Work ScheduleStandard (Mon-Fri)Environmental ConditionsOfficeJob DescriptionThe 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 ResponsibilitiesSolution Design & Full-Stack DevelopmentDesign, develop, test, and deploy end-to-end components of web-based and digital applicationsTranslate business problems and user needs into clear technical requirements, solution designs, and working outputsDevelop maintainable front-end and back-end services using appropriate software-engineering patterns and standardsIntegrate applications with enterprise platforms, APIs, databases, and third-party servicesApply user-centred design and UX/UI principles to create intuitive, accessible, and effective user experiencesIndependently resolve moderately complex technical problems and contribute to solution architecture decisions within assigned projectsAI, Machine Learning & Data EngineeringDesign, build, and integrate AI, machine-learning, generative-AI, and agent-based capabilities into digital solutionsEvaluate models, frameworks, and technical approaches against defined business, user, performance, risk, and compliance requirementsDevelop scalable data pipelines and data-processing components for structured and unstructured dataPrepare, transform, validate, and monitor data to support reliable analytics and AI-enabled functionalityApply responsible-AI, data-governance, privacy, and security principles throughout solution developmentDocument model behaviour, data lineage, technical assumptions, limitations, and evaluation resultsDevelopment Lifecycle & Engineering QualityFollow established software development lifecycle, agile delivery, coding, testing, release, and change-control practicesUse source control, automated testing, code review, continuous integration, and continuous delivery practices to maintain solution qualityCreate and maintain clear technical documentation, including designs, code documentation, test evidence, deployment instructions, and support informationMonitor solution performance, troubleshoot defects, and implement improvements within the scope of assigned projectsContribute to reusable technical patterns, development standards, and shared engineering practicesIdentify technical risks, dependencies, and constraints and escalate them with clear recommendationsRegulatory Compliance & ValidationDevelop solutions in alignment with applicable GxP, quality, privacy, cybersecurity, and data-integrity requirementsEnsure relevant solution components support compliance with 21 CFR Part 11 and associated electronic-record and electronic-signature controlsSupport computer-system validation activities, including requirements traceability, risk assessment, test execution, evidence generation, and issue resolutionMaintain development and validation documentation to support inspection and audit readinessApply ALCOA+ and related data-integrity principles to the design, processing, storage, and use of regulated dataCollaborate with quality, regulatory, privacy, security, and validation specialists to resolve compliance requirements and risksCollaboration & Stakeholder EngagementCollaborate with business stakeholders, clinical-trial subject-matter experts, product or project leads, designers, data specialists, and technology teamsExplain technical concepts, options, risks, and trade-offs clearly to technical and non-technical audiencesParticipate in discovery, requirements, design, demonstration, and review sessions, contributing practical technical insightWork effectively within multidisciplinary and geographically distributed project teamsProvide transparent progress updates and contribute to project planning, estimation, and prioritisationCommunicate professionally in English with global colleagues and stakeholders in written and spoken settingsQualifications and RequirementsRequiredBachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, Engineering, or a related discipline, or equivalent practical experience2-4 years of relevant experience in software development, data engineering, AI/ML engineering, or a related technical roleHands-on experience developing full-stack applications using modern front-end and back-end technologiesExperience working with databases, APIs, data integration, and software-testing practicesWorking knowledge of cloud platforms, preferably AWS or Microsoft AzureAbility to work independently on moderately complex technical problems and deliver reliable outputs across multiple projectsProfessional working proficiency in spoken and written English, sufficient to collaborate effectively with global teams, participate in technical discussions, and produce clear documentationStrong analytical, problem-solving, collaboration, and communication skillsPreferredExperience with AI/ML frameworks, large language models, generative-AI applications, or agent-based solutionsExperience building data pipelines, analytics platforms, or cloud-native applicationsExperience applying UX/UI and user-centred design principles in software developmentExperience in clinical research, clinical trials, life sciences, healthcare, or another regulated environmentFamiliarity with GxP, 21 CFR Part 11, computer-system validation, data integrity, and audit-readiness requirementsExperience with agile delivery, DevOps, CI/CD, infrastructure as code, containerisation, or automated testingExperience working in global, cross-functional, or distributed teamsSkillsFull-stack development: Ability to design and build reliable front-end, back-end, API, and database componentsAI and machine learning: Ability to develop, integrate, evaluate, and monitor AI/ML and agent-based capabilitiesData engineering: Ability to create scalable data pipelines and maintain data quality, lineage, security, and integrityCloud engineering: Ability to develop and deploy solutions using AWS, Microsoft Azure, or comparable cloud servicesUser-centred development: Ability to translate user needs into intuitive and accessible digital experiencesEngineering quality: Strong application of secure coding, testing, source control, documentation, CI/CD, and maintainability practicesRegulatory awareness: Ability to develop within GxP, 21 CFR Part 11, validation, privacy, security, and data-integrity constraintsProblem-solving: Ability to analyse moderately complex technical problems, evaluate options, and deliver practical solutions independentlyCommunication: Ability to communicate technical information clearly in English to global technical and non-technical stakeholdersCollaboration: Ability to work effectively across business, clinical, design, data, quality, and technology disciplines