Principal Engineer - QA systems

Job Summary

The Senior Technical SME for QA Systems provides technical leadership across the Quality Assurance product family and technology platforms, including Veeva, SAP, Mendix and AI-enabled automation solutions. The role leads solution design, implementation, validation and troubleshooting, ensuring technical outputs align with approved architecture, product strategy and engineering standards. The role coordinates engineers, site teams, architects, Product Owners, Service Managers and suppliers, acting 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 combines hands-on AI-enabled and automation and software engineering with technical leadership to deliver reusable agents, automation components, integrations and engineering tools. Working closely with the Automation Manager from the Enterprise AI team, the role translates the Quality Assurance AI and automation strategy into practical solutions and drives the technical adoption of AI within the team.

Responsibilities

• Design, develop, test and implement AI-enabled automation and agents capabilities supporting the Quality Assurance platform development team, implementing technical solution designs and configurations in accordance with approved architecture and product strategy.
• Perform troubleshooting and root-cause analysis, with timely escalation where manufacturing batches, product quality, patient supply or data integrity may be affected.
• Own technical quality for the assigned scope, including specifications, design documentation, configuration records and technical validation evidence, and design or configure interfaces, workflows, recipes, data models and environments, writing or reviewing related specifications and test scripts.
• Analyze logs, metrics, monitoring and system behavior to identify defects, performance issues and opportunities for improvement, and 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, and assess technical risks to ensure mitigation addresses security, compliance, resilience, data integrity and supportability.
• Provide technical direction during complex incidents, releases and stabilization and coordinate internal and supplier engineering resources.
• Maintain technical standards and reusable engineering assets for the assigned product family or platform, and establish reusable artificial intelligence engineering standards, reference architectures and design patterns, while coaching engineers and suppliers.
• Drive engineering lessons learned and cross-team continuous improvement, defining artificial intelligence evaluation strategies, acceptance criteria, test evidence and production-readiness decisions.
• Ensure appropriate controls for responsible artificial intelligence, data privacy, cybersecurity, human oversight, traceability and regulated change, and lead complex investigations into artificial intelligence quality, retrieval, data, integration and operational issues.

Basic Qualifications

• Bachelor's or master's degree in engineering, Computer Science, Information Technology, Automation, Data, Life Sciences or another technical discipline, or equivalent practical experience.
• Experience with technical, cloud, integration, automation, data, validation, cyber security or engineering certifications.
• Minimum of five years of hands-on technical engineering experience in large-scale enterprise or operational technology environments.
• Experience leading technical design and implementation for a product family, platform, programme or multiple sites, and reviewing and approving specifications, design documents, configurations, test scripts and technical validation evidence.
• Experience leading troubleshooting and root-cause investigations across systems, interfaces, workflows, data and infrastructure, and coordinating internal engineers, site teams, vendors and specialist partners through design, deployment and stabilization activities.
• Experience assessing technical risk and ensuring security, data integrity, resilience, compliance and supportability requirements are met.
• Experience coaching engineers and converting lessons learned into reusable standards, patterns and knowledge assets.
• Experience leading at least one artificial intelligence or generative artificial intelligence solution from design through testing, controlled release and operational support.
• Experience supporting audits, inspections and formal technical assurance activities, and designing or providing technical assurance for intelligent automation solutions.
• Experience defining artificial intelligence evaluation datasets, measurable acceptance criteria and risk-based test strategies, and integrating artificial intelligence services with enterprise applications, data sources and workflow platforms.
• Experience providing technical directions to engineers, suppliers and multidisciplinary delivery teams.

Preferred Qualifications

• Apply analytical and structured problem-solving methods to technical engineering and automation activities l and structured problem-solving skills applied to technical engineering and automation activities.
• Experience in Translating architecture and product direction into technical designs and implementation plans.
• Experience in Producing technical documentation and maintaining specifications, designs, test evidence and configuration records in line with governance requirements.
• Experience in interfaces, workflows, data, environments, monitoring and operational support practices.
• Experience in security, quality, validation, data integrity, resilience and change control requirements.
• Collaborates across global business, site, engineering, architecture, product, service and supplier teams, contributing to continuous improvement activities with focus on standardization, reuse, automation and knowledge sharing.
• Provides technical leadership by reviewing designs against requirements and standards, proposing improvements, and providing coaching and structured knowledge transfer within engineering and operations teams.
• Communicates technical risk and recommendations to governance forums and senior stakeholders using inclusive and accessible language, drawing on applied knowledge of generative artificial intelligence, large language models, machine learning and retrieval-augmented generation.
• Designs architectures that integrate artificial intelligence models with enterprise data, applications, application programming interfaces, and workflows.
• Knowledge of artificial intelligence evaluation, including correctness, groundedness, relevance, consistency, safety and regression testing, and knowledge of responsible artificial intelligence, privacy, cybersecurity, prompt injection, data leakage and human-in-the-loop controls.

Skills

• Agile Methodology
• Cross-Functional Teamwork
• Data Analysis
• Design Thinking
• DevOps
• Prioritization
• Product Development Research
• Product Roadmapping
• Project Management
• Return on Investment (ROI)
• Software Development
• Strategy Deployment
• User Experience (UX)
• User Interface (UI) Design

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.