Anthropic
DevOps / AgentOps Engineer, GTM Systems
$320K–$405K
San Francisco, CA +1 · Full-time · Posted Aug 19, 2026
- Location
- San Francisco, CA
San Francisco, California, United States - Experience
- Years of experience correlate with internal job-level requirements; no specific number stated.
- Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience; relevant field of study demonstrated through coursework, training, or professional experience.
- Visa sponsorship
- Visa sponsorship is available, but not for every role or candidate; the company says it will make every reasonable effort to obtain a visa after an offer.
About the job
Build and operate an AI-first CI/CD and agent-operations pipeline for Salesforce and internal applications, with governed release, approval, audit, and rollback processes.
What you'll do
- Design and run release pipelines across branching, validation, deployment, and rollback, with agentic, human-in-the-loop, and AI-assisted workflows.
- Define agent permissions and sandboxing, approval gates, environment and secrets management, observability, and rollback controls.
- Produce audit evidence and track pipeline performance; help engineers adopt and improve the pipeline.
What they ask for
- Have built and operated a team CI/CD pipeline, including branching, merge gating, and rollback.
- Hands-on Salesforce deployment experience or experience with a comparable enterprise platform.
- Fluency with AI coding tools and agentic workflows, including judgment about human review and agent boundaries.
- Experience with GitHub Actions or a comparable CI system, infrastructure as code, and scripting.
Nice to have
- Shipped agents or automation inside a production system of record, or operated under SOX or a similar audit regime.
- Experience with Salesforce DevOps tooling, governed-pipeline migrations, or approval workflows in Slack or a comparable tool.
Pay
$320,000 — $405,000 USD (base salary)
Tools
Salesforce, GitHub Actions, Gearset, Copado, sfdx, Slack
AI focus
Build an AI-first release pipeline with agentic, human-in-the-loop, and AI-assisted lanes; define agents’ scope, tools, permissions, sandboxing, and escalation boundaries.
Model-written summary · the original posting is authoritative