Senior AI Tools Engineer

Role Description

We are seeking a passionate AI Tools Engineer to join the Site Reliability Engineering (SRE) Data Team. We encourage applicants with SRE or equivalent experience.

You will build and deploy sophisticated AI-powered tools and products. These tools support the operation and optimization of a critical production global GeForce Now service. This role is critical for transforming extensive production data streams—such as signals, metrics, and logs—into actionable intelligence. The intelligence automates root cause analysis for incidents and predicts future service trends and patterns.

• Build and implement robust AI/ML tools capable of analyzing production data to identify root causes for complex incidents and identify future operational trends.
• Lead the development of brand-new LLM- and Agent-based systems to improve operational efficiency.
• Establish and maintain excellent data management practices, including constructing workflows to convert and handle large-scale data sources vital for model development.
• Take charge of and enhance LLM-based pipelines while integrating a strong grasp of LLM progress into product development.
• Act as a resident authority on AI Frameworks, recommending the best platforms, toolsets, and architectural approaches to ensure the long-term technical sustainability of the product.

Qualifications

• B.S. in Computer Science, Statistics, or Engineering (or equivalent experience), and 5+ years of experience.
• Strong proficiency in Python; familiarity with Go or other systems languages is a plus.
• Practical experience building, optimizing, and deploying AI tools.
• Strong knowledge of the AI space and current developments, including understanding how LLM-based platforms are built, optimized, and which platforms work best.
• Hands-on experience with container orchestration (Kubernetes) and cloud environments (AWS cloud).
• Active engagement with developments in the AI field and the ability to distinguish meaningful advances from noise when making technical decisions.
• Expertise in automation and handling large-scale data pipelines.
• Experience applying monitoring and visualization tools, such as Grafana, to interact with data.
• Excellent ability to handle data sources and pipelines to transform and manage data.

Requirements

• Current experience in LLM improvement pipelines as well as a strong grasp of recent developments in LLM training.
• Understanding of SRE concepts and experience managing production environments, as well as experience with Kubernetes, AWS, and other cloud technologies.
• Someone with excellent knowledge of LLMs and AI Models who can reason and recommend an approach that sustains the team and product long-term.
• Proficiency in automation.

Benefits

• Competitive salary package.
• Equity eligibility.
• Comprehensive benefits.