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Sierra is building a platform enabling enterprises to deploy AI agents that deliver better, more human customer experiences. The company partners with industry leaders including SoftBank, Uber, Rivian, CLEAR, and Sutter Health, and is founded by Bret Taylor (former Salesforce co-CEO, Google Maps co-creator, OpenAI Board Chair) and Clay Bavor (18-year Google veteran, led Google Labs and AR/VR initiatives).
As an Agent Strategist, you own the complete agent development lifecycle for Sierra's customers—from initial scoping through conversation design, tooling, evaluation, launch, and continuous production iteration. You translate business goals into measurable agent outcomes and tune relentlessly until the agent outperforms in the real world.
Key responsibilities include: owning the agent development lifecycle and ensuring agents move from pilot to production handling thousands of conversations daily; serving as a trusted strategic advisor to enterprise executives, understanding their success metrics and shaping AI strategy; partnering with customer working teams on daily execution, running sessions, troubleshooting, and keeping builds on track; and directly impacting Sierra's product roadmap by surfacing unmet customer needs to research and platform teams.
Recent projects include scoping and launching subscription-retention agents for telecom/media companies, building commerce agents that troubleshoot devices and personalize recommendations, redesigning conversation flows for regulated financial services interactions, partnering on net-new agent architectures, and defining evaluation frameworks that drive measurable weekly outcome improvements.
You bring genuine customer obsession and energy for understanding business needs in complex organizations; clear, direct communication across technical and non-technical audiences; strong analytical and critical-thinking skills to break down complex problems and adapt quickly; technical aptitude to engage with APIs, data models, system architecture, and engineering tradeoffs; and a track record of running multiple high-visibility projects to completion. Financial services experience—whether in fintech, at financial institutions, or with knowledge of compliance (fair lending, PII handling)—is a strong plus.
Ideal candidates have hands-on experience building or deploying AI/LLM agents in production, familiarity with eval frameworks, agent tooling, RAG, and prompt engineering, founding or early-stage operator experience, and a technical degree (CS, Engineering, Mathematics) or MBA with technology-business intersection experience.
