Site Forward Deployed Engineer
GSK
Business Introduction GSK remains committed to achieving bold commercial ambitions for the future. By 2031, we aim to deliver £40 billion in annual sales, leveraging our existing strong performance momentum to significantly increase our positive impact on the health of billions of patients globally. Our Ahead Together strategy is centred on early intervention to prevent and alter the course of disease, thereby protecting people and supporting healthcare systems. Our diverse portfolio consists of vaccines, specialty medicines, and general medicines. Through continuous innovation and a dedicated focus on scientific and technical excellence, we strive to develop and launch new, groundbreaking treatments that address critical health challenges. Job Purpose New strategic role established to provide on-site technology leadership, product engagement, and delivery support at key manufacturing sites while acting as the interface between local business stakeholders and global digital product teams. Embed directly with GSC site and business teams to rapidly translate high-priority Smart Manufacturing and AI opportunities into working PoCs, PoVs, and MVPs. Apply AI-native engineering methods to validate business value, technical feasibility, and governance requirements, provide evidence-based kill or continue recommendations, and hand proven solutions to the respective product teams for production scale-up and lifecycle management. This role is equivalent in scope and seniority to an Associate Director or Senior Manager position. Key responsibilities This role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following:
- Embed with strategic GSC sites and business teams to understand operational challenges, workflows, data, constraints, and high-value opportunities.
- Translate priority Smart Manufacturing, AI, Data and Digital opportunities into clearly framed, measurable use cases and executable technical solutions.
- Design, build and validate working PoCs, PoVs and MVPs using real site data, systems and workflows, with delivery measured in days or weeks rather than extended discovery cycles.
- Provide hands-on engineering across AI, data, integration, applications and automation, using AI-assisted development and agent-based workflows where appropriate.
- Make evidence-based continue, adapt or stop recommendations based on demonstrated business value, technical feasibility, adoption potential, risk and scalability.
- Incorporate GSK requirements for Code Orange, Responsible AI, cybersecurity, data governance, privacy, GxP and architecture governance from the start of each engagement.
- Partner with the respective GSK & GSC product teams to transition validated solutions for industrialization, scaling, operational support and lifecycle ownership.
- Resolve deployment barriers across legacy systems, fragmented data, integration, security, compliance and local operating processes in collaboration with site and product teams.
- Convert site-specific learning into reusable agents, integration patterns, prompt templates, reference architectures and product requirements that benefit other GSC strategic sites.
- Build site capability through collaborative delivery, technical coaching, documentation and knowledge transfer, while providing structured feedback to GSK & GSC product and platform roadmaps.
- Bachelor’s degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, Engineering, Information Technology, Manufacturing Systems, or a related technical discipline.
- 6+ years of job-related experience in technology, engineering, data, AI, digital, or manufacturing environments.
- Experience delivering AI, Data & Analytics, Smart Manufacturing, or Digital transformation initiatives within manufacturing or supply chain environments.
- Software engineering experience using modern application development frameworks.
- Experience with Generative AI, AI agents, prompt engineering, retrieval-augmented generation (RAG), or AI-assisted development approaches.
- Experience developing proofs of concept (PoCs), proofs of value (PoVs), or minimum viable products (MVPs).
- Experience working directly with business stakeholders to identify, shape, and deliver technology solutions.
- Experience working across cross-functional product, data, engineering, or business teams.
- Master’s degree in Artificial Intelligence, Computer Science, Data Science, Software Engineering, Manufacturing Informatics, Digital Transformation, Technology Management, or a related discipline.
- Proficiency in Python or another relevant programming language.
- Knowledge of manufacturing operations, business processes, and operational technology environments.
- Knowledge of Responsible AI, cybersecurity, privacy, data governance, and GxP-regulated environments.
- Cloud platform and modern data platform experience, including Azure.
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