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><h3><strong>The Opportunity</strong></h3> <p>We are seeking an experienced Forward Deployed AI Engineer to work directly with client engineering teams, manage multiple concurrent projects, and drive technical solutions that extend beyond our core platform offering. This is a client-facing, hands-on technical role that combines deep AI expertise with business acumen to deliver results on tight timelines while building lasting client relationships. <span style="font-weight: 400;"><strong>While we are a remote-first company, we are prioritizing candidates currently based in the London metro area.</strong></span></p> <h3>What You’ll Do</h3> <ul> <li>Partner directly with enterprise AI teams to design, implement, and scale production-grade GenAI observability and evaluation programs.</li> <li>Lead technical discussions with customer stakeholders ranging from engineers to senior executives, translating business priorities into scalable technical solutions.</li> <li>Build custom integrations, tooling, and workflows that extend the Arize platform to meet customer-specific requirements.</li> <li>Manage multiple concurrent customer engagements, driving projects from scoping through delivery while maintaining a high bar for technical execution and customer experience.</li> <li>Collaborate cross-functionally with Sales, CS, Product, and Engineering teams to shape implementation strategy, influence product direction, and expand customer impact.</li> <li>Help define and scale best practices, technical playbooks, and delivery methodologies for the growing Forward Deployed Engineering team.</li> </ul> <h3>What We’re Looking For</h3> <ul> <li><strong>Software Development:</strong> 2-5 years of hands-on software development experience with strong technical foundations. We work extensively in Python, Java, and TypeScript, and expect candidates to be comfortable working in at least two of those languages.</li> <li><strong>ML/AI Engineering:</strong> Experience building MLOps pipelines and/or developing, deploying, and iterating on Generative AI applications in production environments.. </li> <li><strong>Cloud Technologies</strong>: Experience working with public cloud platforms (e.g., AWS, GCP, Azure) as well as containerization and orchestration technologies (e.g., Docker and Kubernetes).</li> <li><strong>Communication: </strong>Excellent communication skills with the ability to work effectively across both technical and business audiences. You should be comfortable engaging with senior executives on business outcomes and metrics, collaborating with engineers on technical implementation details, and translating seamlessly between the two.</li> <li><strong>Project Management: </strong>Proven ability to manage multiple client engineering engagements simultaneously and deliver high-quality technical outcomes under demanding timelines.</li> <li><strong>Adaptability: </strong>Comfortable operating in fast-paced startup or consulting environments, with the ability to navigate diverse client organizations, technical stacks, and evolving priorities.</li> <li><strong>Passion for AI: </strong>We live and breathe AI at Arize. The strongest candidates are genuinely excited about the space and energized by staying at the forefront of rapidly evolving AI technologies.</li> </ul> <p><span style="font-weight: 400;">The estimated annual salary and variable compensation for this role is between $155,000 - $190,000 USD, 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.</span></p> <p><span style="font-weight: 400;">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.</span></p><div class="content-conclusion"><h3>More About Arize</h3> <p>Arize’s mission is to make the world’s AI work—and work for people.<br>Our founders came together through a shared frustration: while investments in AI are growing rapidly across every industry, organizations face a critical challenge—understanding whether AI is performing and how to improve it at scale.</p> <p>Learn more about what we're doing here:</p> <p><a href="https://techcrunch.com/2025/02/20/arize-ai-hopes-it-has-first-mover-advantage-in-ai-observability/">https://techcrunch.com/2025/02/20/arize-ai-hopes-it-has-first-mover-advantage-in-ai-observability/</a></p> <p><a href="https://arize.com/blog/arize-ai-raises-70m-series-c-to-build-the-gold-standard-for-ai-evaluation-obse