Optimization Systems Engineer, Lead

Location: Remote

Department: Portfolio roles

Location Type: REMOTE

Employment Type: FULL_TIME

• Design how scheduling algorithms, constraint solvers, and optimization tools plug into our platform
• Own the interfaces, data contracts, and execution patterns that connect algorithmic intelligence to our product

• Take optimization approaches (MIP solvers, heuristics, constraint programming) and architect production-grade systems around them
• Own APIs, orchestration, state management, and rollback patterns

• Bring deep knowledge of how MRP runs work, where APS tools break down, and why planners abandon optimization outputs
• Translate that knowledge into every design decision

• Evaluate and select solvers, libraries, and frameworks
• Know the tradeoffs between commercial solvers (Gurobi, CPLEX) and open-source alternatives and recommend based on our constraints, not vendor marketing

• Architect the software layer that handles schedule generation, what-if analysis, constraint evaluation, and recommendation delivery
• Make it fast, observable, and trustworthy

• Work directly with our data science and data platform teams to define what data you need, in what shape, at what latency
• Translate fluently between the algorithmic world and the engineering world

• You've built optimization software and you've shipped it—not configured it, not managed the team that built it. You've written the code, debugged the edge cases, and dealt with the fallout when the solver returned garbage because the input data was wrong
• You've seen the inside of ERP/MRP/APS systems and have strong opinions about what's broken. You've felt the frustration of watching a planner ignore an optimization output because it didn't account for something obvious. You want to fix that
• You're a builder, not an operator. A blank repo and open architecture excites you more than maintaining an existing system
• You're an AI-native developer. You use tools like Cursor, think in terms of spec-driven development, and leverage AI to move faster without sacrificing quality—this is how we work
• You default to simplicity. You know the difference between elegant and over-engineered. When a heuristic solves 90% of the problem, you don't reach for a MIP solver

• Strong software engineering fundamentals—you can architect systems, not just write algorithms. API design, state management, testing strategies, deployment patterns are not foreign concepts
• Fluency in optimization paradigms: linear/mixed-integer programming, constraint programming, heuristics, metaheuristics—and knowing when to use what
• Experience with production scheduling, supply chain planning, or adjacent domains (transportation, logistics, energy). Manufacturing-specific experience is a plus but not required—the constraint-thinking transfers
• Comfortable working in Python; experience with C/C++ for performance-critical components is a strong plus
• Familiar with modern data infrastructure (Databricks, Delta Lake, or similar) at a level that makes you a good partner to the data team

• Risk: We reward our team and partners with meaningful equity.
• Technology: We build and launch scalable technology products from day one.
• Industry Focus: We stay deeply focused on the underlying fabric of mobility and logistics.