Process Engineer II, Manufacturing Science & Technology (MSAT)

Empower Pharmacy•Houston, TX

3d•Onsite

About The Position

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.

Requirements

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.
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.

Nice To Haves

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

Responsibilities

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.
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.
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.
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.
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.
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.
Implements manufacturing solutions improving efficiency, product quality, and scalability. Utilizes AI-enabled analytics and automation technologies to strengthen process performance and support enterprise growth.
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.
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.