AI Engineer – Decision & Optimization Systems
ABOUT GALLATIN
At Gallatin, we are rebuilding logistics infrastructure for the national security missions of the United States and allied partners. We build AI systems that determine how logistics decisions are made — not just how they're executed. From factory to foxhole, we operate at the layer where data becomes decisions, and decisions make the advantage.
ABOUT THE ROLE
We’re looking for an AI Engineer – Decision & Optimization Systems to own the feasibility, authority, and constraint layers that sit between AI reasoning and real-world execution.
In this role, you will build the systems that decide what plans are allowed to exist before any optimizer, agent, or human can act on them. Your work ensures that AI-generated logistics plans respect command hierarchy, policy, safety, and operational reality—so when we execute, we execute correctly.
You will work closely with routing, packing, optimization, and AI-agent teams to translate intent, authority, and uncertainty into auditable, enforceable, and explainable decision systems.
WHAT YOU’LL DO
BUILD & OWN FEASIBILITY AND AUTHORITY MODELS
- Design and implement models that encode command hierarchy, authority limits, and policy rules into formal feasibility checks.
- Convert AI-agent outputs (LLMs, planners, probabilistic models) into deterministic, enforceable constraints before execution.
- Ensure that authority and policy interpretations are traceable, inspectable, and safe.
CONSTRAINT & FEASIBILITY FRAMEWORKS
- Build and maintain a centralized constraint framework used across optimization and planning systems.
- Encode:
- Authority rules
- Compatibility constraints
- Timing windows
- Asset availability and readiness
- Surface clear diagnostics for infeasible plans and constraint violations so humans and machines can understand what failed and why.
DATA OWNERSHIP & VALIDATION
- Own the data inputs required for feasibility and constraint enforcement.
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