Staff+ Software Engineer, Platform Portability
Anthropic is hiring a Staff+ Software Engineer, Platform Portability in San Francisco, New York and Seattle, United States. It pays $405k-$485k a year and Level rates it ; you can apply on Anthropic.
Level's read on this job
- Level rates this software engineer role Builds AI ●●●●: the job is building AI systems.
- Pay on this posting starts 141% higher than the typical software engineer posting on Level.
- Some of the work can be done remotely, according to the posting.
- The posting mentions visa sponsorship.
- The posting mentions AWS, Google Cloud and Kubernetes among its tools and skills.
AI in this role
Design and build provider-agnostic infrastructure abstractions and deployment pipelines to scale Anthropic's AI model inference across multiple clouds.
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
Anthropic trains and serves Claude across multiple cloud providers and accelerator platforms. The Platform Portability team owns the abstractions, tooling, and deployment infrastructure that make this possible without every engineering and research team needing to become experts in different clouds.
As an engineer on Platform Portability, you'll design and build the systems that let us bring up new capacity, ship our platform to cloud provider platforms & marketplaces, and move workloads between providers with confidence. You'll work closely with our cloud partners on capabilities we need that don't exist yet, and with internal Compute, Inference, and Security teams to make "which cloud is this running on?" a question most engineers at Anthropic never have to ask. Your work directly determines how quickly and reliably we can put safe, frontier AI in front of users — wherever they are.
What you'll do
Our work splits into two workstreams, and we need your help across both.
Portable infrastructure. We build the provider-agnostic abstractions for storage, messaging, and connectivity that let Anthropic's systems run on any cloud, and they have to hold up at the scale of frontier model inference. You'll design and build those abstractions, plus the tooling that lets internal teams provision, configure, and operate services across clouds through one consistent interface. You'll also hunt down the provider-specific assumptions hiding in our codebase and set the patterns that keep new ones from creeping in.
Claude on partner clouds. We ship Claude onto third-party cloud platforms, and every launch has to be repeatable. You'll own that delivery end to end, including the build, release, and validation pipelines behind it. You'll work directly with engineering teams at our cloud partners and internal infrastructure stakeholders to land the features we need, debug platform issues, and influence their roadmaps. Expect to go deep on native integrations with each provider, and to do the cross-cutting work that keeps our platform consistent across all of them.
Across both, you'll shape how the rest of Anthropic builds for multiple clouds. You'll review designs with cloud-portability implications, mentor engineers across the org on multi-cloud patterns, and bring internal stakeholders into alignment through clear writing and conversation. You'll also take your turn in the on-call rotation, and you'll design the postmortems, runbooks, and incident response that help us never fail the same way twice.
You might be a good fit if you:
- Have a minimum of 8 years of practical experience building and operating production distributed systems
- Own large-scale infrastructure systems and lead ambiguous, cross-team technical projects from design through production
- Run the same production workload across multiple cloud providers, including the migration or abstraction work that made it possible
- Understand how cloud IAM models and networking primitives (VPC peering, private connectivity, service mesh) differ across providers
- Write production code in at least one general-purpose programming language (e.g., Python, Go, or Rust)
- Work confidently with Kubernetes and Infrastructure as Code (e.g., Terraform, Pulumi)
- Understand ML infrastructure and supporting interconnects
- Ship software through hyperscaler marketplaces or managed-model platforms
- Bring a background in security, compliance, or data residency for regulated or sovereign cloud environments
- Care about the societal impacts of your work and Anthropic's mission to build safe, beneficial AI
Deadline to apply: None. Applications will be reviewed on a rolling basis.
Location Preference: Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team.
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 USDLogistics
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, Platform Portability at Anthropic rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ 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
Pay
- This job starts at
- $405k
- Typical software engineer job
- $168k
This posting starts 141% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- How do you think about the risk of an AI system in this kind of role failing silently?
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where infrastructure was part of your work. What did you do?
- Tell me about a project where cloud computing was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Safety, AI Research, Distributed Systems, Infrastructure, and Cloud Computing. 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.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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