Senior AI Engineer, AI tools
$224k - $357k • Remote • US, CA, Santa Clara
Posted 10d ago
About the job
NVIDIA is seeking a Senior AI Engineer to evaluate and integrate emerging AI tools, agent harnesses, and models into NVIDIA's engineering workflows. This role involves identifying opportunities for AI-first solutions, designing and implementing reference workflows for coding and testing, and optimizing performance and cost. The engineer will collaborate with AI product vendors to gain industry insights, influence product roadmaps, and introduce new capabilities into NVIDIA's AI ecosystem. This position requires providing guidance on AI tool and model selection, recommended configurations, and hands-on training to internal teams.
Responsibilities
- Evaluate AI tools, agent harnesses, and models for task success, output quality, reliability, latency, cost, and enterprise readiness.
- Identify opportunities for AI-first approaches and recommend them over conventional solutions.
- Design, implement, and validate reference workflows for coding, testing, code review, and troubleshooting.
- Introduce technologies to improve turnaround time in massively parallel systems.
- Optimize performance and cost by identifying bottlenecks in training, evaluation, and testing workflows.
- Collaborate with AI product vendors to understand the AI industry and share insights internally.
- Evaluate new capabilities from tool vendors, influence product roadmaps, and resolve adoption issues.
- Provide guidance on AI tool and model selection, configurations, and onboarding materials.
- Deliver hands-on training on AI tools and workflows.
Requirements
- MS in EE/CS or equivalent experience with 12+ years of work experience.
- Strong understanding of LLMs, machine learning, and agentic AI, including the impact of models, agent harnesses, context, and tool use.
- Hands-on experience evaluating AI tools/models and applying LLMs to software engineering workflows.
- Skills in experiment design, benchmark development, reproducibility, and failure analysis.
- Strong software engineering skills in Python, with experience in Java or Go and extensive scripting/automation.
- Experience building evaluation pipelines, developer tooling, or full-stack applications with API integration, data management, and cloud/enterprise deployment.
- Experience with CI/CD tools like Jenkins, Gitlab CI, Packer, Terraform, Artifactory, Ansible, or Chef.
- Good understanding of distributed systems, microservice architecture, and REST APIs.
- Familiarity with software development, testing, code review, and build workflows.
- Ability to translate evaluation results into clear technical recommendations and practical user guidance.
- Ability to work effectively across organizational boundaries to enhance alignment and productivity.
Benefits
- Equity
- Benefits