Director, Software Engineering

The Team

Salesforce Database (SDB) underpins Salesforce's multi-tenant cloud platform. The SDB AI team develops shared AI foundations, tools, agents, and workflows for database engineering and operations. This work uses database-specific knowledge and production signals to improve software delivery, identify operational risks earlier, and automate tasks.

The Role

We are looking for a Director of Software Engineering to lead the SDB AI team by shaping strategy, setting direction and priorities, and leading engineering, delivery, and operations with a strong focus on business outcomes. The role requires experience managing and developing engineering teams, technical depth in AI, production operations, and the tradeoffs between long-term capabilities and near-term needs.

What You'll Do

• Shape the strategy and own end-to-end delivery for the SDB AI team, from technical roadmap and architecture decisions to execution and operational excellence.
• Lead and strengthen the team of AI engineers and data scientists as it scales: set goals and ownership, manage delivery and performance, remove obstacles, and develop technical leaders.
• Partner with database service owners, other stakeholders, and AI teams across Salesforce to translate business priorities into technical strategy and a roadmap. Prioritize work by expected business impact and define measurable outcomes.
• Guide technical decisions about agent context, model selection, tool design, and evaluation. Build on AI capabilities already available within Salesforce and develop database-specific tools where needed.
• Deliver production AI capabilities for database operations, including operational intelligence for proactive detection, investigation, security, and automation.
• Represent the team in architecture and planning forums, resolve cross-team dependencies, and communicate tradeoffs and progress to engineering leadership.

What We're Looking For

• 10+ years of software engineering experience, including 5+ years leading and developing engineering teams that deliver complex production systems.
• Proven track record of leading and scaling high-performing, diverse engineering teams, setting direction, making clear tradeoffs, and delivering production AI systems.
• Deep expertise in AI, including machine learning and agentic systems, and strong technical judgment in system design, reliability, and operational risk. Able to review architecture and implementation decisions with senior engineers and architects.
• Experience with large-scale databases and distributed systems, public cloud, and multi-tenant platforms.
• Excellent communication skills, strong people leadership, and the ability to develop talent through direct feedback and coaching.
• A degree in computer science or a related field, or equivalent practical experience.