Own the discovery, development, launch, and continuous improvement of voice AI agents for field service businesses. Lead customer research, product prioritization, agent behavior experiments, integrations, conversation quality evaluations, and adoption tracking. Partner closely with customers, engineering, and design while optimizing task completion, accuracy, reliability, latency, cost, and handoff quality across real-world phone interactions.
We’re looking for a hands-on Product Manager to build voice AI agents for field service businesses. These agents need to do more than hold a conversation. They need to understand customer needs, take the right actions and complete tasks reliably over the phone.
You’ll own inbound and outbound calling experiences, working closely with customers, engineering and design from discovery through launch and ongoing improvement.
What you’ll own
- Customer discovery and product direction: understand how businesses handle calls, identify opportunities and prioritise the workflows that deliver the most value.
- Agent behaviour: experiment with prompts, models and conversation flows. Review call recordings and transcripts to understand failures and improve the experience.
- Integrations: work with engineering and other business-system integrations, including tool calling, missing information and failed actions.
- Quality and evaluations: define test scenarios and success criteria for real-world conversations, including ambiguous requests, interruptions, incorrect answers and unsuccessful actions. Validate changes before rollout and monitor performance after launch.
- Outcomes and adoption: track task completion, booking accuracy, handoff quality, response latency, reliability, cost per successful interaction and customer adoption.
What we’re looking for
- 4+ years of product management experience, including hands-on experience shipping and improving AI or conversational products in production.
- Experience translating customer problems into clear requirements, priorities and measurable outcomes.
- Practical understanding of how speech-to-text, LLMs and text-to-speech work together, and how agents use knowledge sources, tools and APIs.
- Familiarity with voice-specific challenges such as turn-taking, interruptions, latency, accents and background noise.
- Experience with prompt/model experimentation, evaluations and using customer conversations to guide product decisions.
- Good judgment on quality, speed and cost trade-offs, including when an agent should clarify, retry or hand over to a person.
- Confidence leading customer conversations and demos, explaining product limitations and working with customers through adoption.
This is a product role with technical depth. You should be comfortable working through problems with engineering and staying close to how the agent performs in real customer conversations.
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