Work Schedule
Standard (Mon-Fri)
Environmental Conditions
Office
Job Description
The Innovation Technologist independently designs and delivers end-to-end technical components that translate defined business problems into practical, evidence-led digital solutions. The role combines full-stack development, data engineering, artificial intelligence and machine learning, and user-centred design to create scalable and compliant solutions supporting clinical-trial and regulated business needs.
Working across moderately complex projects, the Innovation Technologist collaborates with business, clinical, data, technology, and design stakeholders to understand requirements, evaluate technical options, develop working solutions, and demonstrate their value. The role operates within established software-development, quality, security, and regulatory frameworks and contributes technical expertise across the innovation and solution-development lifecycle.
Key Responsibilities
Solution Design & Full-Stack Development
- Design, develop, test, and deploy end-to-end components of web-based and digital applications
- Translate business problems and user needs into clear technical requirements, solution designs, and working outputs
- Develop maintainable front-end and back-end services using appropriate software-engineering patterns and standards
- Integrate applications with enterprise platforms, APIs, databases, and third-party services
- Apply user-centred design and UX/UI principles to create intuitive, accessible, and effective user experiences
- Independently resolve moderately complex technical problems and contribute to solution architecture decisions within assigned projects
AI, Machine Learning & Data Engineering
- Design, build, and integrate AI, machine-learning, generative-AI, and agent-based capabilities into digital solutions
- Evaluate models, frameworks, and technical approaches against defined business, user, performance, risk, and compliance requirements
- Develop scalable data pipelines and data-processing components for structured and unstructured data
- Prepare, transform, validate, and monitor data to support reliable analytics and AI-enabled functionality
- Apply responsible-AI, data-governance, privacy, and security principles throughout solution development
- Document model behaviour, data lineage, technical assumptions, limitations, and evaluation results
Development Lifecycle & Engineering Quality
- Follow established software development lifecycle, agile delivery, coding, testing, release, and change-control practices
- Use source control, automated testing, code review, continuous integration, and continuous delivery practices to maintain solution quality
- Create and maintain clear technical documentation, including designs, code documentation, test evidence, deployment instructions, and support information
- Monitor solution performance, troubleshoot defects, and implement improvements within the scope of assigned projects
- Contribute to reusable technical patterns, development standards, and shared engineering practices
- Identify technical risks, dependencies, and constraints and escalate them with clear recommendations
Regulatory Compliance & Validation
- Develop solutions in alignment with applicable GxP, quality, privacy, cybersecurity, and data-integrity requirements
- Ensure relevant solution components support compliance with 21 CFR Part 11 and associated electronic-record and electronic-signature controls
- Support computer-system validation activities, including requirements traceability, risk assessment, test execution, evidence generation, and issue resolution
- Maintain development and validation documentation to support inspection and audit readiness
- Apply ALCOA+ and related data-integrity principles to the design, processing, storage, and use of regulated data
- Collaborate with quality, regulatory, privacy, security, and validation specialists to resolve compliance requirements and risks
Collaboration & Stakeholder Engagement
- Collaborate with business stakeholders, clinical-trial subject-matter experts, product or project leads, designers, data specialists, and technology teams
- Explain technical concepts, options, risks, and trade-offs clearly to technical and non-technical audiences
- Participate in discovery, requirements, design, demonstration, and review sessions, contributing practical technical insight
- Work effectively within multidisciplinary and geographically distributed project teams
- Provide transparent progress updates and contribute to project planning, estimation, and prioritisation
- Communicate professionally in English with global colleagues and stakeholders in written and spoken settings
Qualifications and Requirements
Required
- Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, Engineering, or a related discipline, or equivalent practical experience
- 2-4 years of relevant experience in software development, data engineering, AI/ML engineering, or a related technical role
- Hands-on experience developing full-stack applications using modern front-end and back-end technologies
- Experience working with databases, APIs, data integration, and software-testing practices
- Working knowledge of cloud platforms, preferably AWS or Microsoft Azure
- Ability to work independently on moderately complex technical problems and deliver reliable outputs across multiple projects
- Professional working proficiency in spoken and written English, sufficient to collaborate effectively with global teams, participate in technical discussions, and produce clear documentation
- Strong analytical, problem-solving, collaboration, and communication skills
Preferred
- Experience with AI/ML frameworks, large language models, generative-AI applications, or agent-based solutions
- Experience building data pipelines, analytics platforms, or cloud-native applications
- Experience applying UX/UI and user-centred design principles in software development
- Experience in clinical research, clinical trials, life sciences, healthcare, or another regulated environment
- Familiarity with GxP, 21 CFR Part 11, computer-system validation, data integrity, and audit-readiness requirements
- Experience with agile delivery, DevOps, CI/CD, infrastructure as code, containerisation, or automated testing
- Experience working in global, cross-functional, or distributed teams
Skills
- Full-stack development: Ability to design and build reliable front-end, back-end, API, and database components
- AI and machine learning: Ability to develop, integrate, evaluate, and monitor AI/ML and agent-based capabilities
- Data engineering: Ability to create scalable data pipelines and maintain data quality, lineage, security, and integrity
- Cloud engineering: Ability to develop and deploy solutions using AWS, Microsoft Azure, or comparable cloud services
- User-centred development: Ability to translate user needs into intuitive and accessible digital experiences
- Engineering quality: Strong application of secure coding, testing, source control, documentation, CI/CD, and maintainability practices
- Regulatory awareness: Ability to develop within GxP, 21 CFR Part 11, validation, privacy, security, and data-integrity constraints
- Problem-solving: Ability to analyse moderately complex technical problems, evaluate options, and deliver practical solutions independently
- Communication: Ability to communicate technical information clearly in English to global technical and non-technical stakeholders
- Collaboration: Ability to work effectively across business, clinical, design, data, quality, and technology disciplines