The Opportunity
AI is rapidly transforming the world. Whether it’s developing the next generation of human-level intelligence, enhancing voice assistants, or enabling researchers to analyze genetic markers at scale, AI is increasingly integrated into various aspects of our daily lives.
Arize AI is the leading AI observability and evaluation platform, empowering AI engineers to build and deploy high-performing, reliable models. As the AI landscape shifts from traditional ML to generative AI and agentic systems, Arize ensures teams have the tools to monitor, troubleshoot, and improve AI in production.
The Team
Our On-Prem engineering team is responsible for the deployment of Arize in customer environments. In addition to working with customers in defining infrastructure requirements, the team designs and develops software and tooling that enables the management of these systems at large scale. The On-Prem team has grown to be expert in Kubernetes and cloud deployment on GCP, Azure, and AWS as well as dealing with networking and security aspects of on-premise deployments. The team is dynamic and relies on few talented individuals with a high degree of autonomy and initiative.
What You’ll Do
- Work hands-on with the infrastructure that supports our distributed & highly scalable services in both SaaS and on-prem offerings
- Gather requirements from customers and adapt manifests and software to support new environments
- Use and augment monitoring tools to observe platform health, ensure performance and reliability
- Interact with the product team to test new features and package new on-prem releases
- Automate and optimize the release pipeline to make it as frictionless as possible
- Exhibit continuous curiosity for emerging technology that could solve our challenges
- 3+ years of experience as a DevOps Engineer, Cloud Engineer, Infrastructure Engineer or similar
- Excellent communication skills and ability to work directly with customers to understand and address their infrastructure needs
- Experience and fluency in Kubernetes
- A self starter with an ability to thrived in a fast paced environment
- Experience working with multiple cloud providers (AWS, GCP, Azure) and understanding how to adapt cloud-native architectures for on-premises environments
- Strong troubleshooting skills
The estimated annual salary for this role is between $100,000 - $185,000, plus a competitive equity package. Actual compensation is determined based upon a variety of job related factors that may include: transferable work experience, skill sets, and qualifications. Total compensation also includes a comprehensive benefit package, including: medical, dental, vision, 401(k) plan, unlimited paid time off, generous parental leave plan, and others for mental and wellness support.
While we are a remote-first company, we have opened offices in New York City and the San Francisco Bay Area, as an option for those in those cities who wish to work in-person. For all other employees, there is a WFH monthly stipend to pay for co-working spaces.
More About Arize
Arize’s mission is to make the world’s AI work and work for the people. Our founders came together through a common frustration: investments in AI are growing rapidly across businesses and organizations of all types, yet it is incredibly difficult to understand why a machine learning model behaves the way it does after it is deployed into the real world.
Learn more about Arize in an interview with our founders: https://www.forbes.com/sites/frederickdaso/2020/09/01/arize-ai-helps-us-understand-how-ai-works/#322488d7753c
Diversity & Inclusion @ Arize
Our company's mission is to make AI work and make AI work for the people, we hope to make an impact in bias industry-wide and that's a big motivator for people who work here. We actively hope that individuals contribute to a good culture
- Regularly have chats with industry experts, researchers, and ethicists across the ecosystem to advance the use of responsible AI
- Culturally conscious events such as LGBTQ trivia during pride month
- We have an active Lady Arizers subgroup
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What We Do
The leading machine learning observability platform for ML practitioners to detect and troubleshoot AI/ML model issues
