration with Solution Architect and development teams
- Mentor team members to foster their professional, technical, and domain growth in quality engineering
- Establish and enforce test standards, quality processes, and best practices via code reviews, inspection, and discussion
- Lead technical architecture reviews for test infrastructure and provide guidance on complex quality engineering decisions
- Lead by example, demonstrating strong technical leadership skills and fostering a collaborative and innovative quality culture
- Drive adoption of quality metrics and KPIs across development teams
Quality Leadership
- Lead cross-functional quality initiatives across product development teams, ensuring software risks are identified, mitigated, and resolved early in the lifecycle.
- Supports Audits: Prepare and present software quality documentation for internal and external audits ensuring audit readiness and compliance
Innovation & Continuous Improvement
- Drive adoption of emerging technologies in test automation, AI/ML testing, and quality engineering tools
- Monitor the market to gather intelligence on emerging quality engineering practices and tools
- Lead initiatives to modernize quality engineering practices while maintaining regulatory compliance
- Share knowledge and insights through presentations, documentation, and training sessions
- Promote innovation in validated environment testing approaches
Other
- Carryout any other reasonable duties as requested.
Functional Competencies (Technical Knowledge/Skills)
- Solid understanding of DICOM standard implementation and testing requirements, including DICOM conformance statement validation and IHE integration profile testing
- Advanced knowledge and experience of testing medical imaging modalities (CT, MRI, X-Ray, PET, Ultrasound) and their specific DICOM implementations
- Expertise in designing test automation frameworks for message queuing systems and high-throughput medical data processing
- Deep knowledge of clinical trial processes, regulatory requirements (FDA 21 CFR Part 11, GxP, HIPAA, GDPR), and quality management systems (ISO 13485, IEC 62304)
- Expertise in AI/ML testing methodologies for medical imaging (computer-aided diagnosis, image segmentation, model validation)
- Proficiency in containerization, serverless architectures, and cloud-native testing strategies
- Advanced knowledge of API testing and real-time communication protocol validation
- Experience in DICOMweb services validation
- Experience in security testing frameworks, encryption validation, and identity management testing
- Advanced knowledge of test data management for medical