DevOps / AgentOps Engineer, GTM Systems

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

Go To Market ("GTM") Systems builds and runs the platform that Sales and contracting operate on, a production Salesforce org plus a growing portfolio of custom internal applications and agents. These systems process revenue-impacting transactions, guide critical business processes, and produce data the rest of the company runs on. Today the path from request, development, test, and pull request to production push is manual and slows the team down rather than speeding it up.

We are hiring a DevOps / AgentOps engineer to build and run that path. You will stand up and maintain an AI-first CI/CD pipeline covering both Salesforce and custom application code. This release pipeline will support three modes: fully agentic, human-in-the-loop, and AI-assisted. Anthropic is an unusual place to do this. Our own frontier models are part of the toolkit and the question we want you to answer is what a delivery system looks like when you design it for agents and humans working side by side rather than retrofitting agents into a pipeline built for humans alone.

You will work closely with a team of business systems analysts, software engineers, and integration engineers to develop the solution to accelerate their everyday work. The pipeline you build is the one path to production for a system under audit, so the guardrails, approvals, and audit trail are part of the product, not an afterthought.

• →Design, build, and operate the CI/CD pipeline for a production Salesforce org and a portfolio of custom internal applications, from branching and validation through deploy and rollback
• →Define how a change is classified and routed into an agentic, human-in-the-loop, or AI-assisted lane, what gates each lane passes through, and how a change escalates between lanes when validation fails or risk changes
• →Build the agent operations layer: what agents are scoped to do in the pipeline, what tools and permissions they hold, how they are sandboxed differently for Salesforce and custom-app work, and what they are not trusted to do unsupervised
• →Implement approval workflows that keep PR review and business sign-off as distinct gates, with clear rules for which changes need which, who is asked, and what evidence they see
• →Own environment strategy, secrets handling, deploy observability, and kill-switch and rollback mechanics across all three lanes
• →Produce the audit trail and evidence a SOX-scoped platform needs
• →Measure and report on the pipeline itself: lead time, failure rate, share of work moving through each lane, and where humans are still doing work an agent should be doing
• →Pair with engineers on the team as they move onto the pipeline, and turn what you learn from them into better defaults

• Have built and run a CI/CD pipeline for a team, including the branching model, merge gating, and rollback path, and can explain the choices you made and what you would change
• Have hands-on experience with Salesforce deployment mechanics (metadata API, source-tracked development, org-to-org promotion) or a comparable enterprise platform
• Work fluently with AI coding tools and agentic workflows, and have opinions about which kinds of engineering work belong in the hands of an agent, which need a human review, and where the boundaries are
• Design for the failure case: you think about blast radius, sandboxing, permissions, and what happens when an automated change is wrong before you think about the happy path
• Are comfortable working across GitHub Actions or a comparable CI system, infrastructure as code, and the scripting needed to glue platforms together
• Write clear design documents and can defend a design to engineers, business approvers, and auditors in language each of them will accept

• Have shipped agents or automation that operate inside a production system of record, and have dealt with what happens when they misbehave
• Have operated a platform under SOX or a similar audit regime and know what evidence a change-management control actually requires
• Have experience with Salesforce DevOps tooling (Gearset, Copado, sfdx-based pipelines) and know where those tools stop and custom work begins
• Have run a migration from ad hoc or manual deploys to a governed pipeline and can talk about how you kept a team shipping while you did it
• Have built approval or notification workflows in Slack or a comparable tool that people actually used

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.