Process Engineer II, Manufacturing Science & Technology (MSAT)

Position Summary:

Process Engineer II, Manufacturing Science & Technology (MSAT) drives process optimization, technology transfer, and manufacturing scalability across Empower's 503A and 503B operations. Leveraging AI-enabled analytics, predictive modeling, and digital manufacturing systems, the role improves process performance, compliance, and operational efficiency. Success requires strategic thinking, execution rigor, learning agility, and technical expertise within a hyper-growth, highly regulated environment. P80–P90 talent demonstrates accountability, innovation, collaboration, and problem solving supporting manufacturing excellence and business performance.

Responsibilities: 

Process Development

• Process Optimization: Develops and improves manufacturing processes supporting efficiency, scalability, and compliance. Utilizes AI-enabled analytics and process intelligence tools to reduce variability, strengthen performance, and support reliable production execution, including packing operations.
• Technology Transfer: Supports technology transfer activities ensuring successful transition from development to commercial manufacturing. Leverages AI-powered analytics and operational dashboards to improve readiness, process consistency, and product commercialization.
• Process Validation: Executes process validation activities supporting manufacturing readiness and regulatory compliance. Applies AI-assisted analytics and statistical tools to strengthen process control, reduce risk, and support sustainable manufacturing performance.

Manufacturing Support

• Technical Troubleshooting: Investigates manufacturing challenges, process deviations, and performance issues impacting quality or throughput. Utilizes AI-enabled analytics and root cause methodologies to accelerate issue resolution and improve process reliability.
• Operational Collaboration: Partners with Manufacturing, Quality, Regulatory Affairs, Validation, Engineering, and R&D teams supporting process improvements and operational objectives. Leverages AI-powered collaboration tools to strengthen communication and execution.
• Data Analysis: Evaluates manufacturing data, process trends, and performance metrics supporting data-driven decision-making. Applies AI-assisted analytics and statistical methodologies to identify opportunities and improve operational efficiency.

Continuous Improvement

• Innovation Support: Implements manufacturing solutions improving efficiency, product quality, and scalability. Utilizes AI-enabled analytics and automation technologies to strengthen process performance and support enterprise growth.
• Risk Management: Identifies process risks and manufacturing challenges impacting quality or compliance. Applies AI-powered predictive analytics and risk assessment methodologies to improve process control and mitigation planning.
• Operational Excellence: Drives continuous improvement initiatives supporting manufacturing performance and process reliability. Leverages AI-assisted workflow optimization and performance analytics to improve execution quality and operational consistency.

Knowledge and Skills:

• Strong expertise in pharmaceutical manufacturing processes, process optimization, technology transfer, process validation, statistical process control, manufacturing science principles, and packing operations.
• Proficiency using AI-enabled analytics platforms, manufacturing execution systems, statistical software, process monitoring technologies, and digital manufacturing tools supporting operational excellence.
• Develop the Manufacturing Batch Record (MBR) and Packing Record, process flow, conduct site gap analyses, and prepare summary reports upon completion of engineering trials and stability batches.
• Advanced knowledge of cGMP requirements, process validation methodologies, continuous improvement principles, risk-based decision-making, and regulated manufacturing operations.
• Excellent analytical, problem-solving, project management, and communication skills with the ability to lead cross-functional initiatives and support complex manufacturing environments.

Experience and Qualifications: 

• Bachelor's degree in Chemical Engineering, Pharmaceutical Sciences, Engineering, or a related scientific discipline required.
• Minimum of four years of process engineering, manufacturing science, process development, or related experience within pharmaceutical, biotechnology, or regulated manufacturing environments preferred.
• Experience supporting technology transfer, process validation, scale-up activities, manufacturing troubleshooting, and continuous improvement initiatives strongly preferred.
• Familiarity with manufacturing execution systems, statistical analysis software, AI-enabled process analytics, and digital manufacturing technologies preferred.

Certificates, Licenses, Registrations:

• Lean Six Sigma Green Belt, Certified Pharmaceutical Industry Professional (CPIP), Professional Engineer (PE), or Certified Quality Engineer (CQE) certification preferred.