Director, Agentforce Testing Center Engineering

Opportunity Description

We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place.

Responsibilities

Build the "Evaluation Core" :

Lead the engineering of a scalable evaluation platform that runs in parallel with agent execution.

Thread Science & Engineering :

Operationalize applied science by turning theoretical benchmarks into production regression tests and bring about a discipline of eval driven development.

Thought Leadership :

Act as the internal SME for AI testing. Educate cross-functional partners (Product, UX, ML) on the difference between stochastic AI behavior and traditional deterministic software.

You are an Engineering leader who can lead the group through technical leadership, process management, maintain a good discipline of high quality code delivery aided with AI tools as necessary.

You are a People leader who ensures teams have clear priorities and adequate resources. You are a multiplier and have a passion for team and team members’ success providing technical guidance, career development, and mentoring.

Required Skills

Specialized Agent Evaluation Experience :

You have specific experience building evaluation harnesses for LLMs or Agents.

Applied Science & Engineering Hybrid :

You have a track record of managing "Research Engineering" or "Applied Science" teams where you had to operationalize vague scientific goals into shipping code. You are comfortable curating "Golden Sets" of data and building custom benchmarks from scratch.

Deep Knowledge of Eval Methodologies :

You are fluent in modern evaluation techniques, including :

LLM-as-a-Judge : Validating judges against human ground truth to prevent self-bias.

Behavioral Analysis : Evaluating how an agent thinks (Reasoning Traces / Chain of Thought), not just the final output.

Production-Grade AI Experience :

You have shipped AI products where you had to manage real-world constraints like token budgets, inference latency, and cost-normalized accuracy. Pragmatic orientation to building ML solutions that work in production at scale.

Familiarity with academic and industry benchmarks and their limitations in a business environment.

Experience building simulation environments (mock APIs, virtual users) to stress-test agents safely before deployment.

Experience with Data engineering, specifically around data acquisition, creating data pipelines, metric measurement, and analysis.

Experience owning highly available services and putting processes in place to maintain uptime.

Prior experience working with global teams.

Strong verbal and written communication skills, organizational and time management skills.

Advanced degree in Computer Science, Machine Learning, or related field with a focus on system evaluation or reliability.

#LI-Y

#J-18808-Ljbffr