Principal AI Engineer

About the role

Agentforce is the future of AI, and you are the future of Salesforce. We are seeking a highly skilled AI Platform Engineer to play a pivotal role in building the next generation of our ML/AI platform.

Responsibilities

• Design and build agent harness infrastructure: the scaffolding that wraps LLM calls, manages tool use, handles retries, enforces policy, and feeds results back into iterative improvement loops.
• Implement agentic loop patterns with multi-turn reasoning, tool orchestration, memory management, and structured output handling as reusable platform primitives.
• Build the agent flywheel: automated pipelines that collect agent traces, surface regressions, route failures to evaluation, and close the loop from production signal back to prompt/model improvement.
• Own the end-to-end lifecycle from agent experiment to production deployment, including versioning, rollout controls, and rollback mechanisms.
• Work on systems that directly impact marketing, sales, service, and product growth verticals across the organization.

Requirements

• 9+ years as a Platform Engineer, ML Infrastructure Engineer, or Software Engineer.
• Demonstrated experience building agent harness infrastructure using agentic loops, tool orchestration, structured output handling, multi-turn conversation management.
• Strong understanding of sandboxing and safe agent execution like isolation patterns, tiered autonomy, blast radius controls.
• Strong Python engineering skills for building scalable tools, automation, and platform components.
• Deep expertise in AWS.
• Extensive experience with CI/CD tooling, especially GitHub Actions and ArgoCD.
• Experience with containerization (Docker) and orchestration (Kubernetes).
• Experience with AgentOps concepts and production.

Qualifications

• Strong problem-solving skills and ability to manage multiple priorities across a complex platform.
• Experience with Salesforce Ecosystem including Agentforce and Data360.
• Experience with unstructured databases (vector or graph databases) and RAG pipelines.
• Experience working with modern data platforms and real-time processing frameworks, including cloud data warehouses (e.g., snowflake), streaming technologies (e.g. kafka, flink).

Skills

• Python engineering skills for building scalable tools, automation, and platform components.
• Deep expertise in AWS.
• Extensive experience with CI/CD tooling, especially GitHub Actions and ArgoCD.
• Experience with containerization (Docker) and orchestration (Kubernetes).
• Experience with AgentOps concepts and production.

Benefits

At Salesforce, we offer 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.

Pay

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 - $344,700 annually.

Schedule

Full-time.