Product Management Director

Description About Employee Service at Salesforce Salesforce Employee Service Powers Next-generation Internal Support And Service Management. Our Platform Enables Organizations To Deliver Seamless IT And HR Experiences To Their Workforce By

• Automating internal service processes and streamlining cross-departmental workflows.
• Leveraging AI to intelligently mine knowledge, resolve employee inquiries instantly, and power autonomous, agent-driven interactions.
• Delivering exceptional employee experiences with intelligent case routing, predictive insights, and real-time collaboration tools that boost enterprise productivity.

About The Role We’re seeking a visionary Director of Product Management to lead our next-generation AI initiatives and drive the strategy of AI-first, collaboration-first, and platform-centric innovations across our Employee Service portfolio (spanning IT Service Management and HR Service Delivery). This role is critical to building enterprise-grade internal service solutions that empower employees, IT helpdesks, and HR teams at scale.

You will lead the charge in transitioning our employee service paradigm from reactive ticketing to proactive, autonomous workflows. You will build and scale enterprise-grade Agentic AI systems, determining how autonomous agents collaborate with human employees, integrating state-of-the-art LLMs, and defining the future of AI-first work.

As the owner of the AI roadmap, you will translate the latest industry trends—spanning Generative AI and Predictive Machine Learning—into scalable product features. Working cross-functionally with engineering, data science, UX, sales, and marketing, you will ensure our AI solutions remain cutting-edge, secure, and highly impactful for transforming how enterprises support their workforce.

What You’ll Do

• Define Product Strategy: Own the product vision and strategy for AI-driven capabilities within Employee Service (IT and HR domains), ensuring alignment with broader business goals.
• Agentic AI Leadership: Lead the conceptualization and delivery of Agentic AI workflows, enabling autonomous, task-oriented AI agents to resolve internal IT tickets and HR requests.
• Architectural Strategy: Drive product and architectural decisions around LLM integration, RAG pipelines, and agent orchestration frameworks. You will own the trade-offs between model performance, latency, cost, and context window optimization.
• AI Trust, Safety & Evals: Design robust evaluation frameworks for AI agents to measure accuracy, mitigate hallucinations, manage prompt injection risks, and maintain enterprise-grade data privacy.
• AI-First UX: Define the UX paradigms for human-in-the-loop (HITL) interactions, ensuring seamless handoffs between autonomous agents and employees/IT Teams.
• Customer Discovery & Integration: Engage directly with enterprise customers to understand complex pain points, specifically focusing on how they discover, adopt, and integrate AI applications into their internal IT, HR, and custom enterprise ecosystems (e.g., via API-based integrations and secure server environments).
• Cross-Functional Execution: Collaborate deeply with engineering, data science, and UX teams to build scalable, intuitive, and high-performance AI solutions, driving prioritization and trade-offs.
• Go-to-Market Alignment: Partner with sales, marketing, and enablement teams to define GTM strategies, positioning, and messaging to ensure successful product launches and market adoption.
• Executive Communication: Regularly present product updates, AI strategies, and measurable results to C-suite leadership and external partners, ensuring continuous alignment.
• Data-Driven Iteration: Leverage data-driven insights to continuously improve product offerings, tracking employee adoption, operational cost savings, and market share expansion.

What We’re Looking For

• Experience: 14+ years of product management experience in enterprise SaaS, with a demonstrated track record of taking an Agentic product from 0-to-1 and scaling it in a production environment.
• AI/ML Expertise: Hands-on familiarity with LLM orchestration (e.g., LangChain, LlamaIndex), embedding models, vector databases, and designing autonomous agent loops (planning, tool use, reflection). You deeply understand the trade-offs between different foundation models and fine-tuning vs. RAG approaches. Strong working knowledge of predictive ML models and data pipelines….