Jobs at Arize AI

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.

Design and open-source LLM observability libraries, pipelines, and APIs; collaborate with the OSS community; prototype LLM techniques; integrate tooling into Arize's platform to improve debugging, evaluation, and metrics; and produce docs, tutorials, and evangelism to grow the LLM evaluation community.

As an AI Solutions Manager, you'll nurture AI/ML customer relationships, drive product adoption, and ensure client success through tailored solutions and account management.

Partner with EMEA AI/ML teams to drive adoption of Arize's observability platform, manage accounts through onboarding and renewals, run workshops/QBRs, identify upsell opportunities, and coordinate technical resources to ensure customers achieve measurable AI outcomes.

The AI Solutions Engineer will advise clients on ML and GenAI best practices, demonstrate product value, and drive business reviews and expansions.

Own expansion and renewal sales within an enterprise customer base. Identify growth opportunities via usage analysis, build executive relationships, execute account strategies with internal teams, forecast and maintain Salesforce hygiene, and travel as needed to drive upsell and long-term expansion.

The Forward Deployed Engineer will work with client engineering teams to design and implement GenAI observability programs, manage projects, and maintain client relationships, requiring strong technical and communication skills.

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

The Account Executive will find, win, and grow new customers in the AI/ML sector, managing complex sales cycles and relationships with stakeholders.

As an AI Solutions Manager, you will drive customer adoption of AI technologies, build relationships, conduct discovery, and collaborate with technical teams to address customer needs, focusing on measurable business outcomes.

As an AI Application Engineer, you will debug and improve platforms, develop AI tools and proof-of-concepts, and collaborate across teams to enhance AI systems.

The Technical Product Marketing Manager will enhance developer engagement and growth through effective messaging and experiences with the Arize ecosystem, focusing on Phoenix.

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.

Partner with Account Executives to present Arize's GenAI observability platform, lead technical demos and discovery, design and run PoCs, advise on GenAI/LLM best practices, handle technical objections, and build relationships with technical and business stakeholders across prospective customers.

The Account Executive will engage with AI/ML leaders, drive sales strategies, manage accounts, and facilitate proof of concept engagements to grow new customers.

As an AI Solutions Manager, you will foster relationships, drive customer adoption of AI solutions, manage renewals, and identify growth opportunities.

The role involves managing cloud partnerships, driving revenue growth, coordinating field enablement, and optimizing marketplace operations across major cloud platforms.

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

Drive new business and grow enterprise accounts for Arize AI by prospecting, conducting discovery with AI/ML stakeholders, managing complex full-cycle sales and proof-of-concepts, and collaborating cross-functionally. Use strategic sales plays, deep account research, and stakeholder management to close deals and expand usage.