Senior AI Architect & Production ML Lead

OP RaaS; Pittsburgh (Allegheny County); Hybrid; USD 180,000 - 240,000; Full time

Job summary

FedEx is seeking an AI Principal Lead to design and deploy scalable AI systems, including Neptune ontology and knowledge graphs, enabling unified network design across Surface and Air operations. You will own MLOps, CI/CD pipelines, observability, SLOs, and governance to ensure production-ready AI services at scale.

Collaborate with Data Scientists, Data Engineers, and Domain Architects to transition prototypes into reliable business-ready solutions.

Qualifications

• Master’s degree in CS, DS, or related field preferred.
• 5+ years architecting large-scale AI systems.
• Experience with production AI, ML Ops, and data pipelines.
• Proficiency with graph structures and ontologies.

Responsibilities

• Hands-On Model & Graph Development: write production-quality code to engineer scalable AI systems, graphs, and data pipelines.
• Domain-Driven AI Architecture: develop intelligent, LLM-driven AI Agents and algorithms for enterprise demand patterns and transportation networks.
• MLOps & Enterprise Reliability: design and maintain scalable ML pipelines, collaborate with MLOps teams on CI/CD and live deployment.
• Mission-Critical Governance: establish SLOs for latency; implement observability, data drift monitoring, and rollback strategies.
• Cross-Functional Engineering: collaborate with Data Scientists, Data Engineers, and Domain Architects to productionize models.

Skills

Hands-on AI engineering

Knowledge graphs

MLOps & CI/CD

Data pipelines

LLM-driven AI Agents

Docker & Kubernetes

Enterprise reliability

Domain logistics knowledge

Education

Master’s degree in CS/DS/Engineering

Tools

Docker

Kubernetes

CI/CD tooling

Job description

FedEx is seeking an AI Principal Lead to design and deploy scalable AI systems, including Neptune ontology and knowledge graphs, enabling unified network design across Surface and Air operations. You will own MLOps, CI/CD pipelines, observability, SLOs, and governance to ensure production-ready AI services at scale.

Collaborate with Data Scientists, Data Engineers, and Domain Architects to transition prototypes into reliable business-ready solutions.