AI Engineer – Routing & Network Optimization

Gallatin•El Segundo, CA

About The Position

About Gallatin At Gallatin, we are rebuilding defense logistics for the warfighters of the United States and allied forces. We take an AI-first approach to modernizing how materiel, fuel, and equipment move from factory to foxhole—so commanders and operators can make faster, better, and safer decisions under uncertainty. We believe that transformational systems are built shoulder-to-shoulder, not over Zoom, and we operate from our offices in El Segundo, California and Austin, Texas. About the Role We’re looking for an AI Engineer – Routing & Network Optimization to own how supplies, vehicles, and materiel move across Gallatin’s global distribution networks. In this role, you will build the systems that determine how things move through time-phased, capacity-constrained, and risk-aware networks at scale. Your work transforms AI-driven intent and operational demand into optimal, executable routes across thousands of assets and nodes. You will work closely with feasibility, packing, optimization, and AI-agent teams to ensure routing decisions are correct, scalable, and resilient under real-world operational volatility.

Requirements

Strong Engineering & Optimization Skills
Strong programming skills in Python or similar, with experience translating mathematical models into production-grade systems.
Experience integrating routing or optimization algorithms into live planning pipelines with monitoring, validation, and performance tuning.
Operations Research & Network Optimization Background
Degree or equivalent experience in Operations Research, Applied Math, Industrial Engineering, Computer Science, or related field.
Strong foundation in: Graph theory and network optimization Shortest-path algorithms (Dijkstra, A, Bellman-Ford) Network flow models (max flow, min cut, min-cost flow)
Experience with VRP, capacitated routing, or routing with time windows.
Experience with large-scale graphs, time-expanded networks, or multi-commodity flow models.
Hands-on experience with modeling languages and solvers such as Pyomo, GAMS, AMPL, CPLEX, or Gurobi.
Systems Thinking
Ability to reason about scale, uncertainty, and time-dependent systems.
Comfort owning routing logic and data end-to-end.
Strong performance, correctness, and reliability mindset in high-stakes environments.

Nice To Haves

Experience with vehicle routing or transportation systems.
Experience working alongside simulation or digital-twin teams.
Exposure to defense, government, or mission-critical logistics.
Experience with ML models, experimentation (A/B testing), or causal inference.
Experience in data operationalization and production analytics.

Responsibilities

Build & Own Routing and Network Models
Design and implement routing models across transportation, warehousing, and resupply networks.
Encode constraints related to: Distance and time Asset and lane capacity Availability, readiness, and risk
Support multi-hop, time-phased, and event-aware routing across dynamic networks.
Algorithm Engineering & Optimization
Implement and tune routing solvers using exact, heuristic, and hybrid algorithms.
Scale routing algorithms to large graphs, real-time updates, and uncertain inputs.
Evaluate tradeoffs between solution quality, runtime, and operational robustness.
Network Data Ownership
Own routing datasets including nodes, edges, costs, capacities, and constraints.
Validate and maintain network representations used by all routing and planning systems.
Handle data gaps, uncertainty, and changing network conditions without breaking execution.
Production Integration
Integrate routing systems into real-time and batch planning pipelines.
Partner with feasibility, simulation, and execution teams to validate route executability.
Support scenario testing, what-if analysis, and iterative optimization based on real operational feedback.