Director, AI Talent + Employee Experience Practices, Employee Success
SalesforceAbout the role
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Job Category
Employee SuccessJob Details
About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
About Salesforce
Salesforce helps organizations of any size reimagine their business with AI. Agentforce — the first digital labor solution for enterprises — seamlessly integrates with Customer 360 applications, Data Cloud, and Einstein AI to create a limitless workforce, bringing humans and agents together to deliver customer success on a single, trusted platform.
Salesforce has 5 core values: Trust, Customer Success, Innovation, Equality and Sustainability. Beyond being a core value- Equality is how we innovate and lead. Join the Equality and Engagement team as we create equal opportunities, industry-leading talent experiences, and bring everyone along in the future of Agentforce.
About the Role
This is a leadership role within our Employee Success (HR) organization. As we lead through the biggest technology transformation of our lifetime – humans and agents working together – the nature of our workforce is changing. This pivotal role will partner cross-functionally to design practices and strategy to drive AI and Agent-powered employee experiences that are aligned to employee success best practices at each stage of the lifecycle. This is an exciting opportunity to be on the leading edge and define the future of the digital workforce.
Primary Responsibilities
Design and Advise Human and Agent powered Employee Experience Practices
Partner with stakeholders to design best practices and policies that ensure our AI and Agent-powered employee experiences are compliant, accessible, and aligned to our employee success best practices at each stage of the lifecycle.
Anticipate and address emerging talent and AI opportunities and compliance implications
Stay abreast of the latest research, best practices, and regulatory developments in AI + Employee experience compliance, HR policy, employee relations, talent management and ethical use.
Translate employee success principles into practical and actionable guidance around AI for technical and non-technical stakeholders across ES.
Partner on Content Readiness, Process, and Governance Best Practices
Partner to ensure content, data, and processes are prepared for AI transformation
Collaborate through policy documents, steer-cos, and review boards
Influence Product Roadmap and Enhancements
Work with technical and ethical use teams to influence ES product roadmap
Partner on ES product innovation to drive employee engagement and embed our values into our employee experience and workforce.
Leverage Employee Insights to Inform Product and Workforce Innovation
Utilize employee insights to drive impactful and responsible AI and Agent product, process, and policy enhancements.
Thought Leadership and Narrative
Serve as a subject matter expert and thought leader on the AI and Agent powered employee experience
Amplify and drive cohesive narrative and approach to employees and agents working together in the current and future digital workforce.
Contribute to the development of best practices and standards for responsible AI in Employee Success
Experience + Skills
10+ years of progressive experience and/or advanced degree in human resources, employee policy, HR technology, responsible AI, talent management, employee experience, employee relations, or a relevant field, with demonstrated leadership experience.
Understanding of the HR tech stack (e.g. recruiting, performance management, employee analytics) and its intersection with AI use cases.
Working knowledge of AI/ML development cycles, technical guardrails, and model evaluation approaches.
Deep understanding of
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