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Designs and governs AI-ready data architecture for a pharmaceutical manufacturing site. Responsibilities include data models, integration, metadata, governance, cloud platforms, AI workflows, LLM and RAG patterns, human-in-the-loop controls, AI lifecycle governance, GxP compliance, validation support, audit readiness, and cross-site architecture leadership. The role also evaluates AI tools, mentors teams, promotes AI literacy, and drives analytics and AI adoption across manufacturing and quality functions.

The Principal Automation Engineer will design, verify, and validate DeltaV automation systems and support GMP manufacturing operations. Responsibilities include system administration, collaboration with quality and engineering teams, and mentoring others in safety and engineering principles.

Lead development of agentic AI systems that autonomously plan, execute, analyze, and optimize laboratory experiments. Build integrations with robotic platforms and analytical instruments, implement closed-loop learning, deploy reliable containerized services, and ensure experiment data supports downstream model training. Own the platform roadmap, reliability, adoption, and technical direction while managing and mentoring a team of scientist-engineers. Collaborate with chemists, biologists, automation engineers, NVIDIA, vendors, and senior R&D leadership.

Leads software engineering teams and owns technical strategy, architecture, roadmaps, budgets, staffing, and operational health across application or platform domains. Guides development of scalable web and cloud solutions, engineering standards, AI-enabled capabilities, and modernization initiatives. Partners with product, business, medical, regulatory, and executive stakeholders while developing technical leaders, managing vendors, improving delivery processes, and ensuring security, privacy, reliability, and regulatory compliance.

Owns enterprise processes for capital invoice management, payment assurance, forecast validation, earned value management, and cost assurance across a global capital portfolio. Establishes governance, controls, standards, KPIs, and business requirements; partners with Finance, Procurement, Legal, Engineering Systems, and Project Controls; validates invoices and forecasts; manages compliance and performance assurance; and develops training and adoption resources.

Leads performance governance for a capital project network, overseeing portfolio metrics, audits, after-action reviews, project controls compliance, capacity forecasting, delivery assurance, contractor cost reviews, contract exhibits, and process adherence. The role trains project teams on standards, coordinates PMO and governance support, tracks corrective actions, and influences senior stakeholders across pharmaceutical manufacturing capital projects.

Leads engineering design delivery for complex pharmaceutical manufacturing capital projects. Coordinates internal teams, external design firms, project managers, and technical stakeholders across design and verification phases. Establishes design requirements, standards, schedules, governance, and verification plans; resolves technical issues; supports value engineering, cost reduction, risk assessments, discrepancy management, and design best-practice adoption. Requires extensive pharmaceutical or API manufacturing engineering experience and regular project-site work.

Architects and delivers enterprise data, analytics, machine learning, generative AI, and agentic AI products for pharmaceutical manufacturing and quality operations. Leads technical product pods, defines scalable data architectures and pipelines, guides engineering and data science teams, and advances solutions from prototypes to governed production systems. Applies quality assurance, GxP, validation, cybersecurity, data integrity, and responsible AI principles to regulated workflows including CAPA, deviations, audits, inspection readiness, and quality risk management. Partners with business and technology leaders to drive reusable, secure, and measurable digital capabilities.

Engineer agentic AI and automation integrations connecting planning systems with laboratory instruments, robotic platforms, ELN/LIMS, and data pipelines. Build multi-agent workflows with orchestration, state management, tool integration, error recovery, and human oversight. Deploy containerized services using Docker, Kubernetes, Argo, GitOps, and CI/CD. Collaborate with scientists, automation engineers, and NVIDIA researchers to transition prototypes into reliable autonomous experimentation systems for drug discovery.

Own end-to-end security architecture and risk posture for a strategic, AWS-heavy program protecting trade secrets and sensitive intellectual property. Lead cloud and application security reviews, threat modeling, risk assessments, control design, and risk acceptance. Develop secure reference architectures, design patterns, standards, and guidance across cloud platforms, data flows, identity, and integrations. Provide technical leadership, mentorship, and security direction while communicating risks effectively to technical, business, audit, and executive stakeholders.