Description

About the Role

We're looking for a Senior Member of Technical Staff (SMTS) to own the end-to-end data science and software systems that power predictive and agentic intelligence for Sales Cloud. You'll work at the intersection of cutting-edge AI and real-world sales outcomes — building models that help sellers close deals faster, understand pipeline risk, and take action with confidence.

This is a high-ownership, high-impact role. You'll independently design, train, and operationalize models in Model Builder, stand up rigorous evaluations for agentic workflows, and deliver explainable signals — from opportunity scoring to deal-risk insights — that sellers genuinely act on. You'll be the recognized SME in your domain, influencing product roadmaps and coaching junior engineers along the way.

About the Team

We're part of C360 Apps – Sales Cloud, building AI and data science applications used by Sales Cloud customers worldwide. Our work spans predictive ML, forecasting, and sales planning — all powered by Agentforce, Data Cloud (Data 360), Model Builder, and the latest LLM tooling. We sit at the frontier of intelligent, data-driven selling and are shaping what that looks like for the next generation of Salesforce products.

What You'll Do

Design, train, and deploy production ML models for core Sales Cloud use cases: opportunity scoring, deal-risk detection, and seller-facing explainable insights

Build and operationalize agentic workflows on Agentforce, including LLM-as-judge evaluation frameworks and agentic evaluation metrics

Partner closely with Product Management to help shape and drive the roadmap — bringing engineering perspective to prioritization and feasibility decisions

Explore and adopt new technologies: improved forecasting methods, RAG architectures, prompt tuning strategies, and emerging AI tooling

Mentor and coach junior engineers on the team

What We're Looking For

Essential:

Strong object-oriented programming skills in one or more of: Python, Java, JavaScript, C++, C#, Ruby (Python strongly preferred for ML work)

Solid experience with relational databases, SQL, PL/SQL, and schema design

Hands-on experience with both supervised and unsupervised machine learning

Experience building RAG applications and agentic workflows, including prompt tuning and optimization

Familiarity with LLM evaluation, LLM-as-a-judge patterns, and agentic evaluation metrics

Strong communication and collaboration skills — you can influence without authority and bring partners along

Nice to Have:

Experience with Agentforce, Data Cloud / Data 360, Model Builder, or Salesforce BDTs

Familiarity with the Salesforce core codebase