Innovation Technologist

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