IT Manager, Data Platform Engineering
BrightseedFull Time
Senior (5 to 8 years)
Candidates should possess a strong background in performance optimization, particularly around low-latency storage and retrieval systems, and a track record of leading engineering teams working on distributed infrastructure while maintaining technical depth. Experience with modern infrastructure (Kubernetes, cloud-native architectures) and distributed systems patterns is essential, along with a focus on pragmatic solutions while meeting strict performance and reliability requirements.
As the Engineering Manager, you will lead and scale a team of engineers building the next-generation event processing and storage infrastructure, driving architectural decisions for mission-critical distributed systems, focusing on reliability, performance, and scalability. You will also design and implement sophisticated storage and query engines optimized for AI observability workloads, partner with product teams to evolve the platform, and mentor and grow engineering talent while fostering a culture of distributed systems excellence.
AI observability and model evaluation platform
Arize AI provides a platform focused on AI observability and evaluating language models. The platform allows companies to monitor, troubleshoot, and assess the performance of various machine learning models, including those used for natural language processing, computer vision, and recommendations. Users can access analytics and workflows that help identify and resolve issues within their AI systems, ensuring optimal performance. Key features include task-based evaluations for aspects like hallucination and relevance, as well as tools for visualizing query and knowledge base embeddings to enhance retrieval accuracy. Unlike many competitors, Arize AI specifically targets the needs of top AI companies, offering tailored solutions for continuous improvement of their models. The goal of Arize AI is to empower these companies to enhance their AI capabilities through effective monitoring and evaluation.