Lead Software Engineer

Everything’s on the menu ept compromise.

Wonder is the mealtime platform built to feed every craving in one order. With Wonder, you can mix and match hundreds of dishes from 20+ exclusive restaurants in a single order, so everyone gets exactly what they’re craving. Enjoy everything from tacos to Thai with $0 delivery fees, plus dine-in or pick up at a Wonder location near you. Each dish is made to order on-site by our culinary team and served hot.

Behind the scenes, Wonder owns and operates every step of the dining experience, from recipe development to the technology that powers our experience, allowing us to deliver quality, variety, and consistency at scale.

Join us as we work to make great food more accessible.

We’re looking for a Staff Engineer to join our team in building the 'brain' of Wonder’s supply chain system. You will work closely with Senior Software Engineers to develop the logic that translates sales forecasts into automated ordering plans for our distribution centers, fulfillment centers, production facilities and vendor orders. Our team works with stakeholders from all over the company to solve complicated problems with cutting‑edge technology.

This role is perfect for someone who loves the intersection of clean, production‑ready code and complex mathematical modeling. You will help us simulate real‑world constraints such as lead times and procurement strategies to ensure our high‑density restaurants are always stocked and ready to serve.

• Develop & Implement:
  Write production‑level code to deploy operation research models and algorithms that drive cross network fulfillment.
• Simulation Modeling:
  Build and maintain simulation frameworks to stress‑test procurement strategies against real‑world uncertainty
• System Configuration:
  Manage the technical logic for complex configurations including multi‑location availability, on‑order tracking, and delivery schedules.
• Collaborate on Architecture:
  Work under the guidance of Senior Software Engineers to ensure all models are performant, scalable, and integrated into the core platform.
• Data Translation:
  Partner with Product and Analytics to define data requirements, ensuring our models use the most accurate and "clean" signals from the supply chain.
• Iterative Development:
  Follow a 'simple first' approach, delivering practical code that balances mathematical complexity with system reliability.
• Engineered for Resilience:
  Design and implement highly available planning logic that maintains high uptime and data consistency, ensuring that DC and vendor ordering systems are mission‑critical and failure‑tolerant.
• Performance at Scale:
  Optimize algorithm execution and data retrieval patterns to ensure the planning engine remains performant as we scale the number of locations, configurations, and sales volume.

• 5–8+ years of relevant experience in software engineering or systems modeling
• MS or PhD in Computer Science, Operations Research, Industrial Engineering, Applied Math, or a related quantitative field
• Demonstrated ability to model complex physical supply chain problems and iteratively build production‑ready solutions
• Mastery of Java, Kotlin, Python, or other related languages and SQL is required. Professional experience with at least one statically‑typed, compiled language to ensure compatibility with high‑performance backend systems is preferred.
• Proven track record of deploying, scaling, and maintaining optimization or simulation solutions in a production environment with high uptime requirements
• Experience building discrete‑event or stochastic simulations to stress‑test supply chain logic against real‑world uncertainty
• Strong grasp of modern software development life cycles, including CI/CD, unit testing/integration testing, and version control (Git)
• Ability to work under the guidance of Senior Engineering and Product leadership to translate complex business KPIs (cost, fill rate, waste) into technical solutions
• Specific experience in e‑commerce, food tech, or retail distribution centers (understanding "picking" logic and "vendor lead times")

Wonder uses geographic‑specific salary…