Top Artificial Intelligence Jobs

Lead and standardize client onboarding and integrations for a private-markets AI platform. Partner with Customer Success, Engineering, and Product to design scalable implementation workflows, ensure data integrity, mitigate risks, drive adoption, and use analytics to improve processes and outcomes in a fast-moving startup environment.

The Enterprise Account Executive will close new business, grow key accounts, build client relationships, manage the pipeline, and report results while contributing to team culture and strategy.

Lead the backend development for Artian's AI automation platform, focusing on scalable services, API design, and architectural decisions. Mentor engineers and enhance engineering practices in a collaborative environment.

The Implementation Associate will onboard customers onto the Hauler Hero platform, manage multiple projects, configure accounts, and communicate progress effectively.

Work alongside founders to own a piece of growth at an early-stage AI matchmaking startup. Responsibilities may include GTM strategy to scale users, sourcing and hiring the founding team, and implementing user feedback with founders and engineers. Requires systems-minded thinking and strong communication in a high-autonomy environment.

Triage and resolve technical customer issues by debugging complex systems, interacting with customers, developing fixes, collaborating with product, QA, DevOps, and automating tests and deployments to ensure high-quality support and product stability.

The role involves developing and executing new product features, collaborating with various teams, and influencing stakeholders, with a strong focus on B2B SaaS context.

Join the sales engineering team to assist customers, provide demos, guide proof of concepts, and collaborate with account executives to close deals.

The Lead Generation Specialist is responsible for executing multi-channel campaigns to generate qualified leads, optimizing campaigns, and driving attendance to events. The role demands a focus on measurable pipeline contribution, using AI for campaign improvements and maintaining CRM data.

The AI Infrastructure Engineer designs and builds infrastructure for AI and ML models across various environments, optimizing performance and reliability.