Top Tech Jobs & Startup Jobs in Austin, TX

Drive enterprise SaaS sales across EMEA by prospecting AI and machine learning stakeholders, conducting discovery, presenting Arize’s platform, managing proof-of-concept engagements, navigating complex sales cycles, closing new business, driving adoption, and expanding customer accounts. The role requires full-cycle enterprise sales expertise, strong communication, independent execution, account research, and relationship-building within the AI/ML community.

Deploy and support distributed SaaS and on-premise infrastructure, gather customer requirements, adapt deployment manifests, monitor platform health, troubleshoot issues, package releases, and automate release pipelines across Kubernetes and AWS, GCP, and Azure environments.

Own the end-to-end user experience for a technical B2B SaaS product. Responsibilities include researching user friction, observing sessions in FullStory, prototyping flows in Figma or code, refining interaction patterns, implementing design improvements, building reusable design systems, partnering with engineers, and conducting usability tests. The role emphasizes UX refinement, edge cases, loading and empty states, smooth transitions, and incorporating user feedback.

The role involves developing scalable backend systems in Go and other languages, building high-volume analytics, and designing APIs for ML workflows.

As a Senior AI Product Engineer, you will build scalable services and front-end applications, design APIs, and enhance AI product offerings, focusing on improving user experience and collaboration with engineering teams.

Design and prototype user experiences for AI tools, creating interactive visualizations and reusable components that enhance both human and AI interactions in the workspace.

As a Technical Product Manager at Arize, you will strategize and develop the product roadmap, engage customers for feedback, collaborate with cross-functional teams, and integrate market insights into product requirements.

The AI Sales Engineer will build relationships with customers, lead product demonstrations, handle objections, and act as a domain expert in ML. Responsibilities include collaborating with sales and technical teams to create value propositions and developing educational materials about ML and MLOps.