Sr. Director - AI Engineering

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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.

About the Role

Salesforce's AI Foundations team is foundational to enabling both traditional machine learning applications and AI agents at enterprise scale. This team empowers the Digital Enterprise Technology organization to build, deploy, evaluate, and operate trusted AI systems in days instead of months. As Senior Director of Engineering, you will provide unified technical leadership across the AI foundations platform stack-spanning ML infrastructure, agent lifecycle management, evaluation, observability, and governance. You will drive interoperability across platform components, operationalize a data mesh-oriented architecture, and ensure the platform delivers high reliability, strong security, and cost-efficient scalability. This role is central to aligning platform capabilities with strategic business priorities, enabling safe and rapid adoption of generative AI and predictive AI across the enterprise.

What You'll Do

• Lead the engineering of AI Foundations team that enables teams to build, deploy, evaluate, experiment on, monitor, and govern AI agents and ML models safely and at enterprise scale.
• Own three core platform areas
  
  • ML Platform & Developer Productivity (training, inference, environments, cost/perf)
  • Model & Agent Lifecycle & Governance (CI/CD, registries, lineage, access control)
  • Agent Observability, Evaluation & Reliability (quality, drift, experimentation)

• Make agent evaluation and experimentation default platform capabilities, ensuring every production agent and model ships with:
  
  • Offline evaluation (golden scenarios, regression suites)
  • Pre-deployment quality gates in CI/CD
  • Controlled experimentation (A/B tests, canaries, shadow traffic)
  • Continuous post-deployment monitoring
• Drive end-to-end observability across data pipelines, retrieval, model inference, tool execution, and agent outcomes, with clear SLIs/SLOs for quality, latency, reliability, and cost.
• Standardize ML and agent development workflows, reducing time-to-production and eliminating bespoke infrastructure across teams.
• Partner cross-functionally with Applied AI, Data Science, Product, Security, Legal, and Responsible AI to translate business and regulatory requirements into enforceable engineering systems.
• Build and lead a high-performing organization of engineering managers and senior engineers, setting a strong technical bar and culture of operational excellence.

Required Skills

• 15+ years of engineering experience, with 7+ years leading platform or infrastructure teams in ML, data, or AI-heavy environments.
• A master's or Ph.D. degree in computer science, machine learning, artificial intelligence, or equivalent industry experience.
• Proven experience with ML and platform infrastructure, including Kubernetes-based systems, CI/CD, distributed systems, and observability stacks (metrics, logs, tracing).
• Expertise in generative AI, ML algorithms, and frameworks such as Hugging Face, Tensorflow, PyTorch, etc.
• Experience with cloud platforms (e.g., AWS, Google Cloud Platform) and distributed computing frameworks (e.g., Spark, Hadoop).
• Hands-on familiarity with experimentation frameworks, such as A/B testing, canaries, and shadow deployments, and integrating experiments into ML/agent pipelines.
• Experience building evaluation systems for models and agents, including offline tests, regression suites, online monitoring, and LLM-as-a-Judge-style approaches.
• Strong background in AI agents and LLM systems, including tool use, multi-step workflows, RAG, prompt and policy management, and common agent failure modes.
• Experience with data and ML platforms (e.g., Snowflake-centric workflows, feature stores, training pipelines).

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

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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: 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 $239,500 - $365,200 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $263,200 - $401,400 annually.The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.