Site Forward Deployed Engineer

GSK•King of Prussia, PA

About The Position

This strategic role provides on-site technology leadership, product engagement, and delivery support at key manufacturing sites. The engineer acts as the interface between local business stakeholders and global digital product teams, embedding with GSC site and business teams to turn high-priority Smart Manufacturing and AI opportunities into working proofs of concept, proofs of value, and minimum viable products. The role uses AI-native engineering methods to validate business value, technical feasibility, and governance requirements; makes evidence-based recommendations to continue, adapt, or stop work; and transitions validated solutions to product teams for production scale-up and lifecycle management. The position is equivalent in scope and seniority to an Associate Director or Senior Manager role. The engineer delivers hands-on solutions across AI, data, integration, applications, and automation, working with real site data, systems, and workflows. The role incorporates GSK requirements for Code Orange, Responsible AI, cybersecurity, data governance, privacy, GxP, and architecture governance from the outset. It also helps build site capability through collaborative delivery, technical coaching, documentation, and knowledge transfer, while turning site-specific learning into reusable assets and feedback for product and platform roadmaps.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, Engineering, Information Technology, Manufacturing Systems, or a related technical discipline.
At least 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 in 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, proofs of value, or minimum viable products.
Experience working directly with business stakeholders to identify, shape, and deliver technology solutions.
Experience working across cross-functional product, data, engineering, or business teams.

Nice To Haves

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.

Responsibilities

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 measurable use cases and executable technical solutions.
Design, build, and validate PoCs, PoVs, and MVPs using real site data, systems, and workflows, delivering in days or weeks where possible.
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 business value, technical feasibility, adoption potential, risk, and scalability.
Incorporate Code Orange, Responsible AI, cybersecurity, data governance, privacy, GxP, and architecture governance requirements from the beginning of each engagement.
Partner with GSK and GSC product teams to transition validated solutions for industrialization, scaling, operational support, and lifecycle ownership.
Resolve deployment barriers involving 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 for other strategic GSC sites.
Build site capability through collaborative delivery, technical coaching, documentation, and knowledge transfer.
Provide structured feedback to GSK and GSC product and platform roadmaps.