Arize AI provides an ML observability platform that monitors, explains, and troubleshoots production models, offering embeddings inspection, bias tracing, drift detection, real-time analytics, and human/multi-model review.
<div class="content-intro"><h3>About Arize</h3> <p>AI is rapidly transforming the world. As generative AI reshapes industries, teams need powerful ways to monitor, troubleshoot, and optimize their AI systems. That’s where we come in. <strong data-stringify-type="bold">Arize AI is the leading AI & Agent Engineering observability and evaluation platform</strong>, empowering AI engineers to ship high-performing, reliable agents and applications. From first prototype to production scale, Arize AX unifies build, test, and run in a single workspace—so teams can ship faster with confidence.</p> <p>We’re a <strong data-stringify-type="bold">Series C</strong> company backed by top-tier investors,<strong data-stringify-type="bold"> </strong>with<strong data-stringify-type="bold"> over $135M in funding</strong> and a rapidly growing customer base of <strong data-stringify-type="bold">150+ leading enterprises and Fortune 500 companies. </strong>Customers like <a class="c-link" href="http://booking.com/" target="_blank" data-stringify-link="http://Booking.com" data-sk="tooltip_parent">Booking.com</a>, Uber, Siemens, and PepsiCo leverage Arize to deliver AI that works.</p></div><h4><strong>The Opportunity</strong></h4> <p>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.</p> <p>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.</p> <p><strong>The Team</strong></p> <p>Our Fullstack Engineering team builds both the highly scalable distributed services that power Arize's ML observability platform and the intuitive frontend applications that bring these capabilities to life. The team primarily works in TypeScript and Python to create seamless data visualization and monitoring experiences, with some services written in Go. We focus on delivering robust features that help clients interpret, visualize, and monitor their AI and ML models across the entire stack.</p> <p>You will be a part of the core team that drives product innovation at Arize. You will be challenged with understanding how some of the most impactful engineering teams are developing AI and LLM-powered applications, and how to build the right tools to enable them to do their best work. Our product solutions range from clean APIs that <a href="https://docs.arize.com/phoenix/tracing/how-to-tracing/instrumentation">magically instrument</a> applications,<a href="https://docs.arize.com/arize/llm-playground/prompt-playground"> interactive playgrounds</a> for prompt engineering and agent development, or scaling up <a href="https://docs.arize.com/arize/llm-evaluation-and-annotations/catching-hallucinations/tasks-for-online-evals">real-time evaluation infrastructure</a> to handle millions of annotations per second</p> <p><strong>What You’ll Do</strong></p> <ul> <li>Write maintainable, scalable, and performant code across the stack primarily in Typescript and React with opportunities to work in Python and Go.</li> <li>Design and build APIs, and domain / object models specific to our customers’ Machine Learning and LLM workflows.</li> <li>Design and build out performant and reusable react components that will be used throughout the application.</li> <li>Research and implement cutting-edge visualization & dimensionality reduction algorithms in a distributed environment.</li> <li>Collaborate with our product, design, and directly with customer engineering teams to enhance and expand our product offerings.</li> <li>Contribute to the build our own in-house AI Agents</li> <li>Participate in or lead architectural decisions for new and existing features in collaboration with product, design and our backend teams. </li> <li>Contribute to design & code reviews and technical documentation.</li> </ul> <p><strong>What We’re Looking For</strong></p> <ul> <li>5+ years of frontend experience working on external user-facing UI’s - preferably in React and Typescript</li> <li>Previous experience debugging complex systems in a team environment.</li> <li>Enthusiasm and interest in the AI and LLM ecosystem, with a desire to learn and stay updated on emerging technologies.</li> <li>Previous work building and operating highly complex, high-volume SaaS platforms/systems.</li> <li>Strong sense of product ownership in order to push features over the line.</li> <li>Passion for creating beautiful UX design with the end user in mind.</li> <li>A good teammate, someone who sees supporting their team as a core part of the job</li> </ul> <p><strong>Bonus Points, But Not Required</strong></p> <ul> <li>Experience working with GraphQl or a comparable API technology.</li> <li>Experience working with ML, analytics, data science or data visualization products.</li> <li>Working knowledge of Machine Learning and/or Data Science.</li> <li>First-hand experience working with large language models (LLMs) or developing AI products.</li> </ul> <p>The estimated annual salary for this role is between $125,000 - $225,000, plus a competitive equity package. Actual compensation is determined based on a variety of job-related factors that may include transferable work experience, skill sets, and qualifications. Total compensation also includes a comprehensive benefits package, including medical, dental, vision, a 401(k) plan, unlimited paid time off, a generous parental leave plan, and additional support for mental health and wellness.</p> <p>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