AI-Driven Digital Process Engineer - Warehouse Optimization

Procter & Gamble; United States; On-site; USD 85,000 - 120,000; Full time

Job summary

Procter & Gamble in GRTR CHICAGO FULFILLMENT CTR is seeking a Digital Process Engineer to optimize manufacturing processes and drive digital innovation in warehousing. You will learn required warehousing skills, onboard to IWS, and develop AI-enabled tools to accelerate problem solving and data-driven decisions.

Responsibilities include designing digital processes, analyzing bottlenecks, validating processes (IQ/OQ/PQ), monitoring SPC, and collaborating across R&D, production, quality, and

Qualifications

• A degree in Engineering or a related field is required.
• Prior experience in warehouse operations or process engineering is preferred.
• Strong analytical skills to identify process inefficiencies and propose solutions.
• Foundational AI literacy, including the ability to use AI tools responsibly, interpret AI-generated insights, work with structured data, and partner with technical teams to apply AI solutions in warehouse operations.
• Excellent communication skills to effectively collaborate with team members and other stakeholders.
• A growth mindset with a desire to learn and grow within the role.

Responsibilities

• Design, develop, and implement new digital warehousing processes and optimize existing ones to enhance productivity, reduce costs, and improve product quality.
• Conduct process analysis, identify bottlenecks for warehouse flow, and propose solutions to improve operational efficiency and throughput.
• Develop and execute process validation protocols, including IQ, OQ, and PQ, to ensure compliance with industry standards and internal procedures.
• Monitor process performance using statistical process control (SPC) and other analytical tools, troubleshoot deviations, and implement corrective actions.
• Collaborate with cross-functional teams including R&D, production, quality assurance, and maintenance to support new product introductions and continuous improvement initiatives.
• Prepare detailed technical reports, process documentation, standard operating procedures (SOPs), and training materials.
• Evaluate and recommend new equipment, technologies, and materials to improve process capabilities and product performance.
• Apply AI-enabled tools and methods, including generative AI, predictive analytics, machine learning concepts, and automation workflows, to identify process improvement opportunities, streamline data analysis, reduce manual effort, and support faster, data-driven decision-making.
• Transform complex datasets from diverse sources into actionable insights to inform strategic decision-making and improve operational performance.
• Develop and maintain automated performance scorecards and dashboards for real-time visibility into key operational metrics.
• Prepare data models and features, perform feature quality checks, and build/maintain ETL/ELT pipelines that reliably feed AI products and operational reporting.
• Collaborate closely with operational teams to define solution requirements, ensure successful AI/ML adoption, and drive integration.
• Conduct in-depth data analysis of automation systems, such as picking operations, to identify bottlenecks, improve throughput, and enhance accuracy.
• Ensure all processes comply with safety regulations, environmental standards, and quality management systems.
• Lead and participate in root cause analysis for process failures and implement preventive measures.

Skills

Analytical skills

AI literacy

Communication skills

Growth mindset

Education

Engineering degree or related field

Job description

Procter & Gamble in GRTR CHICAGO FULFILLMENT CTR is seeking a Digital Process Engineer to optimize manufacturing processes and drive digital innovation in warehousing. You will learn required warehousing skills, onboard to IWS, and develop AI-enabled tools to accelerate problem solving and data-driven decisions.

Responsibilities include designing digital processes, analyzing bottlenecks, validating processes (IQ/OQ/PQ), monitoring SPC, and collaborating across R&D, production, quality, and