Senior Agentic AI Engineer - Supply Chain Ops

NVIDIA Corporation; United States; On-site; USD 224,000 - 357,000; Full time

Job summary

NVIDIA Corporation is seeking a Senior AI Engineer in Operations to define and implement agentic AI for Supply Chain. You will shape decision intelligence, build scalable agentic AI systems, and work across IT, product, and research teams using NVIDIA technologies.

You will own architecture, ensure secure deployments, monitor observability, and optimize performance across on-prem, cloud, and hybrid environments.

Qualifications

• Bachelor's degree in CS or related field with 12+ years in software architecture or enterprise engineering.
• Strong production Python experience and backend service development (SQL/JSON; Java a plus).
• Experience with Palantir AI Foundry, AIP Forward Deployment a must (2+ years).
• Proficiency in AI/ML, LLMs, RAG, and agent orchestration frameworks.
• Familiarity with LangChain, AutoGPT-style workflows and vector databases.

Responsibilities

• Develop and own enterprise-grade Agentic AI systems for SC use cases and multi-agent architectures.
• Lead end-to-end design, testing, data setup, and issue remediation during UAT; guide development team activities.
• Hands-on development of agentic AI solutions; ensure secure, scalable deployment.
• Collaborate with IT, product, and research teams; leverage NeMo and AIQ technologies.
• Define deployment models (on-prem, cloud, hybrid, containerized) and drive architecture decisions.

Skills

Python

SQL

JSON

Java

LLMs

RAG architectures

Agent orchestration

Education

Bachelor's degree in Computer Science or related field

Tools

LangChain

AutoGPT

Vector databases

Embeddings

Retrieval optimization

Kubernetes

Job description

NVIDIA Corporation is seeking a Senior AI Engineer in Operations to define and implement agentic AI for Supply Chain. You will shape decision intelligence, build scalable agentic AI systems, and work across IT, product, and research teams using NVIDIA technologies.

You will own architecture, ensure secure deployments, monitor observability, and optimize performance across on-prem, cloud, and hybrid environments.