AI Engineer – Routing & Network Optimization

Gallatin•Austin, TX

1d•$80,000 - $210,000

About The Position

We’re hiring 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 turns 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 make sure routing decisions are correct, scalable, and resilient under real-world operational volatility.

Requirements

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.
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.
Ability to reason about scale, uncertainty, and time-dependent systems.
Comfort owning routing logic and data end-to-end.
A strong focus on performance, correctness, and reliability 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 with data operationalization and production analytics.

Responsibilities

Design and implement routing models across transportation, warehousing, and resupply networks.
Encode constraints related to: Distance and time, Availability, readiness, and risk, Asset and lane capacity.
Support multi-hop, event-aware, and time-phased routing across dynamic networks.
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.
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.
Integrate routing systems into batch and real-time 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.