AI Engineer – Decision & Optimization Systems
About The Position
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.
Requirements
- Strong Engineering & Modeling Skills
- 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.
- Optimization & Decision Science Background
- 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.
- Systems Thinking
- 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.
Nice To Haves
- 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.
Responsibilities
- 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.
- 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 all actions on valid, policy-compliant inputs.
- Validate system behavior using scenario testing, simulations, and operational feedback from real users.
Benefits
- Competitive compensation including generous equity, 100% employer-paid health insurance, 401(k), unlimited PTO, and catered meals.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
11-50 employees
