Open Source Design Engineer, Arize AI
$145-185k
Plus a competitive equity package
Machine learning observability platform
Be an early applicant
Machine learning observability platform
21-100 employees
Be an early applicant
$145-185k
Plus a competitive equity package
21-100 employees
Company mission
To make the world’s AI work and work for the people.
Role
Who you are
- Have strong frontend engineering skills (React, TypeScript) paired with design sensibility
- Think deeply about interaction design, information architecture, and developer experience
- Are curious about AI systems and eager to learn how agents, evaluations, and observability work
- Enjoy prototyping quickly and iterating toward polish
- Care about accessibility, performance, and craft
- Thrive in open-source communities and async collaboration
What the job involves
- We're looking for a Design Engineer to build ambitious interfaces at the frontier of AI development, evaluation, and observability
- You'll design, prototype, and ship experiences that help AI teams understand, troubleshoot, and improve the systems powering their next-generation applications
- Here's what makes this role different: Modern AI work is no longer purely human-driven. Arize Phoenix is a platform used by AI teams and AI agents such as Claude Code
- You won't just craft great UX. You'll pioneer great AX (Agent Experience)—product surfaces that are delightful for people and interoperable, safe, and legible for agents
- Design and build compelling product experiences for Arize Phoenix across UI-driven and programmatic workflows
- Create interactive visualizations for embeddings, traces, evaluation runs, and agent/tool workflows
- Develop reusable components and templates for our design system, from concept to production
- Build Agent Experience primitives: interaction contracts, human-in-the-loop workflows, and agent-friendly UI surfaces
- Enable agents to query, navigate, trigger evaluations
- Shape the patterns that define how humans and AI agents collaborate within a shared workspace
- Prototype new AI features and UI patterns for visualizing performance, surfacing anomalies, and explaining AI behavior—especially for multi-step agent systems
- Use AI-assisted UI generation to accelerate prototyping while maintaining craft, accessibility, and consistency
- Push the boundaries of what's possible when your users include both humans and machines
Our take
Machine learning is rapidly becoming a fundamental and mainstream automation tool used across many industries. The issue, however, is that monitoring, assessing, and improving ML models is costly, and especially tricky without monitoring capabilities. It’s created a market demand for ML monitoring tools, and Arize’s platform offers a rich suite of them.
The Arize platform gives developers and operators comprehensive oversight of their models with tools including performance tracing, drift detection, and integration and deployment. This provides a crucial guardrail: as more decision-making is handed over to ML in areas like insurance and loans, poor ML model performance can have a catastrophic effect on both individuals and customers alike.
Remarkably, given this development, ML observability platforms aren’t yet in huge supply. Arize startup rivals like Censius and WhyLabs are making strong headway, but a clear winner has by no means yet emerged. Arize has, however, netted some major customers: Spotify, Instacart, Uber, and P&G are a handful of the major clients that will help it lay a strong foundation in what is anticipated to be a highly lucrative market.
Kirsty
Company Specialist at Welcome to the Jungle
Meet the team
Meet Andy, Product Design Team Lead
Our mission
Collaborate to create functional and innovative design solutions.Insights
23% employee growth in 12 months
Company
Funding (last 2 of 3 rounds)
Sep 2022
$38m
SERIES B
Sep 2021
$19m
SERIES A
Total funding: $61m
Company benefits
- Remote work
- Open PTO policy
- Health, dental, vision insurance
- 401K
- Company wellness days
- Coworking
Company values
- Do > Say - We believe in building, not just talking. Execution matters more than meetings, and progress beats process. Instead of endless debate, we prototype. Instead of bureaucracy, we ship. AI moves fast—so do we.
- N+1 - Good enough isn’t good enough. We believe in continuous improvement—whether it’s improving AI-powered systems, our product, or ourselves, there’s always a better version to build, iterate, and level up.
- Bring Solutions - Spot a problem? Own it. We don’t waste time on complaints or excuses—we focus on fixing, improving, and building. Whether it’s a blocker in a project or a gap in how we work, the expectation is simple: push for a better way forward.
Company HQ
New York, NY 10006
Articles
Leadership
Jason Lopatecki
(Co-Founder & CEO)Previously a System Architect at Calix, before they moved on to found and serve as CSO/CIO at TubeMogul for over a decade.
Aparna Dhinakaran
(Co-Founder & CPO)Has held Software Engineer roles at both Dote and Apple, and worked on Machine Learning at TubeMogul and Uber. Also co-founded and served as CEO at Monitor ML, and is additionally a columnist at Forbes.
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