SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 190,900 - 334,100 / annual
ServiceNow's CRM Voice AI team is building autonomous voice agents for enterprise customer service that resolve interactions end-to-end. The team operates in pods—small, dedicated teams embedded with enterprise customers—shipping production voice AI and scaling aggressively against well-funded AI startups and CCaaS incumbents.
In this role, you will run one of the team's most complex customer engagements directly while providing product direction across two additional pods. You own the full lifecycle: agent shadowing, conversation design, build, production go-live, monitoring, optimization, and customer handoff. You manage relationships with customer leadership teams, setting and delivering on timelines and expectations.
Your core responsibilities include:
- Owning agent design, build, and evaluation for your primary pod and supporting pods
- Driving ServiceNow's conversational experience: dialog quality, turn-taking, interruption handling, barge-in behavior, and endpointing
- Collaborating directly with the platform voice team on voice pipeline innovation, low-latency infrastructure, real-time streaming, LLM orchestration, and voice-to-voice model integration
- Supporting customers across industry verticals and evaluating which patterns, intents, and conversation flows can be productized into out-of-the-box voice content
- Turning one-off customer wins into repeatable, scalable assets
You'll combine startup-speed execution with enterprise scale, shipping production voice AI with real customers while influencing platform architecture decisions with production data. The role puts you in a customer's contact center debugging live voice agents one day and shaping platform infrastructure decisions the next.
Requirements:
- 12+ years of product management experience with recent hands-on work shipping voice AI or conversational AI products (last 12-18 months of shipping matters most)
- Hands-on experience building and evaluating AI agents: conversation design, prompt engineering, testing and iteration against real user interactions
- Fluency with the voice stack: ASR, TTS, streaming pipelines, latency optimization, endpointing, barge-in, turn-taking (with real tradeoff decisions, not just vendor evaluation)
- Experience with telephony integration: SIP, call transfers, IVR systems, or CCaaS platforms
- Direct experience working with enterprise customers on technical deployments in their environment, on their calls, solving their problems
- Strong opinions on what makes voice conversations feel human, backed by experience building or evaluating conversational systems
- Technical depth in LLM orchestration for real-time conversational use cases
- Experience defining voice-specific evaluations: task completion, latency, transcription accuracy, conversational quality
Preferred:
- Track record of productizing customer-specific solutions into repeatable, industry-level assets
- Industry expertise in high-volume contact center verticals: telecommunications, financial services, travel, healthcare
