Principal Engineer – QA systems

Overview

Senior Technical SME providing technical leadership across GSK's Quality Assurance product family and technology platforms (Veeva, SAP, Mendix and AI-enabled automation solutions), leading solution design, implementation, validation and troubleshooting within Enterprise Systems.

What you'll do

• Design, develop, test and implement AI-enabled automation and agent capabilities supporting the Quality Assurance platform development team, 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.
• 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.
• 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.
• 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, establish reusable AI engineering standards, reference architectures and design patterns, and coach engineers and suppliers.
• Drive engineering lessons learned and cross-team continuous improvement, defining 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, and lead complex investigations into AI quality, retrieval, data, integration and operational issues.

What you'll need

• 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.
• 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 AI 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 AI evaluation datasets, measurable acceptance criteria and risk-based test strategies, and integrating AI services with enterprise applications, data sources and workflow platforms.
• Experience providing technical direction to engineers, suppliers and multidisciplinary delivery teams.

Nice to have

• Apply analytical and structured problem-solving methods to technical engineering and automation activities.
• Experience translating architecture and product direction into technical designs and implementation plans.
• Experience producing technical documentation and maintaining specifications, designs, test evidence and configuration records in line with governance requirements.
• Experience with interfaces, workflows, data, environments, monitoring and operational support practices.
• Experience with 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 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.
• Communicates technical risk and recommendations to governance forums and senior stakeholders using inclusive and accessible language, drawing on applied knowledge of generative AI, large language models, machine learning and retrieval-augmented generation.
• Designs architectures that integrate AI models with enterprise data, applications, application programming interfaces, and workflows.
• Knowledge of AI evaluation, including correctness, groundedness, relevance, consistency, safety and regression testing, and of responsible AI, privacy, cybersecurity, prompt injection, data leakage and human-in-the-loop controls.

Details

• Location: Bengaluru Luxor North Tower.