Sr. Director, Responsible AI Science and Engineering

Salesforce•San Francisco, CA

1d•Hybrid

About The Position

Salesforce's Office of Ethical and Humane Use seeks a Sr. Director of Science and Engineering to lead our Responsible AI efforts in technical testing, evaluation, data science, and engineering. This is a senior technical leadership role tasked with transforming our RAI practice from manual expert reviews to operating scalable, AI-powered automated systems. You will own the technical architecture, scientific rationale, and operational scaling of our RAI systems, ensuring "trustworthy by default" standards across the enterprise.

Requirements

10+ years in software engineering and/or AI research, with a proven ability to build production-scale systems.
Hands-on proficiency in Python, SQL, CI/CD pipelines, and AI powered coding tools (e.g., Claude Code, Cursor).
Relevant applied knowledge of Data Science.
Experience building LLM-powered systems (agent frameworks, RAG, multi-model orchestration) and deep knowledge of modern AI architectures.
Proven track record in evaluation science, adversarial testing (red teaming), and designing systematic defenses against bias, hallucination, and other RAI risks.
A related technical degree required.
5+ years managing technical teams (engineers, researchers, data scientists).
Strong performance management and operational excellence.
Demonstrated ability to translate complex technical/ethical narratives into strategic business goals for executive stakeholders.
Comfort charting direction in high-ambiguity environments, using data to make pragmatic tradeoffs between ambition and deliverability.

Responsibilities

Define the Technical North Star: Develop the 18-24 month roadmap for moving from manual ethics test reviews to automated, AI-powered testing.
Architect Production Systems: Build robust infrastructure (e.g., automated intake pipelines, LLM-judge patterns, LLM Council approaches) that can handle Salesforce-scale traffic.
Set Scientific Rigor: Establish the research foundations, evaluation metrics, and technical logic for how we test and align AI systems.
Influence Cross-Functional Strategy: Partner with technical and product teams to embed RAI into the development lifecycle across business units.
People Leadership: Act as a "player-coach," providing technical mentorship, managing performance, and unblocking complex challenges in study design, data analysis, and software engineering.