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Gallatin is rebuilding logistics infrastructure for U.S. national security missions. This role focuses on building AI systems that determine how logistics decisions are made—operating at the layer where data becomes decisions.
You will own the feasibility, authority, and constraint layers that sit between AI reasoning and real-world execution. Your core responsibility is building systems that decide what plans are allowed to exist before any optimizer, agent, or human can act on them. This ensures AI-generated logistics plans respect command hierarchy, policy, safety, and operational reality.
Key responsibilities include:
**Feasibility & Authority Models**: Design and implement models that encode command hierarchy, authority limits, and policy rules into formal feasibility checks. Convert outputs from AI agents (LLMs, planners, probabilistic models) into deterministic, enforceable constraints before execution. Ensure authority and policy interpretations are traceable, inspectable, and safe.
**Constraint & Feasibility Frameworks**: Build and maintain a centralized constraint framework used across planning and optimization systems. Encode authority rules, timing windows, compatibility constraints, and asset availability/readiness. Surface clear diagnostics for infeasible plans and constraint violations so both humans and machines understand what failed and why.
**Data Ownership & Validation**: Own the data inputs needed for feasibility and constraint enforcement. Define and enforce data contracts, normalization, and validation pipelines. Build robustness against incomplete, delayed, or noisy operational data.
**Production Integration**: Integrate feasibility checks into real-time and batch planning pipelines. Partner with optimization and execution teams to gate every action on valid, policy-compliant inputs. Validate system behavior through scenario testing, simulations, and operational feedback from real users.
You'll partner closely with routing, packing, optimization, and AI-agent teams to turn intent, authority, and uncertainty into decision systems that are auditable, enforceable, and explainable.
Gallatin is a mission-driven team of seasoned entrepreneurs, operators, and technologists. The company values clear thinking, direct communication, and ownership that doesn't stop until something works. The mission is to create decision advantage in the highest-stakes environments.
**Requirements:**
- Proficiency in at least one of: Python, Java, Go, or C++
- Experience building constraint-based or rule-based systems in production
- Experience integrating AI or agent-based reasoning into downstream decision or execution pipelines
- Degree or equivalent experience in Operations Research, Applied Math, Industrial Engineering, Computer Science, or related field
- Strong understanding of: Linear programming, Mixed-integer programming, Constraint satisfaction systems
- Experience using tools such as Gurobi, CPLEX, OR-Tools, Pyomo, AMPL, or equivalent
- Ability to reason about feasibility vs optimality tradeoffs
- Comfort integrating probabilistic or AI-derived outputs into deterministic systems
- Strong instincts for debugging, failure analysis, and explainability in high-stakes environments
**Bonus qualifications:**
- Experience with logistics, supply chain, or routing systems
- Experience working alongside optimization or planning teams
- Exposure to defense, government, or mission-critical operations
- Prior work integrating AI agents into decision or execution pipelines
**Important notes:** U.S. citizenship is required. This position may require the ability to obtain and maintain a U.S. government security clearance and work in classified environments.
