Senior AI Engineer - Multi-Agent Systems & MLOps

FedEx; Memphis (TN); Hybrid; USD 117,000 - 166,000; Full time

Job summary

FedEx in Plano, TX, Memphis, TN, or Pittsburgh, PA, is seeking an AI Engineer to design, develop, deploy, and maintain AI/ML solutions across the enterprise. This hands-on role builds AI agents, data pipelines, and production-grade systems to enable intelligent automation and analytics.

You will collaborate with Data Scientists, Data Engineers, ML Ops, and Platform teams to bring models from prototype to production while ensuring observability, SLOs, and reliable incident response strategies for

Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, or related field is required.
• Minimum 3–5+ years of dedicated experience designing and shipping ML models to production.
• Experience with Google Cloud Platform and Vertex AI is required.

Responsibilities

• Architect, develop, and maintain multi-agent systems, deterministic workflow agents, and autonomous tool-calling pipelines.
• Deploy and operationalize ADK agents to Vertex AI Agent Engine, Cloud Run, and GKE with CI/CD practices.
• Establish observability, SLOs, and incident response/rollback strategies for AI services.
• Collaborate with Data Scientists, Data Engineers, ML Ops, and Platform teams to move models from prototype to production.
• Design high-performance data pipelines and integrate structured enterprise data stores as agent tool datastores.

Skills

Python mastery

ADK (Python)

Vertex AI

LLM tooling

GCP stack

CI/CD

Education

Bachelor's degree in CS/Engineering

Tools

Docker

Kubernetes (GKE)

BigQuery

FastAPI

Job description

FedEx in Plano, TX, Memphis, TN, or Pittsburgh, PA, is seeking an AI Engineer to design, develop, deploy, and maintain AI/ML solutions across the enterprise. This hands-on role builds AI agents, data pipelines, and production-grade systems to enable intelligent automation and analytics.

You will collaborate with Data Scientists, Data Engineers, ML Ops, and Platform teams to bring models from prototype to production while ensuring observability, SLOs, and reliable incident response strategies for