Director of Product Management – Agentforce Voice Models

Salesforce

. Define and own the multi-year roadmap for Agentforce voice capabilities across ASR/STT, TTS, S2S, and real-time voice agents .

Posted 10/2/2026full-timeUnited StatesLead💰 $197,300 - $313,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in speech and audio machine learning, with a focus on ASR, neural TTS, and real-time speech processing. Proven ability to lead teams, drive architectural decisions, and ensure compliance with ethical AI standards in voice technology.

Highest-signal resume keywords

Speech/Audio Machine LearningASR Systems DevelopmentNeural TTS ExpertiseTeam LeadershipMultilingual NLP/ASR Challenges

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ASRNeural TTSSpeech Processing PipelinesSpeaker DiarizationProsody ModelingPythonPyTorchJAXModel TrainingVoice Biometric Capabilities

Soft Skills

Excellent CommunicationTeam DevelopmentCollaboration

Tools & Technologies

AWSGCPAzureSalesforceWebRTC

Certifications & Qualifications

PhD in Computer SciencePhD in Electrical EngineeringPhD in Linguistics

Industry Keywords

Voice AI EthicsDeepfake DetectionVoice Data ComplianceLocalizationData Governance

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPythonPyTorchSwitching

About the role

Key responsibilities & impact

Define and own the multi-year roadmap for Agentforce voice capabilities across ASR/STT, TTS, S2S, and real-time voice agents
Set accuracy, latency, and quality benchmarks and drive the organization to meet them
Evaluate build, buy, and partner decisions for new voice model capabilities
Lead production-grade ASR systems for telephony, WebRTC, and device-side deployment
Drive multilingual and code-switching ASR coverage and govern language onboarding
Own the neural TTS pipeline, including voice cloning, persona design, SSML compliance, and real-time synthesis
Lead prosody research for natural-sounding enterprise voices
Manage voice talent agreements, ethical AI review, and consent frameworks
Architect low-latency speech-to-speech pipelines for full-duplex conversational AI
Integrate voice understanding with agent action loops, tool calls, CRM lookups, and escalation routing
Establish interruption, barge-in, and turn-taking models
Deliver production speaker diarization for multi-party calls
Develop speaker verification and voice-biometric capabilities
Surface voice-derived signals in Salesforce dashboards
Own global language support and localization roadmap
Establish data governance, annotation, and quality-control pipelines for low-resource languages
Recruit, develop, and retain a team of 20–30 research engineers, applied scientists, and ML engineers
Set technical direction, drive architectural decisions, and maintain engineering excellence
Build a culture of experimentation, voice safety red-teaming, and continuous model refreshes
Translate customer and regulatory requirements into model specifications and acceptance criteria
Collaborate with Legal, Privacy, and Trust & Safety on voice AI ethics, consent, deepfake detection, and compliance
Represent Agentforce Voice at conferences, standards bodies, and customer briefings

Requirements

What you’ll need

10+ years in speech/audio machine learning
4+ years in a senior leadership role managing teams of 10 or more engineers or scientists
Deep hands-on expertise in at least two of ASR, neural TTS, or real-time speech processing pipelines
Proven track record of shipping production voice models at scale, serving millions of minutes per day, with measurable accuracy and latency improvements
Fluency in prosody modeling, including pitch contour modeling, duration prediction, and expressiveness fine-tuning
Experience with speaker diarization systems
Strong understanding of multilingual and multi-dialect NLP/ASR challenges
Experience with at least 5 languages in production
Proficiency in Python
Experience with PyTorch or JAX model training at scale
Familiarity with AWS, GCP, or Azure cloud-based training infrastructure
Excellent written and verbal communication
Preferred: PhD in Computer Science, Electrical Engineering, Linguistics, or related field with a speech/audio focus, or equivalent industry experience
Preferred: Familiarity with streaming inference, model quantization, and on-device deployment
Preferred: Experience with voice safety, watermarking, and deepfake/spoofing detection
Preferred: Background in SIP, RTP, WebRTC, and enterprise contact-center platforms
Preferred: Published research or patents in speech processing or audio ML
Preferred: Experience in regulated industries with voice data compliance requirements

Benefits

Comp & perks

Time off programs
Medical insurance
Dental insurance
Vision insurance
Mental health support
Paid parental leave
Life insurance
Disability insurance
401(k)
Employee stock purchasing program
Access to proprietary, enterprise-grade voice data
Access to world-class compute
Autonomy of a startup within the resources of a $35B+ company
Responsible AI commitment
Reasonable accommodation during the application or recruiting process