Lead DevOps Engineer
Access SystemsFull Time
Senior (5 to 8 years)
Candidates should have 3+ years of experience as a DevOps Engineer, Cloud Engineer, or Infrastructure Engineer, with fluency in Kubernetes. Experience with multiple cloud providers (AWS, GCP, Azure) and adapting cloud-native architectures for on-premises environments is required, along with strong troubleshooting skills and excellent communication abilities to work directly with customers.
The DevOps Engineer will work hands-on with infrastructure for distributed and scalable services, gathering customer requirements and adapting software for new environments. Responsibilities include using and augmenting monitoring tools, interacting with the product team for new feature testing and releases, and automating and optimizing the release pipeline. The role also involves demonstrating continuous curiosity for emerging technologies.
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.