Complexity Engineer

Groupe SEGULA Technologies SA; México; Remote; MXN 450,000 - 750,000; Full time

Job summary

Groupe SEGULA Technologies SA is seeking a data-driven Complexity Engineer to lead optimization and rationalization of product variety across our vehicle platforms. Your mission is to control build complexity, eliminate non-value variants, and protect customer-facing option choices.

You will collaborate across Product Engineering, Supply Chain, Purchasing, and Manufacturing, establish feature-tiering strategies, manage configuration rules in PLM/ERP, and travel to plants during prototypes and

Qualifications

• Variant & Combination Analysis: Analyze complete vehicle option matrices, feature offerings, and build combinations using data modeling to identify, quantify, and eliminate low-volume or high-friction variants.
• Component Rationalization: Partner with Design Release Engineers across electrical, mechanical, and interior/exterior attributes to consolidate part numbers, maximize carry-over parts (COP), and drive modular architecture strategies.
• Cost of Complexity Modeling: Develop financial and operational cost models that evaluate the downstream impacts of adding new features or part variants (tooling cost, inventory holding, assembly line time, supply chain risk).
• Configuration & Rule Management: Define, release, and maintain variant configuration rules within PLM and ERP systems to prevent non-buildable or redundant feature combinations.
• Cross-Functional Strategy: Lead alignment workshops with Product Planning, Marketing, Purchasing, and Manufacturing teams to establish clear variance targets for new vehicle programs and running changes.
• Plant & Launch Support: Travel to manufacturing plants during prototype builds and launch phases to review physical build variance on the assembly line, assess station complexity, and identify opportunities for station balancing or part standardization.

Job description

Complexity Engineer

Location: Remote

Job Type: Full-Time

Experience Level: Mid-Level (3+ Years)

Travel Required: 15%–25% (Travel to manufacturing facilities, assembly plants, and regional supply chain hubs as needed)

About the Role

We are seeking a data-driven and analytical Complexity Engineer to lead the optimization, rationalization, and management of product variety across our vehicle platforms.

In this role, you will sit at the intersection of Product Engineering, Supply Chain, Purchasing, and Manufacturing. Your main mission is to control and reduce build-combination complexity, eliminate non-value-added component variants, and minimize manufacturing friction—all while protecting customer-facing option choices. You will establish feature-tiering strategies, manage configuration rules, and quantify the total cost of complexity across the product lifecycle.

Key Responsibilities

• Variant & Combination Analysis: Analyze complete vehicle option matrices, feature offerings, and build combinations using data modeling to identify, quantify, and eliminate low-volume or high-friction variants.

• Component Rationalization: Partner with Design Release Engineers (DREs) across electrical, mechanical, and interior/exterior attributes to consolidate part numbers, maximize carry-over parts (COP), and drive modular architecture strategies.

• Cost of Complexity Modeling: Develop financial and operational cost models that evaluate the downstream impacts of adding new features or part variants (tooling cost, inventory holding, assembly line time, supply chain risk).

• Configuration & Rule Management: Define, release, and maintain variant configuration rules within PLM and ERP systems to prevent non-buildable or redundant feature combinations.

• Cross-Functional Strategy: Lead alignment workshops with Product Planning, Marketing, Purchasing, and Manufacturing teams to establish clear variance targets for new vehicle programs and running changes.

• Plant & Launch Support: Travel to manufacturing plants during prototype builds and launch phases to review physical build variance on the assembly line, assess station complexity, and identify opportunities for station balancing or part standardization.