Senior Manager, Engineering & AI Agent Enablement

At Sonos we want to create the ultimate listening experience for our customers and know that it starts by listening to each other. As part of the Sonos team, you’ll collaborate with people of all styles, skill sets, and backgrounds to realize our vision while fostering a community where everyone feels included and empowered to do the best work of their lives.

This is an on site position. Qualified applicants must live within commuting distance of our Santa Barbara, Seattle, or Boston office locations and should expect to be in office 5 days a week.

Visa Sponsorship:
Sonos is unable to sponsor or take over sponsorship of an employment visa for this role at this time. We ask that applicants be authorized to work for us in country of role posting, both now and in the future.

Sonos is a leading technology hardware and software company dedicated to delivering innovative home audio experiences.

Our Care organization powers customer success through deep technical expertise, and Knowledge and AI are our strategic advantage. We are building a modern, AI-enabled knowledge ecosystem and autonomous service agents that together accelerate resolution, empower agents and customers, and drive continuous improvement across our global support operations.

We are hiring a Senior Manager, Knowledge Engineering & AI Agent Enablement to serve as product owner for two connected capabilities at the core of Sonos Care's AI transformation: the structured, machine-ready knowledge that autonomous agents and retrieval systems depend on, and the autonomous service agents themselves.

This is a dual-remit people leadership role reporting to the Director, CX Product within the Care Enablement & Services organization.

Own the product vision, roadmap, and backlog for Knowledge Engineering and AI Agent Enablement as a unified capability, translating business and customer needs into clear, prioritized requirements for engineering, data science, and AI partner teams. Lead the Knowledge Engineering team and the AI Agent Enablement team: hire, coach, and develop managers and individual contributors across both disciplines, set goals, calibrate performance, and build career paths in two fast‑evolving fields.

Direct the strategy for making structured knowledge assets clean, well‑modeled, and AI‑ready, including taxonomy and ontology governance, metadata standards, data quality, and the retrieval layers (search, retrieval‑augmented generation) that humans and agents draw on. Own the roadmap for autonomous service agents — which issues they resolve, how they elevate, and how they improve over time — overseeing conversation and prompt design, tool and API integrations, and grounding agents in structured knowledge systems.

Establish agent evaluation and benchmarking practices covering accuracy, containment rate, safety, and quality, with human review loops and clear escalation paths to human agents. Govern agent behavior and risk: guardrails, hallucination controls, brand and tone consistency, and compliance sign‑off before agents go live or expand scope. Run agile planning, backlog refinement, sprint reviews, and retrospectives across both teams, partnering with support engineering, data science, and external AI partners on underlying orchestration and infrastructure.

Define, track, and report on KPIs across both remits — knowledge usage, content quality, agent containment, resolution accuracy, escalation rate, customer satisfaction, and combined effects on handle time and case deflection — and use data to drive continuous improvement. Partner with Support leadership, Diagnostic Engineering, Data Science, Training & Quality, and executive stakeholders to prioritize investment, close capability gaps, and present…