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Senior AI Product Engineer, Fullstack

💼 Full-time🗓 2026-06-25

Core

Building scalable distributed services and intuitive frontend applications for an AI observability platform that helps engineers monitor, troubleshoot, and improve AI/LLM models in production.

Role type

Senior Fullstack Product Engineer (AI Observability)

Builds

ML observability platform, interactive playgrounds for prompt engineering, real-time evaluation infrastructure, and in-house AI Agents.

Domain

Artificial Intelligence, Machine Learning Operations (MLOps), Generative AI, SaaS

Deliverable

production ML models | product features

Required skills

TypeScript, React, Python, Go, API design, distributed systems, visualization algorithms, architectural decision-making

Preferred skills

Debugging complex systems, product ownership, experience with high-volume SaaS platforms

Technologies

TypeScript, React, Python, Go

Responsibilities

Write maintainable, scalable code across the stack; Design and build APIs and domain models for ML/LLM workflows; Build reusable React components; Research and implement visualization & dimensionality reduction algorithms; Collaborate with product, design, and customer engineering teams; Contribute to building in-house AI Agents; Participate in or lead architectural decisions.

Seniority

Senior, hands-on IC

Rewrite
## About the Role 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 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. 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 magically instrument applications, interactive playgrounds for prompt engineering and agent development, or scaling up real-time evaluation infrastructure to handle millions of annotations per second. ## Responsibilities - Write maintainable, scalable, and performant code across the stack primarily in Typescript and React with opportunities to work in Python and Go. - Design and build APIs, and domain / object models specific to our customers' Machine Learning and LLM workflows. - Design and build out performant and reusable react components that will be used throughout the application. - Research and implement cutting-edge visualization & dimensionality reduction algorithms in a distributed environment. - Collaborate with our product, design, and directly with customer engineering teams to enhance and expand our product offerings. - Contribute to the build our own in-house AI Agents. - Participate in or lead architectural decisions for new and existing features in collaboration with product, design and our backend teams. - Contribute to design & code reviews and technical documentation. ## Requirements - 5+ years of frontend experience working on external user-facing UI's - preferably in React and Typescript. - Previous experience debugging complex systems in a team environment. - Enthusiasm and interest in the AI and LLM ecosystem, with a desire to learn and stay updated on emerging technologies. - Previous work building and operating highly complex, high-volume SaaS platforms/systems. - Strong sense of product ownership in order to push fea
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