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Sierra is building a platform enabling companies to create better, more human customer experiences with AI. The company partners with industry leaders including SoftBank, Uber, Rivian, CLEAR, and Sutter Health, and is headquartered in San Francisco with growing offices across North America, Europe, and Asia.
As a Strategist in Agent Development, you will own the complete lifecycle of how Sierra's AI agents come to life for customers—from initial pilot through production deployment handling thousands of conversations daily. You sit at the intersection of product, technical agent building, and customer-facing work, staying equally close to the technology and the people you build for.
Key responsibilities include:
- Own the Agent Development Life Cycle, taking agents from initial scope through conversation design, tooling, and evaluation to launch and continuous iteration in production. Translate business goals into agents that outperform and tune relentlessly until optimal in the real world.
- Serve as a trusted strategic advisor to enterprise leaders, sitting shoulder-to-shoulder with customer executives to understand what success means to their business and shaping the AI strategy to get them there.
- Partner with customer working teams day-to-day, running working sessions, troubleshooting agents as issues arise, and making calls that keep builds on track for launch.
- Directly impact product by surfacing unmet needs from customer work and feeding them back to research and platform teams to shape Sierra's direction.
Recent projects include scoping and launching subscription-retention agents for telecommunications/media companies, building commerce agents that troubleshoot devices and personalize recommendations, redesigning conversation flows for regulated financial services interactions, partnering on net-new agent capabilities with live customers as design partners, and defining evaluation metrics to drive measurable outcome improvements.
You bring customer obsession, clear communication across technical and non-technical audiences, strategic problem-solving in ambiguity, technical aptitude (comfortable with API documentation, data models, system architecture), and a track record of running complex, high-visibility projects to outcomes. Ideal candidates have hands-on experience building or deploying AI/LLM agents in production, founding or early-stage operating experience, and a technical degree (CS, Engineering, Mathematics) or equivalent practical experience, ideally complemented by an MBA or comparable technology-business experience.
