Top Artificial Intelligence Jobs

Work with customers to configure and maintain Cresta's Opera platform, identify key moments using keyword/utterance rules, monitor voice analytics trends, produce insight reports, respond to ad hoc analysis requests, and mentor customer analysts to maximize product value.

Own the company’s commercial development from prospecting through signed projects. Identify developers and hyperscalers pursuing large-scale energy and data center projects, leverage investor and industry networks, educate customers on faster iterative engineering, and discover opportunities aligned with the product. Translate customer needs into product priorities while managing every detail independently. Automate repetitive work with AI and build relationships with sophisticated customers in an early, in-person San Francisco environment.

Build end-to-end product features with a backend focus: schema and API design, UI work in React/TypeScript, GCP/Terraform infrastructure, CI/CD, DB performance tuning, production ownership, and product decision-making using AI coding tools.

Build and improve a scan-to-BIM pipeline that converts point-cloud capture data into accurate, structured 3D BIM models. Responsibilities include model creation, mesh generation, data structuring, IFC and 3D-tool usage, and applying computer vision to automate 3D reconstruction. The role requires construction knowledge and hands-on experience with detailed 3D projects, with occasional quarterly onsite gatherings in San Francisco.

Own the finance and accounting product roadmap for an AI-native ERP, covering general ledger, AP, AR, costing, close, and financial reporting. Partner with finance leaders and operators to understand workflows, define product specifications, prioritize capabilities, and collaborate with engineering through release. Validate features, create test cases and release materials, conduct customer discovery and demos, and continuously improve the product based on customer feedback and operational needs.

Own full-stack product features from technical scoping through deployment and post-launch iteration. Design schemas, APIs, and business logic; build user-facing applications across frontend, backend, and databases; collaborate with ML researchers, product, design, and engineering; incorporate user feedback; and improve development, testing, and deployment practices.

Build and lead AssemblyAI’s digital-native sales organization, scaling Account Executives and front-line managers. Own revenue growth, hiring, org design, territories, quotas, compensation, forecasting, pipeline generation, and sales operating cadence. Partner with engineering, research, marketing, and customer-facing technical teams to convert product evaluations into production usage. The role requires technical credibility with APIs and AI infrastructure, experience scaling sales teams, strong recruiting ability, and frequent travel.

Own full-cycle recruiting for GTM, Sales, Customer Success, and other Utah-based roles. Source candidates through referrals, outbound recruiting, and creative strategies; partner with founders and leadership on high-priority hires, quality of hire, and team scaling. Provide market trends and hiring data, lead recruiting initiatives end to end, and serve as a strategic partner to the talent team and hiring leaders.

Configure the Plenful platform for new customers, lead customer-facing implementations, provide technical support, and manage implementation timelines. Partner with Sales, Account Management, Product, and Engineering to define requirements, communicate customer feedback, develop use-case templates, and support expansions. The role requires solving technical problems, explaining complex concepts clearly, managing multiple accounts, and working with healthcare integrations and data formats.

Own end-to-end technical implementation and onboarding for enterprise B2B SaaS customers, from kickoff through go-live. Manage project plans, data integrations, documentation, customer communication, implementation metrics, and handoffs to ongoing customer success. Troubleshoot data pipelines, coordinate with engineering and product, remove implementation roadblocks, and build scalable methodologies that reduce time-to-value. The role requires strong SQL and data integration skills, enterprise stakeholder management, and regular onsite work with Chicago-area customers.