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Anthropic

Staff+ Software Engineer, Deployment

Anthropic is hiring a Staff+ Software Engineer, Deployment in San Francisco, Seattle and New York, United States. It pays $405k-$485k a year and Level rates it ; you can apply on Anthropic.

Level's read on this job

  • On Level's scale, this software engineer role is Little AI ●○○○: aI is not part of the work.
  • The listed pay starts 143% above the typical software engineer posting on Level.
  • The posting allows some remote work.
  • Anthropic mentions visa sponsorship in this posting.
  • Tools and skills the posting cites include AI agents, AI safety and AI research.

AI in this role

ai-agentsai-safetyai-research

About Anthropic

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.

About the role

Every change to Anthropic's software has to reach production somehow: new code, runtime configuration, feature flags, infrastructure changes. Our team builds the systems those changes travel through. Our mission is to give every team at Anthropic a fast, safe, and predictable path from change to production.

We sit within Anthropic's Infrastructure organization and own pipelines, staged rollouts, health-gated promotion, and rollback, along with runtime configuration, feature flags, and the systems that deliver code and artifacts to machines across a very large fleet. You'll own a meaningful part of this end to end, from design through operating it in production.

If you want your work to shape how fast and how safely Anthropic ships, this could be a great fit.

Key responsibilities

  • Set technical direction for major parts of the deployment platform and own them end to end: design, implementation, and operations
  • Build rollout safety into the platform, including progressive delivery, health-gated promotion, automatic pause and rollback, and deploy controls that teams manage themselves
  • Design APIs and abstractions that work equally well for engineers and for AI agents
  • Extend the platform to new workload types and runtimes, from Kubernetes to serverless and edge platforms
  • Build and operate runtime configuration and feature flag systems with validation, gradual rollout, and fast rollback
  • Build infrastructure-as-code workflows that many teams rely on for safe, routine changes
  • Scale artifact distribution so code and configuration reach machines quickly and efficiently
  • Partner with Security so that the path to production is secure by default, with verifiable builds, least-privilege access, and auditable changes
  • Work directly with teams across Anthropic to understand their deployment needs and bring their workloads onto the platform
  • Take part in on-call and incident response, and turn what you learn into guardrails that prevent the same problem from recurring

Minimum qualifications

  • Proficiency in at least one backend or systems programming language, such as Rust, Go, C++, or Java
  • Experience leading the design, building, and operation of distributed systems or infrastructure in production, including technical direction across teams
  • Experience with cloud infrastructure and containerized workloads, such as Kubernetes on AWS or GCP
  • Strong written and verbal communication skills

Preferred qualifications

  • Experience building deployment, release, or change management systems at large scale
  • Experience with production on-call and incident response
  • Experience with Rust in production
  • Experience with progressive delivery and GitOps tooling, such as Argo CD or Argo Rollouts
  • Deep knowledge of Kubernetes, including controllers and operators
  • Experience with Terraform or other infrastructure-as-code systems at scale, including state management and locking
  • Experience building feature flag, experimentation, or dynamic configuration systems
  • Experience with artifact or package distribution, such as OCI registries, Nix, or content-addressed storage
  • Experience with software supply chain security, such as signed build provenance
  • Experience building high-throughput workflow engines or control planes backed by relational databases
  • Experience building internal developer platforms and leading adoption across many teams
  • Experience using AI agents in your own engineering work, or building systems that agents operate

Representative projects

  • Build operator controls for progressive rollouts, including pause and resume that preserve rollout state
  • Design a deployment engine built on fine-grained targets and their dependencies, so each change rolls out exactly where it needs to
  • Build cluster-health-aware rollouts that steer around unhealthy clusters
  • Add a new workload type to the platform, including its rollout, verification, and rollback behavior
  • Design a deployment control plane that handles sharp bursts of agent-driven traffic
  • Design a distribution system that delivers configuration and artifacts to every machine in the fleet as demand grows

The annual compensation range for this role is listed below. 

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary:$405,000—$485,000 USD

Logistics

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.

How we're different

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.

Come work with us!

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.

How we rate this

Staff+ Software Engineer, Deployment at Anthropic rates 23 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsAI SafetyAI Research

Also common in software engineer jobs at this level

Pay

This job starts at
$405k
Typical software engineer job
$167k

This posting starts 143% above the typical software engineer job. See software engineer jobs

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. How do you think about the risk of an AI system in this kind of role failing silently?
  3. Tell me about a research question you investigated. What did you find?

Adapt your resume

  • List these exact terms on your resume: AI agents, AI Safety, and AI Research. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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