Principal Technical SME and Engineer - EHS & Sustainability

Job description

About the Team: Enterprise Systems is the backbone of GSK’s internal operations in Digital & Tech, enabling GSK Global Functions teams such as Finance, Procurement, HR, Legal, Compliance, WREF, CGA and Corporate Secretariat to run seamlessly. This team designs and delivers cutting-edge digital platforms that power critical processes, ensuring efficiency, compliance, and scalability across the enterprise. Enterprise Systems Management & Business Operations delivers digital solutions that support Enterprise Systems running as a high-performing organisation. This team drives financial discipline, operational rigour and strategic alignment across the ES portfolio that safeguard GSK’s integrity and reputation globally. By joining this team, you’ll help shape systems that support thousands of employees worldwide, driving innovation and reliability in the tools that keep GSK moving forward. Job Purpose: The Senior Technical SME and Engineer for Engineering, EHS & Sustainability provides technical leadership for a product family, technology platform, programme or group of sites. The role leads solution design, implementation, validation and troubleshooting and ensures technical outputs align with approved architecture, product strategy and engineering standards. The role coordinates engineers, site teams, Architects, Product Owners, Service Managers and suppliers and acts as the technical lead for complex delivery and operational issues. The job holder reviews technical specifications, configurations and test evidence and leads root-cause analysis where operational, batch or data-integrity impact may exist. The role also develops engineering capability by coaching engineers and super users and converting lessons learned into reusable designs, standards, training and knowledge. Key Responsibilities: Implement technical solution designs and configurations in accordance with approved architecture and product strategy. Own technical quality for the assigned scope, including specifications, design documentation, configuration records and technical validation evidence. Keep EHS, engineering and sustainability system configuration under version control, peer-reviewed, and covered by repeatable tests. Perform troubleshooting and root-cause analysis, with timely escalation where manufacturing batches, product quality, patient supply or data integrity may be affected. Design or configure interfaces, workflows, recipes, data models and environments and write or review related specifications and test scripts. Analyse logs, metrics, monitoring and system behaviour to identify defects, performance issues and opportunities for improvement. Coach site engineers and super users and contribute to training, runbooks and knowledge articles. Lead technical design and implementation across multiple projects, releases or sites. Review and approve key technical specifications, design documents, configurations, test scripts and validation evidence. Provide technical direction during complex incidents, releases and stabilisation and coordinate internal and supplier engineering resources. Assess technical risks and ensure mitigation addresses security, compliance, resilience, data integrity and supportability. Maintain technical standards and reusable engineering assets for the assigned product family or platform. Support formal technical assurance, audits and inspections and ensure corrective actions are evidence based. Drive engineering lessons learned and cross-team continuous improvement. Lead the end-to-end technical design and implementation of secure, scalable AI and generative AI solutions. Define and approve AI evaluation strategies, acceptance criteria, test evidence and production-readiness decisions. Ensure appropriate controls for responsible AI, data privacy, cybersecurity, human oversight, traceability and regulated change. Lead complex investigations into AI quality, retrieval, data, integration and operational issues. Establish reusable AI engineering standards, reference architectures and design patterns, while coaching engineers and suppliers. Basic qualifications: Bachelor's or Master's degree in Engineering, Computer Science, Information Technology, Automation, Data, Life Sciences or a relevant technical discipline, or equivalent practical experience. Relevant technical, cloud, integration, automation, data, validation, cyber security or engineering certifications are desirable. Typically 7+ years of hands-on technical engineering experience in complex enterprise or operational technology environments (Preferably in Engineering: Plant Maintenance, Calibration, Validation; EHS: Incident&Accident Management, Occupational Health, Industrial Hygiene, Chemical Compliance; Sustainability: Energy Efficiency, Renewable and Clean Energy, Waste Management). Proven experience leading technical design and implementation for a product family, platform, programme or multiple sites. Experience reviewing and approving specifications, design documents, configurations, test scripts and technical validation evidence. Demonstrated leadership of complex troubleshooting and root-cause investigations across systems, interfaces, workflows, data and infrastructure. Experience coordinating internal engineers, site teams, vendors and specialist partners through design, deployment and stabilisation. Experience assessing technical risk and ensuring security, data integrity, resilience, compliance and supportability requirements are met. Experience coaching engineers and translating lessons learned into reusable standards, patterns and knowledge. Experience supporting audits, inspections or formal technical assurance activities. Experience leading at least one AI or generative AI solution from design through testing, controlled release and operational support. Experience designing or technically assuring retrieval-augmented generation, machine-learning or intelligent automation solutions. Experience defining AI evaluation datasets, measurable acceptance criteria and risk-based test strategies. Experience integrating AI services with enterprise applications, data sources and workflow platforms. Experience providing technical direction to engineers, suppliers and multidisciplinary delivery teams. Preferred qualifications: Strong analytical and structured problem-solving skills. Ability to translate architecture and product direction into clear technical designs and implementation activities. Clear technical writing and disciplined maintenance of specifications, designs, test evidence and configuration records. Understanding of interfaces, workflows, data, environments, monitoring and operational support. Awareness of security, quality, validation, data integrity, resilience and change controls. Ability to collaborate across global business, site, engineering, architecture, product, service and supplier teams. Continuous-improvement mindset with emphasis on standardisation, reuse, automation and knowledge sharing. Technical leadership and ability to challenge designs constructively. Coaching and knowledge-transfer capability. Confidence communicating technical risk and recommendations to governance and senior stakeholders. Strong applied knowledge of generative AI, large language models, machine learning and retrieval-augmented generation. Ability to architect solutions integrating AI models with enterprise data, applications, APIs and workflows. Strong understanding of AI evaluation, including correctness, groundedness, relevance, consistency, safety and regression testing. Practical knowledge of Python, SQL, REST APIs, data pipelines and source-control practices such as Git. Strong understanding of responsible AI, privacy, cybersecurity, prompt injection, data leakage and human-in-the-loop controls. #AGTech #GSK-LI Skills Agile Methodology, Backlogs, Cross-Functional Teamwork, Design Thinking, DevOps, Process Diagrams, Product Strategies, Project Management