Engineer - Technical SME, EHS & Sustainability

The Engineer - Technical SME, EHS & Sustainability performs defined configuration, testing, documentation and technical support activities for Engineering, EHS and Sustainability central applications used on manufacturing sites globally.

The job holder supports Engineers, Product teams, Service teams and site users by executing technical tasks, gathering diagnostic evidence and maintaining accurate specifications, configuration records, test evidence and knowledge content.

The role resolves routine technical issues within delegated authority and escalates complex design, operational, batch-impact or data-integrity concerns promptly to more senior technical roles.

Key Responsibilities:

• Implement technical solutions (scripts, SQL queries etc.) and configurations in accordance with approved architecture and product strategy.
• Support technical quality for the assigned scope, including specifications, design documentation, configuration records and technical validation evidence.
• Perform troubleshooting and root-cause analysis, with timely escalation where manufacturing batches, product quality, patient supply or data integrity may be affected.
• Support design and configuration of: interfaces, workflows, recipes, data models and environments.
• Analyse logs, metrics, monitoring and system behaviour to identify defects, performance issues and opportunities for improvement.
• Configure approved solutions using standard engineering procedures and detailed instructions.
• Support preparation and update of technical specifications, configuration documentation and validation records.
• Execute defined technical tests, capture evidence and record defects accurately.
• Review logs, alerts and monitoring information and gather evidence for investigation.
• Support deployment, migration, upgrade and environment activities.
• Maintain technical records, configuration inventories, runbooks and knowledge articles.
• Escalate technical risks and unresolved issues in line with documented criteria.
• Support site engineers and super users during implementation and operation.
• Configure, test and support AI-enabled solutions and integrations.
• Evaluate AI-generated outputs for accuracy, relevance and business usability.

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, AI, cloud, integration, automation, data, validation, cyber security or engineering certifications are desirable.
• Typically 1 to 3 years of experience in technical support, software or platform engineering, automation, integration, data, testing or a related technical role (Preferably in Engineering, EHS & Sustainability domain).
• Experience performing configuration, testing or technical support activities using documented standards and procedures.
• Experience creating or updating technical records, specifications, test evidence, configuration inventories or knowledge articles.
• Ability to review logs, alerts, metrics and error information and gather evidence for investigation.
• Experience supporting deployments, upgrades, environment activities or defect resolution.
• Ability to collaborate with Engineers, Product teams, Service teams, site users and suppliers.
• Familiarity with security, data integrity, change, validation and documentation controls.
• Ability to learn technical platforms and escalate issues when complexity or risk exceeds delegated authority.
• Hands-on experience with Generative AI solutions (Copilot, Azure OpenAI, AI assistants, chatbots, etc.).
• Experience testing and validating AI or data-driven solutions.
• Experience working with structured and unstructured data.
• Experience using Python, SQL or similar technologies to solve business problems.

Preferred qualifications:

• Strong analytical and structured problem-solving skills.
• 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.
• Attention to detail and disciplined adherence to approved procedures.
• Willingness to seek guidance where technical authority or risk thresholds are unclear.
• Understanding of Generative AI and Large Language Models (LLMs).
• Prompt engineering and AI output evaluation.
• Python and/or SQL for data analysis, testing and troubleshooting.
• API and system integration knowledge (REST, JSON).
• Understanding of responsible AI, data privacy and security principles