Senior Director, Agentic Transformation Lead

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Job Category:
Software Engineering

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.

Salesforce is moving toward a future where AI agents do the engineering work, and that change starts with how we build software for ourselves. This role leads the AI transformation of the organization that builds and runs Salesforce’s internal, employee‑facing technology – and in doing so, creates the playbook every CIO in our customer base will need next. Every enterprise we’re selling to will hit exactly what we’re hitting right now.

Pilots worked. Agents are ready. The factory floor wasn’t built for them. If we solve this operationally – with receipts – we own the playbook no competitor can replicate. We solve it for ourselves. Then we sell it for a decade. Most of our engineers already use AI tools every day. The job now is to turn that broad adoption into one coordinated, measurable effort: clear standards, consistent adoption, and productivity gains that are real and visible across the whole organization – running at agent speed, not human speed.

This is a senior leadership role that works largely through influence. You will partner across engineering, product, and design. Your impact comes from clarity, standards, and driving outcomes – not from managing a large headcount.

• Coordinate the AI effort. Bring the many separate AI and engineering initiatives across teams into one coordinated program. Reduce duplication, scale what works, and give the work a single, clear direction.
• Standards and quality. Own the standards for how teams build with AI, and the process for improving them. Define what good looks like, how work is reviewed, and how expectations rise as the tools mature. Refuse to accept output that doesn’t work beautifully for the end user.
• Tools and adoption. Choose the set of AI development tools the organization uses – Cursor, Claude, Agentforce, and what comes next – and define the level of adoption every team is expected to reach. Keep the organization current with the best tools available.
• Delivery and release. Remove the deployment, testing, and process bottlenecks that hold back the productivity AI makes possible. Modernize the path from idea to production so teams can ship in weeks, not quarters.
• Measurement. Measure how work moves from idea to production and how the tools are used. Build clear, role‑specific measures so impact is comparable across the org. Track what matters – frequency of ideas tested, outcomes learned, adoption – and avoid metrics that look impressive but don’t reflect real impact.
• Builder progression. Define and drive the system that makes every build compoundingly faster than the last: shared context files, command libraries, three‑model review workflows, and postmortem culture. The builders who win aren’t the ones who use AI – they’re the ones who’ve built the system around AI.
• Roles and ways of working. Define how engineering, product, and design roles change as agents take on more of the work, and shape the broader way the organization operates around it – including how we move toward a headless model where agents run the work and humans make the judgment calls.

• You ship, you don’t just coordinate. You have a working prototype in your hands before you have a deck. When a decision takes more than 48 hours, you shrink the question, test it, and get the data.
• Speed is your default operating mode. You think in…