Cost & Value Engineer - AI-Driven Cost Optimization

Siemens; Peachtree Corners (GA); On-site; USD 91,000 - 157,000; Full time

Job summary

Siemens is seeking a Cost and Value Engineer for a role based at a Siemens Smart Infrastructure location in the United States. You will drive cost and value initiatives across engineering, procurement, and product teams to optimize design-to-cost decisions.

The position emphasizes data-driven decision making, bottom-up cost modeling, supplier collaboration, and the deployment of AI-based solutions to automate workflows and improve profitability.

Qualifications

• Bachelor’s degree in Engineering, Supply Chain, Business, or a related field.
• 7+ years of cost engineering, strategic procurement, or manufacturing experience.
• Data-driven decision making using analytics and digital costing tools.
• Willingness to travel up to 25% domestically and internationally.

Responsibilities

• Drive cost and value engineering initiatives to deliver measurable savings.
• Perform bottom-up cost modeling across systems and components.
• Lead cross-functional collaboration with R&D, procurement, manufacturing, and quality.
• Identify cost reduction opportunities aligned to product roadmaps.
• Facilitate cost optimization workshops, benchmarking, and supplier innovations.
• Develop CVE methods, tools, and AI-driven solutions to automate workflows.

Skills

Cost engineering

Strategic procurement

Supply chain

Data analytics / AI modeling

Digital costing tools

Cross-functional leadership

Travel up to 25%

Education

Bachelor's degree in Engineering, Supply Chain, Business or related field

Advanced degree (MBA / MS)

Tools

Teamcenter Product Cost Management

aPriori

Digital costing tools

Job description

Siemens is seeking a Cost and Value Engineer for a role based at a Siemens Smart Infrastructure location in the United States. You will drive cost and value initiatives across engineering, procurement, and product teams to optimize design-to-cost decisions.

The position emphasizes data-driven decision making, bottom-up cost modeling, supplier collaboration, and the deployment of AI-based solutions to automate workflows and improve profitability.