Applied AI Engineer, Handshake AI Enterprise

About the Role

As an Applied AI Engineer at Handshake AI Enterprise, you'll embed directly inside enterprise customer environments as part of a small, expert team. You'll learn each customer's business deeply, their workflows, their bottlenecks, where the real leverage is, and translate that understanding into production-grade AI agents that measurably change how they operate. This isn't an implementation or consulting role. You'll own the full stack: defining the solution, building and deploying agents, designing evals, and iterating until performance actually moves. Over time, you'll become a genuine domain expert in your customer's vertical and use that expertise to build AI that keeps getting better. If you've built AI that works in the real world and want to do it again at much higher stakes, with better data, closer lab relationships, and a founding team that moves fast, this is the role. What You'll Do Embed directly with enterprise customers as part of a small deployment team, developing deep understanding of their business and workflows Define AI-driven solutions based on real business needs, not theoretical use cases Build and deploy production-grade agents tailored to specific customer use cases, owning end-to-end delivery Design and run evals to measure agent performance; iterate and hill-climb until results move Become a domain expert in your customer's vertical and use that expertise to build better AI over time Work closely with Product and Platform engineers on your team to ship cohesive, reliable solutions Establish engineering best practices, agent patterns, and reusable frameworks that help the team scale output without sacrificing quality Surface insights from deployments that inform Handshake's platform and product roadmap What We're Looking For Strong applied AI engineering experience and backend depth Real-world experience building and shipping AI applications in production, not just fine-tuning or prototyping Strong understanding of agent architectures, evals, and how to measure and systematically improve AI performance Comfort working directly with enterprise customers in ambiguous, high-stakes environments Strong systems thinking, you can zoom out to the business problem and zoom in to the technical solution without losing either thread High ownership mentality, you care about outcomes, not just outputs Strong communication skills, you'll be in the room with senior stakeholders regularly and need to earn their trust quickly Location:

San Francisco, CA | 5 days/week in-office Extra Credit Background at a company with a forward deployment or field engineering model Experience building multi-agent systems in production Domain expertise in a specific enterprise vertical (recruiting, finance, ops, legal, etc.) Familiarity with enterprise security requirements, VPC deployments, or on-prem configurations History of building evals infrastructure or AI quality measurement tooling