Senior Applied AI Engineer

Job Title

Senior Applied AI Engineer

Role Summary

Work within the ASIC networking product engineering group to design, deliver, and operate end-to-end AI solutions that unify engineering data and enable analytics, AI agents, copilots, and workflow automation to improve engineering productivity.

Own architecture, development, deployment, and maintenance of production AI systems and partner with engineering teams to deliver measurable impact.

Experience Level

Senior — requires 5+ years of experience building production AI or data solutions.

Responsibilities

Primary responsibilities include building production AI/data capabilities, consolidating engineering data, and partnering with product teams.

• Design, build, and maintain AI solutions for production, characterization, analysis, and operational workflows.
• Develop agentic analytics and copilots to enable querying, analysis, and reasoning over ASIC data.
• Consolidate data from multiple infrastructure and engineering systems into scalable, reliable pipelines and services.
• Partner with production engineering teams to identify use cases and deliver measurable outcomes.
• Build tools for data access, automation, reporting, anomaly detection, and insight generation.
• Collaborate across teams to improve data quality and support scalable deployment models.
• Monitor, gather user feedback, and drive continuous improvement and roadmap planning.

Requirements

Core technical and professional requirements and preferred qualifications.

• Must-have: 5+ years experience as an AI solutions engineer, machine learning engineer, or software engineer delivering production AI/data solutions.
• Must-have: Strong experience designing, deploying, and maintaining end-to-end AI applications in production.
• Must-have: Hands-on expertise with Python and modern software engineering practices.
• Must-have: Practical experience with large language models, AI agents, retrieval-augmented generation (RAG), and workflow orchestration.
• Must-have: Experience building data pipelines, APIs, services, and applications working with structured and semi-structured engineering data.
• Must-have: Strong communication skills and an ownership-driven mindset.
• Nice-to-have: Experience in semiconductor, hardware, product engineering, test, characterization, or manufacturing analytics.
• Nice-to-have: Familiarity with agent frameworks, vector databases, telemetry platforms, or internal knowledge/data systems.
• Nice-to-have: Cross-functional experience across software, data, infrastructure, and product engineering; proven track record of driving adoption.

Education Requirements

Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field, or equivalent practical experience.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.