Director, Agentforce Engineering

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Software Engineering Job Details About Salesforce 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.

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. We are looking for a technical leader who understands that building an AI agent is only 10% of the work—the real engineering challenge is measuring it. We need a thought leader who can solve the "problem nobody talks about": evaluating non-deterministic agentic systems in production.

You will lead the team responsible for defining what "good" looks like for agents, moving beyond basic accuracy to rigorous evals that bridge agent spec’s to business outcomes. You will thread together Applied Science (defining metrics, curation of golden datasets, establishing ground truth) and Product Engineering (shipping software) 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: Lead as an expert on building Agents and deliver features that measure performance and accuracy of AI Agents.

You are a builder and are a subject matter expert on agentic evals 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 an Engineering leaders with deep technical expertise who operates with empathy and collaboration 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 Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do your best . Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love.

Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. Accommodations If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form . Posting Statement Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment.

What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination.

Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey.

It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program.

More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $197,300 - $313,700 annually.

In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $237,700 - $334,700 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.