engineer on Platform Portability
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Job description
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, youâll 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. Youâll work closely with our cloud partners on capabilities we need that donât exist yet, and with internal Compute, Inference, and Security teams to make âwhich cloud is this running on?â 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 youâll 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 Anthropicâs systems run on any cloud, and they have to hold up at the scale of frontier model inference. Youâll design and build those abstractions, plus the tooling that lets internal teams provision, configure, and operate services across clouds through one consistent interface. Youâll 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. Youâll own that delivery end to end, including the build, release, and validation pipelines behind it. Youâll 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, youâll shape how the rest of Anthropic builds for multiple clouds. Youâll 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. Youâll also take your turn in the on-call rotation, and youâll design the postmortems, runbooks, and incident response that help us never fail the same way twice.
Requirements
- 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), Minimum education: Bachelorâs 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.
Benefits & conditions
- 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 Anthropicâs 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 roleâs On Target Earnings (âOTEâ) 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, 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 Candidatesâ AI Usage: Learn about our policy for using AI in our application process.
About the company
Anthropicâs 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., 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. Weâre 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.
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