Technical Product Manager (Remote)
Salesforce
- Location
- California - San Francisco
- Work model
- Remote
- Level
- Senior
- H-1B history
- 498 approvals (FY2023)
- Posted
- Aug 20, 2026
Skills
About this role
To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Software Engineering Job 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. Customer Engineering is Salesforce's zero-to-one product hardening and incubation function for Agentforce Service Cloud and emerging Salesforce products including ITSM and CCaaS. The team is being stood up now, in FY27, as a dedicated function. The mandate is simple: take a small portfolio of selected lighthouse enterprise customers, get Agentforce Service capabilities live in their production environments, and fix every blocker we find at the product level — not in bespoke workarounds. Every engagement makes the product harder and better. Field learnings feed directly into the Agentforce roadmap. This is a zero-to-one team. We are building the motion that scales to hundreds of customers. The people we hire now set the standard and the culture. We are currently hiring for a portfolio-level technical product manager who owns the Agentforce adoption program from zero to one thousand enterprise customers. They do not manage individual deployments — they manage the entire portfolio: tracking velocity, unblocking FDE/CSM/PS and partner teams, running the deployment playbook, and closing the loop between field signals and product action within a week. Think growth hacker with engineering depth and executive presence. In the external market this role is typically titled Technical Product Manager (TPM). We are seeking an operator with an engineering background who wakes up every morning asking one question: how many customers are live, and what is in the way?
Responsibilities
Run the program. Own the Agentforce adoption program for Service Cloud end-to-end — portfolio-level tracking, deployment velocity, blocker resolution, and go-live reporting across all lighthouse and scaled customers. Set the operating rhythm. Operate a high-touch, daily cadence with product, FDE, CSM, and PS teams for the first 100 customers; transition to a lighter-touch weekly/bi-weekly model as the program matures past 100. Close the feedback loop. Intake customer feedback from the field and close the loop with inbound product managers within a week. You are the fastest path from field signal to product action. Unblock at scale. Identify what is blocking FDE, CSM, PS, and partner teams from running the deployment playbook — and fix it. Enable, enable, enable. Own the playbook. Build and maintain the deployment playbook that the full Agentforce field ecosystem runs from. Own its accuracy and completeness. Track adoption. Carry the adoption metric. Know the number. Know the gap. Know the path. Communicate at every level. Summarise program status clearly for executive leadership and go deep with engineering when the problem demands it. You are comfortable in both rooms. Bridge field and product. Work closely with Agentforce product leadership to ensure that field-validated product requirements reach the right inbound PM with enough signal to act on.
Requirements
8+ years technical program management, product operations, or equivalent in enterprise AI/SaaS Engineering background — can get into the architecture of a problem and have credible conversations with the engineers fixing it Deep personal familiarity with AI and agentic