Principal Inbound Product Manager, CRM Voice AI

How We Work

We work in pods - small, dedicated teams embedded with a single enterprise customer, building their voice agents from first call to self-sufficiency. A pod owns the full lifecycle: agent shadowing, conversation design, build, production go-live, monitoring and optimization and the handoff that makes the customer self-sufficient so the pod can move on to the next one. Each pod pairs forward-deployed engineers with a product manager who owns both the customer outcome and the product learning that comes from it.

Every PM on this team runs at least one pod directly and has visibility across others. You're in the customer's world - on their calls, in their systems, solving their problems - while simultaneously shaping what the product becomes. The learnings from your pods feed directly into the platform roadmap and into repeatable, productized assets that scale beyond any single customer.

What This Role Owns

• You run one pod directly and float across one to two others, providing product direction and unblocking teams. You own the relationship with the customer's leadership team, setting the timelines and expectations, then delivering on them.
• For those pods, you and your team of FDEs own agent design, the build and evaluation.
• Beyond your pods, you own STT and TTS model evaluation and experimentation for CRM Voice AI. The speech model landscape is moving fast. New ASR and TTS models ship constantly, each with different tradeoffs on latency, accuracy, naturalness, language support, and cost. You run structured evaluations against real production workloads, collaborate closely with the platform voice team on model decisions, and drive experimentation across our customer base. When a new model drops and the question is "should we move our customers to this?" - you're the one with the methodology, the data, and the production context to answer it.
• You also support a variety of industry verticals. As you see patterns across your pods and model evaluations, you identify which capabilities and conversation designs can be prioritized and productized for a specific industry, building the playbook for how CRM Voice AI enters a new market.

Why This and Not Somewhere Else

The pod model means you'll accumulate more production voice AI experience in a year than most PMs get in several - building agents across different industries, different contact center environments, and different conversation types. On top of that, speech models are the most dynamic layer of the voice AI stack right now, and most PMs evaluating them do it in a lab.

You're doing it against real production traffic with enterprise customers who have real SLAs. You sit at the intersection of the platform team building the voice infrastructure and the CRM team deploying it, with influence in both directions. The right evaluation methodology is a genuine competitive advantage, and you're the person building it.

What You Bring

• 8+ years of product management experience, with recent work in voice AI, conversational AI, or speech technology.
• Hands-on experience building and evaluating AI agents - conversation design, prompt engineering, testing and iteration against real user interactions. This is the foundation; speech model expertise layers on top of it.
• Working knowledge of speech models - ASR architectures, TTS synthesis approaches, and the tradeoffs between latency, accuracy, naturalness, and cost. You've evaluated or deployed these in production, not just prototyped.
• Comfort with experimentation and evaluation methodology. You know how to design a test, instrument it, and turn the results into a product decision.
• Experience with telephony integration: SIP, call transfers, IVR systems, or CCaaS platforms.
• Experience working directly with enterprise customers on technical products.
• Ability to context-switch between deep technical model evaluation and customer-facing product work without dropping either.

Even Better

• Hands-on experience benchmarking across multiple ASR or TTS providers.
• Background in machine learning or audio/speech engineering, enough to hold your own in model architecture discussions.
• Industry expertise in verticals with high contact center volume: telecommunications, financial services, travel, healthcare.

Pay and benefits

For positions in this location, we offer a base pay of $166,500 - $291,400, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure.

Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs.

Compensation is based on the geographic location in which the role is located and is subject to change based on work location.

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