Director, Product Management , Agentic Optimization

Salesforce Salesforce · Enterprise · San Francisco, CA

Salesforce is seeking a Director of Product Management to own agentic analytics for their Agentforce platform. This role involves analyzing enterprise agent behavior in production, clustering failures, and providing recommendations for improvement. The candidate will own the roadmap, user experience, and go-to-market strategy, working closely with engineering, design, and customers. The role requires daily use of coding agents, experience building and evaluating agents, and a strong understanding of LLM orchestration, tool use, and evaluation frameworks.

What you'd actually do

  1. Set and own the roadmap, outcomes, and product strategy for agentic analytics — from current pilot through GA and beyond.
  2. Own the user experience. Partner with design to build an agent that customers trust and reach for, not one they tolerate.
  3. Own the go-to-market. Work with Enablement, Docs, Marketing, and Sales on positioning, launch, and adoption. Run tight feedback loops with design partners and early customers.
  4. Set and defend success metrics (pilot activation, failure-cluster coverage, recommendation acceptance, agent quality lift) and use them to make real trade-offs. Kill what isn't working.
  5. Prototype with coding agents to pressure-test ideas before writing a spec. A working demo beats a 10-page doc.

Skills

Required

  • Product management experience with a track record of shipping products for technical users
  • Coding-agent fluency: daily user of coding agents, experience building and shipping agents, understanding of LLM orchestration, tool use, evals
  • Applied depth in evaluation and agent quality: experience with evaluation frameworks, annotation flows, failure clustering, measuring agent improvement
  • Comfortable with ambiguity, biased for action
  • Strong written and verbal communication
  • Cross-functional operator
  • Customer empathy at scale

Nice to have

  • Engineering background or equivalent hands-on depth
  • Direct experience with the current agent-building and eval landscape

What the JD emphasized

  • Own the product end to end
  • Build, don't just describe
  • Run the customer program
  • Move fast and coordinate across the portfolio
  • Coding-agent fluency
  • Applied depth in evaluation and agent quality

Other signals

  • AI-powered agents
  • agentic analytics
  • measure, monitor, and improve agents in production
  • customer success
  • product management