Senior AI Tools Engineer

Role Description

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

• Build and deploy sophisticated AI-powered tools and products to support the operation and optimization of a critical production global Geforce Now service.
• Transform extensive production data streams—such as signals, metrics, and logs—into actionable intelligence for automating root cause analysis and predicting future service trends.
• Build and implement robust AI/ML tools capable of analyzing production data to identify root causes for complex incidents and 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 building pipelines to transform and handle large-scale data sources vital for model development.
• 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 for long-term technical sustainability.

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 and optimized.
• 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.
• 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

• Understanding of SRE principles and experience managing production environments.
• Strong in LLM improvement pipelines and recent developments in LLM training.
• Excellent knowledge of LLMs and AI Models with the ability to recommend sustainable approaches.
• Understanding of SRE concepts and managing production environments with experience in Kubernetes, AWS, and other cloud technologies.
• Proficiency in automation.

Benefits

• Competitive salary package with a base salary range of 144,000 USD - 230,000 USD, determined by location and experience.
• Eligibility for equity and benefits.