Senior Lead, Forward Deployed Engineer

About the Role Do you enjoy turning Medical Affairs opportunities into practical digital, data, analytics, and AI solutions? Can you work closely with business and technical teams, learn complex workflows, and contribute to rapid prototypes and production-ready capabilities? As a Senior Lead, Forward Deployed Engineer, for Global Medical Affairs Digital & Tech, you will work alongside product teams, data scientists, GSK Strategic Partner engineering resources to build solutions that improve Medical Affairs solutions Data Generation, Scientific Communications, Medical Information, MSL Engagement and Insights. With support from experienced engineers and product leaders, you will contribute from discovery and rapid validation through production deployment, adoption, and continuous improvement. The focus is on building working, trusted software and analytics that fit real workflows and deliver measurable Medical Affairs value. Why This Role Exists Global Medical Affairs needs hands-on engineers who can help connect business questions, scientific workflows, fragmented data, and scalable technology. This role combines customer collaboration, rapid engineering, production delivery, and reusable platform thinking, while providing the coaching and structure needed to grow technical depth and business understanding. • Proves value quickly — helps frame priority problems and builds PoCs, PoVs, and MVPs using real data and workflows. • Supports production delivery — contributes to engineering validated concepts for secure, reliable, compliant, and supportable use. • Builds for reuse — creates components and patterns that can be adapted across therapy areas, regions, teams, and use cases. • Improves decisions and impact — develops solutions that help Medical Affairs understand performance, identify opportunities, and act. • Works effectively with partners — collaborates with GSK Tech strategic partners and engineering teams to deliver well-designed solutions that can be supported in production. Key Responsibilities Embedded Discovery, Prototyping and Value Validation • Work with Medical Affairs teams to understand scientific and operational workflows, user needs, data constraints, and measures of value. • Contribute to priority use cases from problem framing through PoC, PoV, and MVP using short delivery cycles and direct user feedback. • Build prototypes with representative data and real workflows, testing feasibility, usability, data quality, and potential business value. • Document findings and evidence to continue, pivot, or stop recommendations led by product and technical leaders. Production Engineering and Scale • Contribute to the transition from validated MVP to production, including design, engineering, integration, testing, security, deployment, monitoring, documentation, and support readiness. • Build reliable, maintainable solutions that follow established GSK Digital and Tech requirements for privacy, quality, compliance, performance, resilience, and user experience. • Develop configurable components, reusable services, data products, and patterns that support expansion across Medical Affairs teams and use cases. • Implement product measures and production telemetry to track adoption, service performance, data quality, and opportunities for improvement. • Investigate defects and technical debt, escalating complex decisions and balancing delivery speed with maintainability. Medical Affairs Solutions • Data Generation: contribute to Data Generation products that improve visibility across evidence planning, study execution, evidence generation, data quality, analysis, and reporting. • Scientific Communications: develop Digital, AI and Tech capabilities across medical writing, publications, congress activity, content development, scientific dissemination, reach, engagement, and impact. • Medical Information: build AI-enabled features that identify inquiry trends, knowledge gaps, response performance, content needs, and emerging scientific questions while supporting accurate and compliant operations. • MSL Engagement: contribute to solutions that strengthen planning, engagement and measurement of scientific exchange, stakeholder engagement, field insights, content use, and follow-up. • Cross-functional impact measurement that connect data across these domains to create trusted, dashboards, analytical/insights products, and decision-support experiences. AI-Native Engineering • Use approved AI coding assistants and agent-based workflows for coding, testing, review, documentation, and operational support, applying human judgement and validation throughout. • Apply GenAI, machine learning, natural language processing, knowledge retrieval, and analytics patterns under established technical guidance when appropriate to the problem. • Implement human-in-the-loop controls, evaluation tests, and monitoring so AI-enabled capabilities remain accurate, explainable, responsible, and fit for Medical Affairs use. Basic Qualifications • 3–5 years of full-stack, data, analytics, or software engineering experience, including meaningful contributions to production applications or data products. • Experience translating defined business or user needs into working software, prototypes, or analytical solutions in collaboration with product and technical colleagues. • Working proficiency in one or more modern programming languages or frameworks. • Hands-on experience in several of the following: data engineering, APIs, cloud platforms, application development, automated testing, DevSecOps, observability, or production support. • Practical exposure to GenAI patterns such as retrieval-augmented generation, prompt engineering, agents, evaluation, or responsible human oversight. • Ability to work with business stakeholders and end users, ask effective questions, explain technical choices, and communicate progress and risks clearly. • Awareness of security, privacy, quality, and compliance expectations