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# Senior Systems Engineer -- Agentic AI

- **Company:** NVIDIA Ltd.
- **Location:** Austin, TX, United States
- **Experience:** Expert
- **Salary:** $224,000.0
- **Contract:** Permanent contract
- **Skills:** AI Evaluation, Artificial Intelligence, Business Logic, Systems Engineering, C++ (Programming Language), Cloud Computing, Computer Programming, Computer Engineering, Extract Transform Load (ETL), Distributed Systems, Python (Programming Language), Software Architecture, Systems Development Life Cycle, Systems Architecture, Workflow Management Systems, Rust (Programming Language), Data Processing, Graphics Processing Unit (GPU), High Performance Computing, Large Language Models, Agentic-AI, Information Technology, Machine Learning Operations, Hardware Infrastructure, Golang
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-systems-engineer-agentic-ai-austin-tx--3a4ec9b2-7849-4149-aeae-4a1363fe431a

## About the Role

Systems Engineering, Artificial Intelligence (AI), Autonomous Driving Systems, GPU (Graphics Processing Unit), Systems Engineering, Software Architecture, Artificial Intelligence (AI), System Architecture, Production Systems, Scalable System Development, * BS, MS, or equivalent experience in Computer Science, Computer Engineering, AI, or a related field, with 12+ years of relevant industry experience.

 * Strong foundation in modern AI, including LLMs, multimodal models, inference, agentic AI, and evaluation.
 * Deep expertise in software architecture, distributed systems, and large-scale systems design.
 * Strong hands-on programming skills in Python, C++, Go, Rust, or similar languages, with a track record of building high-quality production software.
 * Background building large-scale systems involving distributed execution, data processing/ETL, workflow orchestration, HPC, cloud, or GPU infrastructure.
 * Ability to reason across the stack-from AI model behavior and application logic to runtime, compute, and infrastructure.
 * Proven ability to take ambiguous, complex technical problems from architecture through implementation and production.

Ways to Stand Out from the Crowd:

 * Knowledge of LLM/VLM inference, model serving, model routing, or inference optimization.
 * Background in AI evaluation, benchmarking, experimentation, or large-scale AI infrastructure.
 * Track record of building reusable platforms supporting heterogeneous AI workloads and compute environments.