On-Site AI & Smart Manufacturing Engineer

GlaxoSmithKline plc; Barnard Castle; On-site; GBP 120,000 - 180,000; Full time

Job summary

GlaxoSmithKline Barnard Castle seeks a senior technologist to embed within site teams, translating manufacturing challenges into AI-enabled solutions. Lead the design, validation and deployment of PoCs, PoVs and MVPs using real plant data and workflows.

You will apply AI-native engineering methods to validate value, feasibility, and governance, delivering evidence-based recommendations and scaling successful solutions with product teams. A strong, collaborative mindset is essential.

Qualifications

• Relevant degree in Computer Science, Software Engineering, Data Science, AI, Engineering or related field.
• Experience delivering AI, data analytics, Smart Manufacturing or digital transformation in manufacturing or supply chain.
• Strong software engineering skills; Python desirable; knowledge of modern frameworks.

Responsibilities

• Embed with site teams to translate challenges into measurable use cases and executable solutions.
• Design, build and validate PoCs, PoVs and MVPs using real site data and workflows.
• Provide hands-on engineering across AI, data, integration, applications and automation.
• Make evidence-based continue/adapt/stop recommendations based on business value and feasibility.
• Address deployment barriers across legacy systems and data with site and product teams.
• Collaborate with product teams to transition validated solutions for industrialization.

Skills

Agile Methodology

Cross-Functional Teamwork

Data Analysis

Design Thinking

DevOps

Prioritization

Product Development Research

Product Roadmapping

Project Management

ROI

Software Development

Strategy Deployment

UX

UI Design

Tools

Python

Job description

GlaxoSmithKline Barnard Castle seeks a senior technologist to embed within site teams, translating manufacturing challenges into AI-enabled solutions. Lead the design, validation and deployment of PoCs, PoVs and MVPs using real plant data and workflows.

You will apply AI-native engineering methods to validate value, feasibility, and governance, delivering evidence-based recommendations and scaling successful solutions with product teams. A strong, collaborative mindset is essential.