Senior Director, Technical Product Management – AI Quality & Evaluation

Salesforce

. Build the next generation of Agentforce within Salesforce’s entrepreneurial incubation team .

Posted 11/6/2026full-timeRemote • United StatesSenior💰 $218,400 - $365,200 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building AI/ML products with a focus on customer outcomes, quality evaluation, and product strategy. Capable of leading cross-functional teams and delivering insights through experimentation and data analysis.

Highest-signal resume keywords

AI/ML Product DevelopmentGenerative AI ExperienceApplied AI/ML JudgmentData Inspection and PrototypingCoaching and Mentoring

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Agent DevelopmentEvaluation CapabilitiesExperimentationQuality DefinitionData AnalysisPrototyping with Coding AgentsModel Behavior AssessmentTraining/Test SplitsEdge Case ReasoningUncertainty Management

Soft Skills

Clear CommunicationCross-Team CollaborationIndependent DeliveryCoachingMentoring

Tools & Technologies

Evaluation PlatformsAI ObservabilityAgent SystemsEnterprise AI Products

Industry Keywords

AI QualityCustomer FeedbackProduct StrategyEntrepreneurial EnvironmentFast-Moving Environment

About the role

Key responsibilities & impact

Build the next generation of Agentforce within Salesforce’s entrepreneurial incubation team
Shape product strategy for AI quality and evaluation
Establish how AI progress is measured, including quality definitions, evaluation requirements, coverage priorities, and release criteria
Set product strategy and roadmap connecting customer needs, technical opportunities, and measurable business outcomes
Make investment tradeoffs across customer quality improvements, evaluation capabilities, and product features
Lead customer investigations and experiments into incorrect agent answers and failed tool-driven workflows
Define expected behavior and partner with researchers and engineers to test changes and validate customer impact
Build an operating approach connecting customer feedback, evaluation evidence, experiments, releases, and learning
Partner with researchers, applied scientists, and engineers to design credible evaluations
Lead delivery of capabilities that help customers understand and improve AI performance
Coach product partners, junior designers, and technical program managers
Bring verified competitive insight into strategy and communicate differentiation, limitations, and investment choices
Independently take quality problems from failure analysis through experimentation and customer validation
Deliver a focused feature with engineering and improve release and investment decisions through evidence and product judgment

Requirements

What you’ll need

Record of building AI/ML products and delivering measurable customer outcomes, with increasing ownership, scope, and impact
Deep hands-on experience building AI agents and evaluation capabilities with AI researchers, applied scientists, or AI engineers
One to two years of substantive generative AI experience can be sufficient when supported by strong AI/ML fundamentals and demonstrated impact
Strong applied AI/ML judgment across model behavior, prompting, retrieval, agent/tool workflows, and tradeoffs among model, data, system, and product improvements
Current hands-on ability to inspect data and traces, prototype with coding agents, and reason about experiments, overfitting, training/test splits, edge cases, and uncertainty
Ability to define quality for a non-deterministic system and challenge technical conclusions
Experience establishing shared standards and resolving cross-team disagreements while preserving accountability and delivery momentum
Evidence of coaching and mentoring colleagues without reporting authority
Ability to deliver independently in a fast-moving environment
Clear communication with customers, technical teams, and senior leaders
Preferred: evaluation platforms, agent systems, AI observability, retrieval, or enterprise AI products
Preferred: experience in an AI-native startup or entrepreneurial environment
Preferred: hands-on prototyping with coding agents and customer-facing performance or outcome experiences
Preferred: leading initiatives across research, engineering, product, and customer-facing organizations

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
Certain roles may be eligible for incentive compensation and equity
Reasonable accommodation during the application or recruiting process