Responsibilities:

• Maintain full ownership of pipeline generating activities in your sales territory
• Collaborate with sales teams to understand their needs and optimize lead handoff processes
• Manage and prioritize a high volume of inbound leads
• Conduct initial qualifications for high-potential leads
• Outbound against strategic prospects to generate high-intent opportunities with Startup and Enterprise teams
• Support the development and execution of strategic outbound initiatives
• Provide data-driven insights to inform sales strategies and resource allocation
• Continuously refine processes to improve efficiency and effectiveness

You may be a good fit if you have:

• 3+ years of experience in a fast-growing startup, preferably in lead management and project management roles or
• 3+ years of experience in finance & investment banking, consulting or software engineering
• Strong analytical skills with the ability to translate data into actionable insights
• Experience with Salesforce, HubSpot, and SQL (preferred)
• Excellent communication and interpersonal skills
• Ability to work in a fast-paced, dynamic environment
• Passion for AI/ML and understanding of API-first or consumption-based business models
• Bachelor's degree in Business, Marketing, Computer Science, or related field

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

About the role

Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand.

Cluster Infra owns the full lifecycle of compute clusters at Anthropic. We build agent-driven automation for cluster provisioning and lifecycle management across all major cloud providers and our own datacenters. Our systems stand up clusters that are interconnected with high bandwidth, secure-by-default, and able to automatically drain and recover in response to failure. As a Staff engineer on this team, you'll set the technical direction for how Anthropic brings compute online - at a moment when the scale of that compute is growing faster than at almost any company in the world.

Key responsibilities

• Own the technical strategy and roadmap for agent-driven cluster lifecycle management - provisioning, updates and decommissioning
• Partner across teams to ensure new compute capacity is ingested on time
• Align with partner teams on physical build-out and leverage cloud solutions to deliver high-bandwidth inter-cluster connectivity
• Collaborate with security owners to ensure clusters are provisioned secure-by-default
• Define and drive strategy on cluster scalability, homogeneity and fault tolerance
• Work closely with cloud providers and internal research, inference and product teams to shape long-term compute, data, and infrastructure strategy
• Establish and evolve operational-excellence practices: incident response, postmortem culture and on-call health
• Support the growth of engineers around you through technical mentorship and coaching

Minimum qualifications

• Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure)
• Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform.
• Track record of leading complex, multi-quarter technical initiatives spanning multiple teams or systems
• Ability to build alignment across senior stakeholders and communicate effectively at all levels

Preferred qualifications

• 8+ years of software engineering experience, including time as a technical lead setting direction for a team
• Experience operating large-scale compute infrastructure at hyperscale (100+ clusters, 10K+ nodes)
• Depth in one or more of: Kubernetes internals, cluster provisioning and management systems, cluster orchestration systems (Mesos, Borg-like)
• Experience with cloud networking: VPC design and peering, Shared VPC/Transit Gateway, Cloud Interconnect/Direct Connect, Cloud NAT, cross-cloud private connectivity, BGP and route control, edge load balancing and DDoS mitigation (Cloud Armor / AWS Shield)
• Experience with cluster and host networking: CNI (Cilium), eBPF, NetworkPolicy, multi-NIC, sFlow, service mesh (Istio/Envoy/Linkerd, mTLS)
• Experience with cluster security: pod security standards and admission control, RBAC and least-privilege IAM, node and container hardening, supply-chain/image provenance
• Deep experience with infrastructure-as-code (Terraform, Atlantis), workflow orchestration (Temporal, Argo Workflows)
• Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software systems

About the role

We are seeking an Operations Manager to build and lead a new pillar of our Platform Operations function: Community Operations & Executive Escalations. This role will stand up the team, processes, and infrastructure that protect Anthropic's reputation when high-stakes user issues surface on social media or arrive through executive channels. You'll own end-to-end escalation management - detection, triage, incident coordination, and resolution- across two distinct but related workstreams: brand-impacting conversations on public social channels and high-sensitivity inbound from Anthropic employees on behalf of users. The ideal candidate combines calm-under-fire incident judgment with the operational rigor to build durable systems.

Responsibilities:

• Hire, lead, and develop a high-performing team of Community Operations specialists, covering detection through resolution
• Build the function from zero: stand up social listening infrastructure, define escalation criteria and severity tiers, author the incident management SOP, and establish coverage hours and on-call schedules
• Own social monitoring across public channels - triaging brand mentions and running escalations to resolution
• Own executive escalations end to end: receive inbound from Anthropic executives on behalf of users, lead your team in quarterbacking investigation and coordinate remediation across partner teams
• Serve as the central coordination point during live escalations and drive public/private response decisions to closure
• Build clear operating models with cross-functional teams so every stakeholder knows exactly where to send an escalation and what happens next
• Define and report on success metrics (time to triage, time to resolution, escalation volume by source) and run post-incident reviews that feed learnings back into criteria and process
• Develop response templates and playbooks for common scenarios so the team can move fast without sacrificing quality or judgment
• Provide thoughtful coaching and feedback to your direct reports, and partner with them on their career development and growth

You may be a good fit if you have:

• 8+ years of experience in community operations, escalations management, or a related field - ideally in a consumer or developer platform environment
• 5+ years of people management experience, preferably in a fast-growing technology company
• Direct experience running incident or escalation workflows: you've been the person managing the channel, paging the on-call, and writing the post-incident report
• Familiarity with social listening tooling and the dynamics of how issues spread across public social platforms
• Excellent judgment under pressure in reading a fast-moving situation, separating signal from noise, and making calls with incomplete information
• Proven track record of building operational programs from 0 to 1: writing the SOP, defining the criteria, standing up the tooling, and then iterating as reality breaks your assumptions
• Strong cross-functional influence and ability to align teams around a shared plan in real time, even when incentives differ
• Clear, concise written communication - you can brief an executive in three sentences and document an incident so the next person can learn from it
• Comfort with ambiguity and a bias toward action; this team doesn't exist yet and you'll be defining what good looks like
• Excitement about protecting Anthropic's reputation and relationships at a moment when public attention on AI has never been higher

Responsibilities:

• Designing and implementing from scratch new information architecture strategies
• Performing finetuning and reinforcement learning to teach language models how to interact with new information architectures
• Building “hard” knowledge base eval sets to help identify failure modes of how language models work with external data
• Designing and evaluating advanced agentic search capabilities.

You may be a good fit if you:

• Are a very experienced Python programmer who can quickly produce reliable, high quality code that your teammates love using
• Have good machine learning research experience 
• Have experience developing software that utilizes Large Language Models such as Claude
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to partner with world-class ML researchers to develop new LLM capabilities
• Care about the societal impacts of your work
• Have clear written and verbal communication

Strong candidates will also have experience with:

• Collaborating with product teams to quickly prototype and deliver innovative solutions
• Building complex agentic systems that utilize LLMs
• Developing scalable distributed information retrieval systems, such as search engines, knowledge graphs, RAG, indexing, ranking, query understanding, and distributed data processing

About the Role:

Anthropic launches products at lightning speed and many of them grow at an unprecedented pace, too. For no product is this more true than Claude Code,  the fastest-growing software product in history. That said, speed of adoption is not the same as depth of adoption. We’re building a team of Technical Specialists to drive meaningful adoption breadth and depth in our most strategic customers. We’ll do this through delivery of high-quality technical engagement and enablement in the customer’s ~ 90 days before and after contract signature.  

As a Technical Specialist, you’ll largely engage with customers post-sale. Once an account’s implementation set-up is complete, you’ll convert bottom-up developer passion into org-wide meaningful adoption through bespoke enablement tailored to the customer's stack, repos, and workflows and focused upon deep adoption of proprietary Claude capabilities, which we know drive stickiness.

You'll also engage in strategic pilots before signature — partnering with Sales, Applied AI, and the customer's engineering leads to scope the pilot, run the enablement, and instrument the success criteria that close the deal. Carrying that context from pilot into post-sale is what makes adoption stick.

This is not a technical implementation role — that work sits with our Implementation Specialists. You'll spend your time in front of developers launching Claude Code, department leaders adopting Cowork, on stage at customer events and Anthropic builder summits, and in Claude Code and Cowork, building the demo apps and reference implementations that prove what's possible.

You’re the kind of person engineers want to grab coffee with after your workshops — credible because you can open a terminal in the meeting and actually drive the tool, exciting because you've thought hard about how agentic AI changes how software gets built, and useful because you can answer the next three questions a senior platform engineer is about to ask about security, scale, or agent behavior.

What You'll Do:

Drive end-user excitement inside enterprise accounts (primary focus)

• Design and deliver customer-specific enablement programs — workshops, office hours, "build your first agent" labs, role-based curricula for engineering, data, platform, security, and knowledge-worker audiences

• Drive deep adoption of proprietary Claude Code capabilities that make our tools sticky (subagents, hooks, MCP servers, headless mode, managed settings) tailored to the customer's stack, repos, and actual workflows (CI/CD, IDE integration, source control, secure coding, agentic pipelines)

• Enable and excite champions and AI Center of Excellence leads inside customer orgs, arming them to scale the motion without you in the room

Support strategic pilots with pre-sales technical enablement

• Partner with Account Executives, Applied AI, and customer engineering leads on pilots for strategic accounts

• Carry pilot context into post-sale engagement so the customer’s experience is seamless and deeply focused upon their unique needs

Run hackathons and builder events that create lasting momentum

• Design, scope, and run on-site and virtual hackathons inside customer organizations

• Bring the playbook: themes, judging rubrics, starter kits, prize structures, post-event follow-through that turns hackathon prototypes into shipped products

• Partner with Anthropic Marketing and Events to amplify the best work from customer hackathons externally where appropriate

Build the demos, content, and reference implementations that sell themselves

• Build production-quality demo apps, reference architectures, and code samples on the Claude Developer Platform, Claude Code, and Claude Enterprise (including Cowork) — using the products daily yourself as core infrastructure

• Create technical content — tutorials, blog posts, recorded walkthroughs, internal "cookbooks" — tailored to enterprise developer audiences and their real workflows (CI/CD, IDE integration, secure coding, agentic workflows, multi-agent orchestration)

• Translate new product capabilities into field-ready content within days of release

Be the trusted technical voice in front of customers

• Deliver keynotes, technical talks, and live-coded demos at customer all-hands, internal AI summits, and Anthropic-hosted builder events

• Run "ask me anything" sessions with customer engineering organizations and engage credibly on architecture, prompting, agent design, evaluation, developer workflow, and the honest limitations of where AI coding tools are today

• Represent Anthropic with our customers' engineering communities and, where appropriate, the broader developer ecosystem

Partner across GTM and back to product

• Partner closely with Sales, Applied AI, and Customer Success to sequence engagements that compound (pilot → activation → adoption → value)

• Bring back signal from the field: what enterprise developers are asking for, where they're getting stuck, what would unlock the next leap in adoption, and feed it to Product and Engineering

• Contribute to the playbook: capture what works in pilots and post-sale enablement, share with peers, raise the floor across the team

You may be a good fit if you have:

• 3–7+ years in a customer-facing technical role — Solutions Architecture, sales engineering, developer relations, or technical consulting.

• You build, and you build with our products. You use Claude Code, the Claude Developer Platform, and Cowork as core infrastructure in your own work. You can ship a working demo over a weekend, steer an agent through a non-trivial task live, and have opinions about what's actually good.

• You can hold a room of engineers. You've delivered technical talks, workshops, or training to engineering audiences — platform engineers, ML/AI teams, security-minded enterprise architects — and you know the difference between a session that creates awareness and one that creates champions.

• Builder credibility. A career that includes meaningful time as a software engineer, founder, solutions engineer, developer advocate, or Solutions Architect. You've shipped code that other people have depended on.

• Pilot and evaluation experience. You've supported technical evaluations or pilots in an enterprise setting — scoping, enablement, handling the security/admin/scale conversations without escalating everything to product.

• Strong written and visual communication. Tutorials, decks, code comments, and Slack threads that people actually read.

• Project management instincts. You can run a multi-week activation plan — or a pilot against a defined success metric — without dropping the ball.

• Willingness to travel. Regular travel for on-site enablement, pilots, hackathons, and customer events. Some evenings and weekends around major events.

• Deep enthusiasm for AI with hands-on experience building with LLMs and an instinct for how this technology should be used responsibly inside large organizations.

About the role

Anthropic runs some of the largest Kubernetes clusters in the industry. We have fleets of hundreds of thousands of nodes across multiple cloud providers and datacenters to train, research, and serve frontier AI models. The Kubernetes Platform team owns the Kubernetes control plane that makes those clusters work.

We are operating at a scale where the defaults stop working. We own the scheduler and extend it to place topology-sensitive ML workloads across thousands of accelerators at once. We scale the control plane itself — apiserver, etcd, controllers — so it stays responsive as object counts and node counts grow by orders of magnitude. And we build the core cluster services every workload depends on, like service discovery, so they hold up under the same pressure.

We make sure the control plane is fast, correct, and always available. Your work will directly determine whether Anthropic can keep reliably and safely training frontier models as our compute footprint continues to grow.

Key responsibilities

• Own, operate, and extend the Kubernetes scheduler for Anthropic's accelerator fleets, including custom scheduling plugins and policies for gang scheduling, topology awareness, and preemption
• Scale the Kubernetes control plane (apiserver, etcd, controller-manager) to support clusters far beyond typical limits, and find the next bottleneck before it finds us
• Design, build, and operate core cluster services such as service discovery that every workload in the fleet depends on
• Build and maintain custom controllers, operators, and CRDs
• Partner with research, training, and inference to understand workload shapes and turn their requirements into platform capabilities
• Collaborate with cloud providers on required features and escalations
• Participate in on-call, lead incident response, and design processes (postmortems, runbooks, SLOs) that help the team avoid repeating failures

Minimum qualifications

• Significant software engineering experience building and operating production distributed systems
• Proficiency in at least one systems-appropriate language (e.g., Go, Python, Rust, or C++)
• Deep, hands-on Kubernetes experience (well beyond "user of”) into scheduler, controllers, apiserver, or operating large multi-tenant clusters
• Demonstrated ability to debug complex issues across the stack, from API behavior down to node and network-level root causes
• A track record of designing for reliability, correctness, and clear failure semantics in systems other engineers depend on
• Strong written and verbal communication; comfort building consensus with internal stakeholders

Preferred qualifications

• Experience with Kubernetes internals or contributions: kube-scheduler / scheduling framework, apiserver, etcd, client-go, controller-runtime, or similar
• Experience building or operating cluster schedulers or batch systems (e.g., Kueue, Volcano, Slurm, or in-house equivalents)
• Background scaling control planes or coordination systems (etcd, ZooKeeper, Consul, or large DNS/service-mesh deployments)
• Familiarity with ML infrastructure: GPUs, TPUs, or Trainium; gang scheduling; topology-aware placement; collective networking such as NCCL
• Experience with GCP and/or AWS, including GKE/EKS internals and Infrastructure as Code
• Low-level systems experience such as Linux kernel tuning, cgroups, or eBPF
• 8+ years of relevant industry experience, including time leading large, ambiguous infrastructure projects

About the Role

Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand.

Developer Productivity owns the end-to-end experience of how engineers and researchers at Anthropic develop, build, test, and ship code at scale — from the source control and language ecosystems that underpin our monorepo, to the build and CI infrastructure that keeps thousands of daily builds running reliably across multiple cloud providers, to the developer acceleration tooling that deeply integrates Claude into engineering workflows.

Team Matching: Team matching is determined after the interview process based on interview performance, interests, and business priorities. Please note we may also consider you for different Infrastructure teams. 

Responsibilities:

• Own the technical strategy and roadmap for your area, translating team-level goals into concrete execution plans
• Define infrastructure architecture, ensuring the hardest problems get solved — whether by you directly or by working through others
• Design and build scalable, reliable distributed infrastructure and shared libraries that support high-volume workloads across all engineering teams
• Own and evolve build environments, package management, and dependency systems to enable fast, reproducible builds
• Define and implement language ecosystem standards, tooling, and frameworks that drive developer productivity across research and production workloads

You may be a good fit if you:

• Have deep experience with build systems, CI/CD pipelines, and/or developer tooling in a large monorepo environment
• Have strong proficiency in Python, Rust and/or Go
• Are obsessed with developer productivity and reducing friction in the software development lifecycle
• Have experience with container orchestration and infrastructure at scale
• Have excellent communication skills and enjoy supporting internal partners to improve their development experience
• Are excited about designing foundational systems and are comfortable working independently on ambiguous, high-impact technical challenges

Strong candidates may have:

• 15+ years (not including internships or co-ops) of experience in a Software Engineer role, building and operating large-scale developer infrastructure
• 3+ years (not including internships or co-ops) of experience leading large scale complex projects or teams as a tech lead
• Experience with CI orchestration tools (Buildkite, Jenkins, GitHub Actions, or similar) and merge queue management at scale
• Experience building or operating remote build execution systems (Bazel Remote Execution API, BuildBarn, BuildBuddy, or similar)
• Experience with Nix/NixOS/Docker and managing large image / package sets at scale
• Experience building CLI tools, developer-facing services, and GitHub API and automation workflows

Deadline to apply: None. Applications will be reviewed on a rolling basis.

About the Role

Our mandate is to make inference deployment boring and unattended.

Anthropic serves Claude to millions of users across GPUs, TPUs, and Trainium — and every model update must reach production safely, quickly, and without disrupting service. We're building the systems that make inference deployment continuous and unattended.

As a Software Engineer on the Launch Engineering team, you'll design and build the deployment infrastructure that moves inference code from merge to production. This is a resource-constrained optimization problem at its core: validation and deployment consume the same accelerator chips that serve customer traffic — your deploys compete with live user requests for the same hardware. Every model brings different fleet sizes, startup times, and correctness requirements, so the system must adapt continuously. You'll build systems that navigate these constraints — orchestrating validation, scheduling deployments intelligently, and driving down cycle time from merge to production.

If you've built deployment systems at scale and gravitate toward the hardest problems at the intersection of automation and resource management, this team will give you an outsized scope to work on them.

Responsibilities

• Own deployment orchestration that continuously moves validated inference builds into production across GPU, TPU, and Trainium fleets, unattended under normal conditions
• Improve capacity-aware deployment scheduling to maximize deployment throughput against constrained accelerator budgets and variable fleet sizes
• Extend deployment observability — dashboards and tooling that answer "what code is running in production," "where is my commit," and "what validation passed for this deploy"
• Drive down cycle time from code merge to production with pipeline architectures that minimize serial dependencies and maximize parallelism
• Optimize fleet rollout strategies for large-scale deployments across thousands of GPU, TPU, and Trainium chips, minimizing disruption to serving capacity
• Evolve self-service model onboarding so that new models can be added to the continuous deployment pipeline without Launch Engineering involvement
• Partner across the Inference organization with teams owning validation, autoscaling, and model routing to integrate deployment automation with their systems

You May Be a Good Fit If You Have

• 5+ years of experience building deployment, release, or delivery infrastructure at scale
• Strong software engineering skills with experience designing systems that manage complex state machines and multi-stage pipelines
• Experience with deployment systems where resource constraints shape the design — whether that's fleet capacity, network bandwidth, hardware availability, or coordinated rollout windows
• A track record of building automation that measurably improves deployment velocity and reliability
• Proficiency with Kubernetes-based deployments, rolling update mechanics, and container orchestration
• Comfort working across the stack — from backend services and databases to CLI tools and web UIs
• Strong communication skills and the ability to work closely with oncall engineers, model teams, and infrastructure partners

Strong Candidates May Also Have

• Experience with ML inference or training infrastructure deployment, particularly across multiple accelerator types (GPU, TPU, Trainium)
• Background in capacity planning or resource-constrained scheduling (e.g., bin-packing, fleet management, job scheduling with hardware affinity)
• Experience with progressive delivery in systems with long validation cycles: canary/soak testing, blue-green deployments, traffic shifting, automated rollback
• Experience at companies with large-scale release engineering challenges (mobile release trains, monorepo deployments, multi-datacenter rollouts)
• Experience with Python and/or Rust in production systems

You may be a good fit if you:

• Have significant software engineering experience, particularly with distributed systems
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to learn more about machine learning systems and infrastructure
• Thrive in environments where technical excellence directly drives both business results and research breakthroughs
• Care about the societal impacts of your work

Strong candidates may also have experience with:

• High-performance, large-scale distributed systems
• Implementing and deploying machine learning systems at scale
• Load balancing, request routing, or traffic management systems
• LLM inference optimization, batching, and caching strategies
• Kubernetes and cloud infrastructure (AWS, GCP, Azure)
• Python or Rust

Representative projects:

• Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
• Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
• Building production-grade deployment pipelines for releasing new models to millions of users
• Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
• Contributing to new inference features (e.g., structured sampling, prompt caching)
• Supporting inference for new model architectures
• Analyzing observability data to tune performance based on real-world production workloads
• Managing multi-region deployments and geographic routing for global customers

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

About the Role

The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform—from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.

Our engineers are extremely high leverage: we simultaneously drive multiple major revenue streams while optimizing one of Anthropic's most precious resources—compute. As we expand to more cloud platforms, the complexity of managing inference efficiently across providers with different hardware, networking stacks, and operational models grows significantly. We need engineers who can navigate these platform differences, build robust abstractions that work across providers, and make smart infrastructure decisions that keep us cost-effective at massive scale.

Your work will increase the scale at which our services operate, accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms, and ensure our LLMs meet rigorous safety, performance, and security standards.

What You'll Do

• Design and build infrastructure that serves Claude across multiple CSPs, accounting for differences in compute hardware, networking, APIs, and operational models
• Collaborate with CSP partner engineering teams to resolve operational issues, influence provider roadmaps, and stand up end-to-end serving on new cloud platforms
• Design and evolve CI/CD automation systems, including validation and deployment pipelines, that reliably ship new model versions to millions of users across cloud platforms without regressions 
• Design interfaces and tooling abstractions across CSPs that enable cost-effective inference management, scale across providers, and reduce per-platform complexity
• Contribute to capacity planning and autoscaling strategies that dynamically match supply with demand across CSP validation and production workloads
• Optimize inference cost and performance across providers—designing workload placement and routing systems that direct requests to the most cost-effective accelerator and region
• Contribute to inference features that must work consistently across all platforms
• Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads

You May Be a Good Fit If You:

• Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
• Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code or container orchestration
• Have strong interest in inference
• Thrive in cross-functional collaboration with both internal teams and external partners
• Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
• Are highly autonomous and self-driven, taking ownership of problems end-to-end with a bias toward flexibility and high-impact work
• Pick up slack, even when it goes outside your job description

Strong Candidates May Also Have Experience With

• Direct experience working with CSP partner teams to scale infrastructure or products across multiple platforms, navigating differences in networking, security, privacy, billing, and managed service offerings
• A background in building platform-agnostic tooling or abstraction layers that work across cloud providers
• Hands-on experience with capacity management, cost optimization, or resource planning at scale across heterogeneous environments
• Strong familiarity with LLM inference optimization, batching, caching, and serving strategies
• Experience with Machine learning infrastructure including GPUs, TPUs, Trainium, or other AI accelerators
• Background designing and building CI/CD systems that automate deployment and validation across cloud environments
• Solid understanding of multi-region deployments, geographic routing, and global traffic management
• Proficiency in Python or Rust

About the Role

AIRE (AI Reliability Engineering) partners with teams across Anthropic to improve reliability across our most critical serving paths -- every hop from the SDK through our network, API layers, serving infrastructure, and accelerators and back. We jump into the trenches alongside partner teams to make the systems that deliver Claude more robust and resilient, be it during an incident or collaborating on projects. 

Reliability here is an emergent phenomenon that transcends any single team's boundaries, so someone has to zoom out and look at the whole picture. That's us -- and it means few teams at Anthropic offer this kind of dynamic, cross-cutting exposure to the systems that matter most.

Responsibilities:

• Develop appropriate Service Level Objectives for large language model serving systems, balancing availability and latency with development velocity
• Design and implement monitoring and observability systems across the token path
• Assist in the design and implementation of high-availability serving infrastructure across multiple regions and cloud provider
• Lead incident response for critical AI services, ensuring rapid recovery, thorough incident reviews, and systematic improvements
• Support the reliability of safeguard model serving -- critical for both site reliability and Anthropic's safety commitments.

You may be a good fit if you:

• Have strong distributed systems, infrastructure, or reliability backgrounds -- we're looking for reliability-minded software engineers and SREs
• Are curious and brave -- comfortable jumping into unfamiliar systems during an incident and helping drive resolution even when you don't have deep expertise yet
• Think holistically about how systems compose and where the seams are
• Can build lasting relationships across teams -- our engagement model depends on being welcomed as teammates, not outsiders with opinions
• Care about users and feel ownership over outcomes, even for systems you don't own
• Have excellent communication and collaboration skills -- you'll be partnering across the entire company
• Bring diverse experience -- the team's strength comes from people who've built product stacks, scaled databases, run massive distributed systems, and everything in between.

Strong candidates may also:

• Have been an SRE, Production Engineer, or in similar reliability-focused roles on large scale systems
• Have experience operating large-scale model serving or training infrastructure (>1000 GPUs)
• Have experience with one or more ML hardware accelerators (GPUs, TPUs, Trainium)
• Understand ML-specific networking optimizations like RDMA and InfiniBand
• Have expertise in AI-specific observability tools and frameworks
• Have experience with chaos engineering and systematic resilience testing
• Have contributed to open-source infrastructure or ML tooling.

About the UX research team

UX research at Anthropic is a small team with outsized leverage. We work across products used by millions of people—and on interactions that don't have established conventions yet.

We inform critical decisions through rigorous research, with stakeholders who eagerly incorporate findings into their work. Research has a seat at the table for product strategy, and we partner closely with design, product, and engineering. We combine qualitative and quantitative methods to understand user needs in a space that's evolving faster than anyone can track.

We move fast, favor impact over polish, and increasingly build our own tools—often with AI doing the heavy lifting—to do research at the speed this environment demands.

About this role

This is a senior individual-contributor role. You'll own research for a complex, fast-moving product area where the surface is expanding quickly and the most important user questions haven't been articulated yet, let alone answered.

You won't work from a fixed research roadmap. You'll prioritize constantly—making clear, well-informed bets about what to learn next, executing on them fast, and pivoting the moment the picture changes. Our product teams are deeply technical and move on instinct; your job is to make that instinct better-calibrated without slowing it down.

Roles here are fluid. On any given week you might be the researcher, the analyst, the one framing the next product bet, or the one building a prototype because that's the fastest way to find out.

Where this role lands depends on team needs and your strengths—we'll figure that out together.

Responsibilities

• Set the research agenda for a product area where the strategic questions are still fuzzy. Define what we need to learn, in what order, and why—then go learn it. Don't wait to be asked
• Design and run mixed-methods research at whatever fidelity the moment calls for. Some of it will be careful, foundational work the team references for a year. Some of it will be a finding you ship the same day the question came up
• Keep product teams close to users in a rigorous way—building the channels, cadence, and evidence base that make user reality hard to ignore
• Get hands-on with product data. Pull your own samples, build your own dashboards, instrument what's missing
• Prototype when prototyping is the fastest path to an answer—a research tool, a survey pipeline, a scrappy version of a feature to put in front of users
• Deeply leverage AI in how you work—using Claude to make yourself dramatically more efficient at analysis, synthesis, tooling, and everything in between
• Use what you study. Dogfood our products hard enough to develop your own informed opinions, and bring that texture into your research
• Anticipate where the product is heading before anyone asks. Show up with the user understanding the team is about to need
• Turn what you learn into recommendations confident enough to redirect a roadmap—including recommending we kill something that isn't working
• Build durable understanding, not just findings. The goal is that PMs, designers, and engineers internalize the user mental model well enough to make good calls when you're not in the room
• Develop new research methods when the existing playbook doesn't fit—particularly methods that use AI to do things that weren't possible before

Qualifications

• Industry UX research experience, including ownership of research strategy for a product or product area
• Track record of research that shifted product direction at the strategy level, not just the feature level
• Deep mixed-methods expertise—qualitative and quantitative
• Enough data fluency to use Claude to work directly with our data warehouse—pulling your own samples, writing your own queries, running your own analyses
• Demonstrated technical range: you've built research tooling, prototyped, scripted analyses, or otherwise shown you can keep up with very technical teams without translation overhead
• Advanced, hands-on use of AI in your own research workflow—you're already taking full advantage of its capabilities to enhance how you work
• Experience embedding with engineering-led product teams that ship fast, and earning influence in that environment
• Excellent storytelling, calibrated to audience. You can discuss a finding with an exec as effectively as with an engineer

About the Role

We are seeking a GRC Automation Lead to join our GRC organization and build the technical foundation for how we scale our risk and compliance programs. In this role, you will lead the team that designs and implements automated workflows, data pipelines, and integrations that transform manual compliance processes into scalable engineering systems. 

This is a greenfield opportunity to establish the team, architecture, and integrations that will define how we approach governance, risk, and compliance at Anthropic. The core challenge is a data problem: compliance information lives across dozens of systems—cloud infrastructure, identity providers, HR platforms, ticketing tools, code repositories—and your job is to design systems that bring it together, normalize it, and make it actionable. Success in this role comes from understanding how systems connect and how data flows between them, not from writing code yourself.

At Anthropic, you'll also have a unique advantage: the ability to design AI-powered workflows where Claude acts as an extension of your team, handling tasks that would traditionally require additional headcount or manual effort. You'll need ingenuity to identify where agentic AI can accelerate evidence collection, interpret unstructured data, triage compliance gaps, and augment human judgment in risk assessments. Working closely with Security, IT, and Engineering teams, you'll translate compliance and regulatory requirements into solutions that support audit programs including SOC 2, ISO, HIPAA, and FedRAMP, building systems that combine traditional automation with AI capabilities to achieve scale that wouldn't otherwise be possible.

Responsibilities: 

• Lead the team that establishes foundational GRC processes and architecture. Design and build automated workflows for risk management and compliance, creating scalable systems that enable continuous monitoring as Anthropic grows.
• Build data pipelines that aggregate risk, control, and asset information from across our technology stack. This means solving hard data integration problems: mapping disparate schemas, handling inconsistent data quality, and creating unified views of compliance posture through dashboards and reporting tools.
• Inform GRC platform strategy and implementation: in partnership with other programs, evaluate, select, and deploy tooling that meets our compliance requirements.
• Translate written policies and compliance requirements into policy-as-code—working with Engineering and Security teams to express requirements as enforceable rules, automated checks, and continuous validation rather than static documents.
• Establish feedback loops between policy and implementation: surface where technical controls diverge from written requirements, identify where policies need to evolve based on infrastructure realities, and ensure that compliance requirements are expressed in terms engineers can act on.
• Design and deploy agentic AI workflows that extend team capacity, using Claude to serve as a virtual GRC analyst to automate evidence analysis, monitor control effectiveness, draft audit responses, interpret policy documents, and handle other tasks that require reasoning over unstructured information.
• Design and maintain integrations connecting GRC tooling with cloud infrastructure, identity management systems, HRIS platforms, ticketing systems, version control, and CI/CD pipelines—working with engineers to implement integrations that enable automated evidence collection and continuous compliance validation.
• Build and lead an AI-forward GRC engineering function as we scale: hiring team members, establishing practices, and defining the technical roadmap for governance and compliance automation at Anthropic.

You may be a good fit if you:

• Have 12+ years of total experience and 3-4+ years of experience managing technical individual contributors or systems-focused teams, with a proven track record of building or scaling small teams (2-5 people) in security, compliance, automation, or operations functions.
• Are a systems thinker first. You understand how complex environments work: how data flows between systems, where integration points exist, what breaks when systems don't talk to each other. Your strength is designing the right architecture and environment for security monitoring, not necessarily implementing it yourself.
• Have 5+ years of experience designing automated workflows, data pipelines, or system integrations, whether through traditional development, low-code platforms, GRC tools, or process automation. We care about your ability to solve integration problems more than your programming language proficiency.
• Have a relentless focus on data integration: you understand how to pull data from multiple sources, normalize it, join it meaningfully, and surface insights. You're comfortable reasoning about messy, inconsistent data and designing systems that handle edge cases gracefully.
• Understand APIs and integration patterns: REST APIs, webhooks, authentication flows, polling vs. push architectures, and can evaluate systems based on how well they expose data and support automation.
• Can work independently with minimal guidance, taking ownership of complex problems from design through implementation while managing ambiguity inherent in early-stage programs.
• Have strong analytical and problem-solving skills with attention to detail necessary for compliance work, balanced with pragmatism about risk-based prioritization in fast-paced environments.

Strong candidates may have:

• Experience designing or implementing AI-powered automation, agentic workflows, or LLM-based tooling in operational contexts.
• Experience with GRC platforms such as ServiceNow GRC, Vanta, Drata, OneTrust, RSA Archer, or similar tools including configuration, customization, and integration capabilities
• Familiarity with scripting languages (Python or similar) for automation tasks, API interactions, and data transformation.
• Prior experience in high-growth startup environments demonstrating ability to build scalable processes and adapt quickly to changing requirements and priorities
• Familiarity with Infrastructure as Code tools (Terraform, CloudFormation, Ansible) and DevSecOps practices including CI/CD pipeline integration and policy-as-code implementations.
• Familiarity with cloud platforms (AWS, GCP, Azure) and an understanding of how compliance-relevant data can be extracted from their APIs and logging systems.

Deadline to apply: None, applications will be received on a rolling basis.

About the role

As a Product Manager for API Growth, you’ll drive growth for the Claude Platform (platform.claude.com) – the surface where developers and businesses build directly on Claude. Your efforts will span the entire funnel, driving growth of key API metrics across acquisition, activation, and monetization. You'll work closely with a cross-functional team of engineers, designers, marketers, and data scientists to develop and execute strategies that accelerate our growth while maintaining our commitment to safety and beneficial AI.

Responsibilities:

• Develop and execute a product strategy focused on driving Claude Platform growth metrics such as acquisition, activation, monetization
• Lead the ideation, development, and launch of growth features across our API product – onboarding, console, docs, billing, and self-serve upgrade paths
• Analyze product metrics and user feedback to identify opportunities and optimize performance
• Collaborate with engineering, design, developer relations, and marketing teams to deliver high-impact growth initiatives
• Conduct user research to understand customer needs and pain points
• Define and track key performance indicators (KPIs) for API growth
• Balance rapid iteration with our commitment to AI safety and ethics

Qualifications:

• 6+ years of product management experience, majority in growth focused roles
• Experience driving growth for API, developer platform, or technical / usage-based products
• Strong analytical skills, and experience with A/B testing and funnel optimization
• Excellent communication and stakeholder management skills
• Ability to thrive in a fast-paced, ambiguous environment
• Passion for AI technology and its potential impact on society
• Technical background or ability to work effectively with engineering teams
• Founder experience is a plus

About the role

As a Product Manager for Monetization, you’ll drive revenue growth across our product suite spanning Claude.ai, Claude Code, Claude Cowork, and Claude Platform. You’ll work closely with other growth teams that are focused on driving growth for specific audiences. You’ll also partner with a cross-functional team of engineers, designers, marketers, and data scientists to develop and execute strategies that accelerate our growth while maintaining our commitment to safety and beneficial AI.

Responsibilities:

• Develop and execute a product strategy focused on increasing revenue growth across our suite of products
• Drive monetization efforts spanning the likes of pricing & packaging, free-to-paid conversion, and consumption-based billing
• Analyze product metrics and user feedback to identify monetization opportunities and optimize performance
• Collaborate with engineering, design, and marketing teams to deliver high-impact growth initiatives
• Conduct user research to understand customer needs and pain points
• Define and track key performance indicators (KPIs) for growth initiatives
• Balance rapid iteration with our commitment to AI safety and ethics

Qualifications:

• 6+ years of product management experience, majority in growth focused roles
• Experience working on growth for mass-scale subscription businesses
• Direct experience owning monetization – pricing, packaging, paid conversion, or upgrade funnels
• Strong analytical skills, and experience with A/B testing and funnel optimization
• Excellent communication and stakeholder management skills
• Ability to thrive in a fast-paced, ambiguous environment
• Passion for AI technology and its potential impact on society
• Technical background or ability to work effectively with engineering teams
• Founder experience is a plus

About the role

Anthropic's Verticals team builds AI products purpose-built for specific industries—financial services, life sciences, healthcare, and legal. Most of these teams are being built 0→1 right now: you'll be forming the team, defining the product, and shipping the first version in markets where no one has done this well yet. Where we're further along, products are already live with enterprise customers and growing fast.

We're hiring Engineering Managers to lead the teams building Claude for Financial Services, Life Sciences, and Healthcare. You'll lead a team shipping AI into professional workflows—owning execution, working directly with customers and go-to-market, and helping shape where the broader Verticals group goes next.

We're hiring for all four verticals through this posting. Team placement happens during the interview process based on your background, interests, and organizational need—if you have deep experience in one of these domains, let us know in your application.

About the teams

• Claude for Financial Services — Builds products for customers in investment banking, asset management, insurance, and corporate finance. Near-term work centers on deeply integrated experiences inside the tools these teams already use, with a roadmap expanding as we learn what's most useful. The team operates close to enterprise customers and close to research.
• Claude for Life Sciences — We're building an agentic research platform for scientists—orchestrating specialist agents for computational biology, literature review, and regulatory review—on top of model capabilities we're investing in for biology and chemistry. The product is live with early customers and expanding fast; you'll lead engineering through that growth
• Claude for Healthcare — We're earlier here: standing up a team to build 0→1, focused initially on payer workflows (claims, prior authorization, utilization management, member communications), with groundwork for clinical applications over time. You'll be defining the product and the team at the same time.

Responsibilities

• Lead and develop a team of engineers building new AI products for enterprise customers in your vertical
• Work closely with research to make the models better in your domain—shaping evals, surfacing failure modes, and feeding customer learnings back into model development
• Own engineering execution end-to-end: planning, prioritization, delivery quality, team health, and incident response
• Partner with sales and customer success on enterprise deals—understanding requirements, joining key conversations, and turning what you learn into engineering priorities
• Shape the roadmap with product and design, not just execute against it
• Drive the compliance and platform-readiness work your customers require, partnering with security and legal
• Recruit, onboard, and grow strong engineers; give direct feedback and build a healthy, high-performing team

You may be a good fit if you

• Have built AI products and have a practical understanding of what it takes to turn model capabilities into applications people actually use
• Are comfortable working with enterprise customers, working alongside sales and customer success and joining customer conversations
• Know the operational realities of building on platforms and integrations you don't control
• Are a skilled engineering manager who treats management as a craft—clear feedback, strong 1:1s, consistent investment in your team's growth

Strong candidates may also have

• Experience in working with research to improve domain specific model capabilities
• Experience with model evaluation frameworks and how evals inform product decisions
• Experience taking a product from 0→1—forming a team, finding product-market fit, and shipping the first version with limited precedent to lean on
• Deep domain knowledge in one of these verticals—investment banking, asset management, insurance, or corporate finance; drug discovery or computational biology; clinical operations, health systems, or payers; or legal practice or legal tech
• Direct experience with the compliance frameworks relevant to these industries, including owning that work within an engineering org
• Exposure to both product-led growth and direct enterprise sales, and an understanding of how engineering decisions interact with each

Representative projects

• Partnering with an enterprise customer to map a core workflow—a deal-documentation process, a target-identification pipeline, a prior-authorization queue—and turning it into an engineering roadmap with a new or existing AI product
• Collaborating with research to design an evaluation framework that gives reliable signal on output quality across your domain's use cases
• Owning a platform-readiness initiative end-to-end—scoping with legal and security, defining the engineering work, and shipping it

Staff Infrastructure Engineer, Node Infra

About the role

Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand.

Node Infra owns the full lifecycle of accelerator capacity at Anthropic. We ingest and provision compute from all major CSPs and our own datacenters, stand up and scale clusters from thousands to hundreds of thousands of hosts, and build the health, diagnostics and repair automation that keep every GPU, TPU and Trainium node in the fleet usable and ready to power Anthropic’s frontier AI research.

Key responsibilities

• Own the technical strategy and roadmap for node lifecycle management - ingestion, bring-up, health checking, and automated repair
• Drive cross-team initiatives to build and scale AI clusters across multiple clouds and accelerator families
• Design and operate the systems that detect, isolate, and remediate unhealthy hardware automatically, driving up fleet MTBI and minimizing stranded capacity
• Define infrastructure architecture, ensuring the hardest problems get solved - whether by you directly or by working through others
• Work closely with cloud providers and internal research/inference/product teams to shape long-term compute, data, and infrastructure strategy
• Establish and evolve operational excellence practices (incident response, postmortem culture, on-call)
• Support the growth of engineers around you through technical mentorship and coaching

Minimum qualifications

• Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure)
• Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform.
• Hands-on experience with machine learning accelerators (GPUs, TPUs, or Trainium)
• Track record of leading complex, multi-quarter technical initiatives that span multiple teams or systems
• Ability to build alignment across senior stakeholders and communicate effectively at all levels

Preferred qualifications

• 8+ years of software engineering experience, including time as a technical lead setting direction for a team
• Experience managing large scale compute infrastructure at hyperscale (10K+ nodes), including capacity management and efficiency
• Depth in one or more of: Kubernetes internals (scheduler, autoscaler, kubelet, Karpenter), cluster orchestration systems (Mesos, Borg-like), or node provisioning pipelines
• Low-level systems experience: kernel, virtualization, device drivers, firmware, or hardware health/diagnostics daemons
• Familiarity with high-performance networking (EFA, RDMA, InfiniBand) for distributed ML workloads.
• Demonstrated ownership of production reliability for high-throughput, latency-sensitive systems
• Contributions to relevant open-source projects (Kubernetes, Linux kernel, container runtimes, etc.)
• Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software systems

About the role

As a Growth Account Executive at Anthropic, you'll drive expansion and retention of our fastest-growing startup customers by helping them harness the transformative potential of safe, frontier AI. You'll leverage your consultative sales expertise to grow revenue while becoming a trusted strategic advisor, helping customers expand their AI capabilities and unlock new use cases. Working closely with GTM, product, and marketing teams, you'll identify expansion opportunities while ensuring our customers get maximum value from Anthropic's solutions.

The ideal candidate will combine strong sales acumen with relationship management skills, focusing on growing accounts through strategic upsells while maintaining high retention rates. By driving expanded deployment of Anthropic's emerging products, you will help enterprises scale their AI capabilities while advancing its ethical development.

Responsibilities:

• Drive revenue growth through strategic account expansion and renewals
• Own the full sales cycle for upsell opportunities while maintaining strong retention rates
• Build and maintain trusted relationships with key stakeholders across your portfolio of high-growth startups
• Lead strategic account planning including Quarterly Business Reviews, health checks, and renewal negotiations
• Partner with customers to identify new use cases and opportunities to expand their AI capabilities with Anthropic
• Serve as the voice of the customer by gathering feedback and conveying market needs to inform our product roadmap
• Develop and execute account strategies that align Anthropic's solutions with customer business objectives
• Proactively identify and mitigate retention risks while maintaining high customer satisfaction

You may be a good fit if you have:

• 5+ years of experience in sales or account management roles, with a proven track record of growing accounts and exceeding retention targets
• Success as a strategic business advisor, deeply understanding startup needs and creating innovative solutions that align with their vision
• Experience managing complex sales cycles, working with technical stakeholders, and negotiating strategic deals
• Strong presentation and communication skills with ability to build relationships across all customer levels, from ICs to C-level executives
• Analytical approach to understanding customer needs combined with creative solutions to drive expansion
• A knack for bringing order to chaos and an enthusiastic "roll up your sleeves" mentality
• Passion for emerging technologies like AI, with interest in ensuring they are developed safely and responsibly
• Experience running strategic business reviews and managing executive relationships
• Track record of consistently meeting or exceeding quota in fast-paced environments

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

About the role

As the Healthcare Sales Lead within Anthropic's Healthcare & Life Sciences team, you will define and execute our AI transformation strategy for health insurance companies and health plans. You'll build and lead a small, specialized team focused on the payer segment, developing repeatable playbooks that guide payers through end-to-end AI strategy definition, implementation, and scale across their critical business functions—from claims processing and utilization management to member engagement and provider network optimization.

This role requires deep domain expertise in the payer business model combined with strategic AI advisory capabilities. You'll become the go-to expert on how Claude transforms payer operations, working directly with C-suite executives at major health plans to design multi-year AI transformation roadmaps. Your playbooks will enable both your team and our broader field organization to drive consistent, high-value outcomes across the payer segment.

You'll partner closely with payer executives to understand their strategic priorities—whether reducing medical costs, improving Star Ratings, enhancing member experience, or streamlining administrative burden—and translate these into concrete AI use cases with measurable ROI. Success means establishing Anthropic as the strategic AI partner for the payer industry.

Responsibilities:

• Payer Strategy & Playbook Development: Develop comprehensive, repeatable playbooks for AI transformation across the payer value chain. Create frameworks that address claims adjudication, prior authorization, care management, member services, provider contracting, Medicare Advantage operations, and risk adjustment.

• Team Building & Leadership: Build and lead a specialized team that deeply understands payer operations and can credibly engage with health plan executives on AI strategy. Develop your team into trusted advisors who can navigate complex payer organizations.

• Executive Engagement: Partner directly with payer C-suite executives (CEOs, CFOs, CMOs, CTOs, CCOs) to understand their strategic priorities and design multi-million dollar AI transformation initiatives. Build long-term trusted advisor relationships.

• Domain Expertise: Serve as Anthropic's subject matter expert on payer operations, business models, regulatory environment (CMS regulations, HIPAA, state insurance departments), and competitive dynamics. Translate this expertise into repeatable go-to-market strategies.

• Cross-Functional Orchestration: Work closely with Account Executives, Applied AI Engineers, Customer Success, Product, and Legal teams to ensure seamless execution of complex payer deals and implementations.

• Industry Partnerships: Build strategic relationships with payer-focused system integrators (e.g., Cognizant, Accenture, Optum Advisory, Deloitte Health), health tech vendors, and industry organizations to scale our go-to-market capabilities.

• Thought Leadership: Establish Anthropic's position as the AI partner of choice for payers through conference presentations, white papers, case studies, and participation in industry forums like AHIP, NAHU, and regional Blues plans associations.
  
  

You may be a good fit if you:

• Have 10+ years of experience in healthcare, with at least 5 years specifically in the payer segment (health plans, managed care organizations, PBMs, or payer-focused consulting)

• Have deep understanding of payer business models, operations, and economics including claims processing, medical management, network contracting, risk adjustment, and regulatory compliance

• Have experience in leadership roles driving technology transformation or operational improvement initiatives within payer organizations or as a payer-focused consultant

• Have built and led teams (even small ones) that delivered measurable business outcomes in healthcare settings

• Are skilled at translating complex business problems into technology solutions and vice versa, with ability to engage credibly with both clinical and technical stakeholders

• Have strong strategic thinking combined with hands-on execution capability—comfortable building frameworks while also rolling up sleeves on deals

• Are an influential communicator who can build trust with payer C-suite executives and navigate complex healthcare organizations

• Have experience with healthcare technology implementations and understand the regulatory constraints that shape payer operations

• Are passionate about using AI to improve healthcare delivery and reduce administrative burden in the healthcare system

About the role

As the Global Leader of Applied AI Architects for Beneficial Deployments, you will lead the team of Applied AI Architects who serve as the primary technical partners to mission-driven organizations and non-profits adopting Claude. You'll build and scale a world-class, globally distributed team that turns frontier AI into real impact in education, global health, economic mobility, and life sciences—while shaping how Anthropic's most important societal partnerships are designed and delivered.

You'll combine deep technical fluency with the leadership judgment needed to operate across segments, regions, and partner types—from global health foundations to leading research institutions to frontline nonprofits. You'll set the vision for how we scale our expertise from a handful of flagship partnerships to an ecosystem of organizations operating as AI-native, and you'll be accountable for the team, processes, and cross-functional relationships that make that possible.

In collaboration with Beneficial Deployment’s Head of Nonprofits, Product, Engineering, Policy, and our broader GTM organization, you'll help ensure our partners incorporate Claude into their work responsibly, effectively, and in ways that meaningfully accelerate their missions. You'll represent Anthropic as a senior technical leader on some of our most visible and consequential partnerships, while maintaining our best-in-class safety standards.

Responsibilities

• Lead, grow, and mentor a globally distributed team of Architects supporting mission-driven non-profits across education, global health, economic mobility, and life sciences

• Set the vision, strategy, and operating model for how Applied AI shows up in Beneficial Deployments—from discovery through deployment, and from individual partnerships to ecosystem-wide infrastructure

• Establish hiring plans, team structure, and career development paths as we scale the team globally; set goals and reviews that promote growth, output, and a high bar for technical excellence

• Partner closely with segment leads and senior partner leadership to understand requirements and shape engagements on our highest-impact partnerships

• Drive the design of cohort-based accelerators, Claude Code enablement programs, and other scalable mechanisms that multiply our impact across many organizations simultaneously

• Identify patterns across partners and segments to inform what we build at the ecosystem level—MCPs, evals, reference implementations, and shared infrastructure

• Collaborate with Product and Engineering to surface partner needs, influence roadmap, and ensure learnings from the field shape how Claude evolves

• Represent Anthropic externally with senior leaders at foundations, nonprofits, research institutions, and government-adjacent organizations

• Travel to partner sites globally for workshops, technical deep dives, and relationship building

• Help shape team processes and culture as Beneficial Deployments scales, and contribute to the broader Applied AI leadership community at Anthropic

• Travel is 30-40% due to the global nature of the team (SF, NYC, London and Bengaluru) and events across Beneficial Deployments.

You may be a good fit if you have

• 10+ years of experience in technical, customer-facing roles (Solutions Architect, Forward Deployed Engineer, Customer Engineer, Sales Engineer, or similar), with meaningful exposure to complex, high-stakes deployments

• 7+ years of engineering or technical leadership experience, preferably building and scaling customer-facing or forward-deployed teams globally

• Experience working with or inside mission-driven organizations—education, healthcare, scientific research, global development, or nonprofits—and a genuine understanding of the constraints, incentives, and operating realities of these sectors

• Familiarity with common LLM implementation patterns, including prompt engineering, evaluation frameworks, agent frameworks, and retrieval systems; working knowledge of Python

• A track record of building teams in ambiguous, fast-moving environments, and comfort wearing multiple hats as the team scales

• Strong executive presence and the ability to foster deep, trusted relationships with senior partner leadership

• Excellent communication, collaboration, and coaching abilities, with a love of teaching and helping others succeed

• The ability to think holistically, identify core principles that translate across scenarios, and make ambiguous problems clear

• A passion for making powerful technology safe and societally beneficial, and for thinking creatively about risks and benefits beyond existing playbooks

Strong candidates may also have

• Experience leading globally distributed teams across time zones and regions

• Background in philanthropy, global health, education technology, or scientific research

• Experience designing cohort-based or programmatic delivery models that scale technical expertise across many organizations

• A working understanding of emerging research in agents, evaluations, and AI safety

About the team

Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences, focusing on raising the floor for the people and institutions working on humanity's hardest problems.

About the role:

As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping customers understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your technical depth with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability.

As a Commercial Solutions Architect, you'll go deep with priority accounts as a hands-on builder, while creating reusable blueprints, demos, and enablement that extend Claude's reach across the broader Commercial book of business.

Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems.

Responsibilities:

• Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation

• Serve as the primary technical advisor to customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams and stakeholders to drive customer success

• Support customers building with the Claude API, Claude Code, and Claude for Enterprise

• Ship working code. Build prototypes and proof-of-concepts hands-on, develop eval frameworks, and write near-production examples that customers can extend

• Build reusable blueprints, demos, and enablement assets that scale across customers

• Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack

• Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases

• Identify common integration patterns and contribute insights back to our Product and Engineering teams

• Travel occasionally to customer sites for workshops, technical deep dives, and relationship building

• Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns

You may be a good fit if you have:

• 3+ years of highly technical experience as a software engineer (or equivalent) with some customer-facing exposure, OR 3+ years as a Solutions Architect, Sales Engineer, or Technical Account Manager with strong hands-on building experience

• A builder identity. You've shipped real software, you have technical taste, and you care about the craft of what you build

• A systems mindset. When you see a problem, your instinct is to ask "how do I make this reusable." You'd rather build one thing that serves ten customers than ten things that serve one each

• Strong coding ability. You ship prototypes regularly and can work in a real codebase, not just notebooks. Comfort with Python expected

• Strong ability to build trust with technical stakeholders and adjust your communication for varied audiences

• Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders

• Experience designing scalable cloud architectures and integrating with enterprise systems

• Familiarity with common LLM frameworks and tools, or a background in machine learning or data science

• Comfort operating in early-stage, ambiguous environments where the playbook doesn't exist yet, and a track record of building structure as you go

• Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities

• A love of teaching, mentoring, and helping others succeed

• Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

About the role:

As a member of the Applied AI team at Anthropic, you will be a technical Product Engineer focused on becoming a trusted technical advisor to Digital Native Businesses - technology companies adopting the Claude API into their core products. You will work closely with customer product and engineering teams as they ship new products powered by Claude: advising on architecture design decisions, developing evaluation frameworks, and guiding customers through the most cutting-edge implementation patterns for LLMs.

Working closely with our Sales, Product, and Engineering teams, you'll guide a focused portfolio of customers from technical discovery through successful deployment. You'll combine deep engineering expertise with customer-facing skills to help customers unlock the full potential of Claude APIs and move their products closer to the frontier, while maintaining our high standards for safety and reliability.

Responsibilities:

• Serve as a specialist technical advisor to Anthropic customers as they deploy new products & workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success
• Partner with account executives and solutions architects to translate customer business requirements into technical solutions
• Influence technical architecture decisions and customer product strategy by developing customized pilots, prototypes, and evaluation suites
• Lead hands-on technical workshops and code reviews with customer engineering teams
• Identify common design patterns and contribute insights back to our Product and Engineering teams
• Create scalable public and internal assets, documenting the latest LLM prompting, evaling, agentic, and architecture techniques
• Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks
• Travel occasionally to customer sites for workshops, implementation support, and building relationships
• Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space

You may be a good fit if you have:

• 4+ years of experience in technical roles such as Forward Deployed Engineer, Software Engineer or Technical Product Manager with a desire to work closely with customers. Former technical founders are also encouraged to apply.
• Production experience with LLMs including advanced prompt engineering, agent development and frameworks, evaluation frameworks, transcript analysis, MCP, and deployment at scale
• Strong programming skills with proficiency in Python or TypeScript and experience building production applications
• Ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems
• High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity
• Passion for advancing safe, beneficial AI systems through creative technical applications
• Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach

Please note this role requires 3 days in office per week. 

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

About the role

As an Applied AI Architect on the Startups team at Anthropic, you will win the trust of founders and engineers by being an exceptional technical partner, helping startups successfully build on the Claude Developer Platform as they grow from early product to scale. You'll combine deep technical expertise with a builder-first mindset to help startups architect innovative LLM solutions, win technical evaluations, and get the most out of Claude.

Working closely with Account Executives and the broader Sales, Product, and Engineering teams, you'll guide startups from initial technical discovery through successful deployment and beyond. You'll leverage your expertise to help founders understand Claude's capabilities, develop evals, and design architectures that maximize the value of our AI systems.

Responsibilities:

• Partner with Account Executives to deeply understand startup requirements, translate them into technical solutions, and serve as a trusted technical advisor throughout the Claude adoption journey from initial evaluation through deployment and expansion
• Win technical evaluations that demonstrate why Claude is the best foundation for what startups are building, helping them develop evaluation frameworks to measure Claude's performance for their specific use cases
• Build technical credibility with founders, founding engineers, and startup engineering teams by speaking their language, understanding their build patterns, and guiding technical architecture decisions
• Gather insights on how startups are building with Claude, identify emerging use cases and deployment patterns, and deliver feedback to Product and Engineering teams
• Travel to customer sites, startup-focused events, and industry conferences for workshops, technical deep dives, and relationship building

You may be a good fit if you have:

• 3+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, Forward Deployed Engineer, or technical founder who has done founder-led sales
• Experience working with startups or high-growth technology companies; you understand the velocity and constraints of early-stage companies
• Strong builder credibility through experience as a software engineer or technical founder; you speak the language of builders and have the presence to earn the trust of technical founders and startup engineering teams
• Deep technical proficiency with building and scaling AI products, a pulse on AI engineering best practices, and the ability to demonstrate why Claude is the best foundation
• Hands-on experience building and deploying LLM-powered applications in production, with expertise in context engineering, evaluation frameworks, and modern AI architectures
• Strong technical communication skills with the ability to translate complex AI concepts into actionable insights for founders and engineering teams
• Track record of selling technical products in competitive markets
• Comfortable with Python and familiarity with common LLM frameworks, tools, and integration patterns
• Passion for making powerful technology safe and societally beneficial

About the role:

You'll be the face of Anthropic in the startup ecosystem — driving awareness and activation among founders and their technical teams. Your focus is lighting up the startup developer community and getting builders excited about, onboarded onto, and actively building on top of the Claude Developer Platform.

This role sits at the intersection of startup ecosystem development and hands-on technical activation. Your primary mandate is driving adoption across the startup funnel — turning ecosystem touchpoints into active, building developers on Anthropic's platform. You'll work closely with the Startups GTM team to convert ecosystem relationships — with VCs, accelerators, and founder communities — into active, building developers.

Responsibilities:

Drive Net New Logo Acquisition Through Developer Enablement

• Lead hands-on developer onboarding experiences at ecosystem events that convert startup founders and their engineers from first API interaction to committed platform adoption

• Build scalable enablement programs — hands-on workshops, build-a-thons, and technical office hours — that activate developers at VC and accelerator partner events

• Develop a playbook for turning ecosystem touchpoints (builder summits, founder days, VC partnerships) into measurable developer sign-ups and active usage

• Partner closely with the Startups GTM team to create seamless handoffs from relationship → activation → retention

Create Compelling Technical Content

• Create high-quality technical content — tutorials, demo apps, and blog posts — that showcase how to build real products on Anthropic's API, with a focus on common startup use cases

• Develop code demos and working prototypes that showcase Claude's capabilities in ways that resonate with technical founders, particularly at ecosystem events and webinars

• Partner with the Product team to stay current on platform capabilities and ensure content reflects the latest developer tooling and best practices

Lead Developer Programming at Startup Events

• Own developer-facing programming at Anthropic's builder summits and global startup activations

• Design and run hands-on technical sessions that move developers from curiosity to active building within a single event

• Build relationships with key technical communities — developer platforms, open-source contributors, and startup accelerator cohorts — to grow Anthropic's developer mindshare

• Represent Anthropic as a trusted technical resource in the startup ecosystem

Partner Across GTM and Ecosystem

• Surface market signal and developer sentiment from the startup ecosystem back to internal teams

• Partner with GTM, Sales, and Marketing to create developer-focused activation campaigns and messaging for the startup ecosystem

• Work with the Startups Partnerships team to ensure VC and accelerator relationships translate into real developer engagement and usage metrics

• Collaborate closely with the Product team to stay aligned on platform strategy, content, and developer programs

Define Success and Scale

• Define and track success metrics — tied to net new logos, developer activation, and ecosystem engagement — and build reporting that connects evangelist activity to business outcomes

• Create scalable processes and grow the team as the startup ecosystem expands

You may be a good fit if you have:

• 7+ years of experience across a combination of founding/building startups and developer-facing roles (developer relations, evangelism, or ecosystem development)

• Experience as a technical founder, early startup employee, or operator who has lived the 0-to-1 journey and knows what it takes to go from idea to product-market fit

• The ability to write production-quality code, build compelling demos, and credibly engage with technical co-founders and their engineering teams

• Strong public speaking skills with comfort on stage, the ability to command a room at builder summits and ecosystem events, and deliver technical content that energizes an audience

• Experience building or scaling developer programs, communities, or enablement motions that drove measurable adoption

• Builder credibility that earns trust with founders, VCs, and accelerator communities. You've shipped products and can speak from experience

• Willingness to travel regularly and flexibility to support events that fall outside standard business hours, including evenings and weekends

• Deep enthusiasm for AI with hands-on experience building with LLMs. You stay close to the technology and genuinely care about building it responsibly

About the design team

Design at Anthropic sits at the intersection of craft, research, and product intuition. We're a small team working on products that millions of people use daily—and on interactions that don't have established conventions yet.

Our work shapes how people experience AI: whether Claude feels like a tool or a collaborator, whether it earns trust or erodes it. We partner closely with engineers and researchers, often designing around capabilities that are emerging in real-time. That means staying close to the models, prototyping rapidly, and being comfortable with ambiguity.

We care deeply about craft—the details that make something feel polished and trustworthy—but we ship fast and learn in the open. We'd rather get something in front of users and iterate than wait for perfection.

Read more here for the type of features we build. 

Responsibilities:

• Contribute to the strategic direction of our tools, rooted in deep user empathy
• Define feature areas with exceptional attention to detail and polish, identifying opportunities to improve quality and consistency of broader flows
• Craft beautiful, polished, and delightful user interfaces that build trust and showcase the power of our AI technology
• Collaborate with product managers, engineers, AI researchers and other stakeholders to define product vision, strategy and roadmaps
• Rapidly prototype ideas using code and other methods to communicate concepts and build excitement
• Find creative ways to ship high-quality work in a fast-paced, often ambiguous, resource-constrained startup environment

Specific projects & responsibilities depend on the team staffing, which we’ll talk about once we’ve seen some more of your work and understood your strengths & interests. A few examples across teams:

• Claude Cowork: Pioneer new ways for Claude to be a true partner in people’s day to day lives that can access your tools, ask for feedback, help you prep for your day, and more; Build expertise in industries like education, financial services, and healthcare to design intuitive experiences that help people leverage AI at work in transformative ways.
• Claude Code: Evolve our industry-leading coding tool, across terminal and Desktop, to deepen the breadth and depth of agentic coding.
• Growth: Design intuitive onboarding flows that help new users get started quickly, understand Claude's capabilities, and achieve their goals in the first session; Uncover barriers that prevent users from getting the most out of Claude and create experiences that empower them to make it a trusted part of their routine.
• Developer Platform: Support frontier capabilities and API features via tooling, workflows, and documentation; Define the future suite of utilities for developers to confidently build, monitor and control agentic systems.
• Consumer: Evolve the Claude mobile app, with a focus on being genuinely helpful for people’s everyday lives: learning, creative projects, personal planning and problem-solving — with an emphasis on quality & safety. 

What we’re looking for:

• You ship fast and stay in motion. You'd rather get something in front of users this week than perfect it for a month. You prototype in code, stay scrappy when speed matters, and know when to polish versus when to learn.
• You're rethinking the basics. Many UI primitives were designed for a different era. You're excited to question fundamental assumptions and invent patterns that feel native to AI.
• You're AI-native in how you work. You're already using Claude Code or similar tools to extend what you can build. You see AI as a creative partner in your own practice.
• You stay close to the models. You pay attention to where capabilities are heading, not just what Claude can do today. You design for the product we're becoming.
• You elevate craft while moving fast. You care about the details—the pixels, the copy, the edge cases—and find ways to maintain that care while shipping quickly.

You may be a good fit if you have:

• Experience designing complex workflows, enterprise/B2B SaaS, developer tools, or API products 
• Strong portfolio showcasing user-centric design thinking, polished UI craftsmanship, and innovative interaction paradigms
• Proven track record of executing end-to-end on large and complex products or a series of products in ambiguous environments
• Excellent collaboration and communication skills to work effectively with cross-functional teams and influence without authority
• Passion for crafting scaled, highly impactful, safe and beneficial artificial intelligence technologies to enable new possibilities
• Experience with prototyping, especially using front-end code (e.g. HTML/CSS/JS) preferred

Role Overview

As a Sales Development Manager for Enterprise at Anthropic, you will lead a strategic BDR team focused on generating high-value pipeline within complex enterprise organizations. You will build and manage a team of 6-10 BDRs who specialize in account-based prospecting, multi-threaded outreach, and sophisticated qualification of enterprise opportunities. This role requires a leader with deep understanding of enterprise sales cycles, complex organizational dynamics, and the patience to develop long-term strategic accounts.

Key Responsibilities:

• Build, lead, and scale a team of 6-10 BDRs focused on Enterprise segments

• Drive strategic pipeline generation through account-based prospecting and targeted outbound campaigns to G2000 accounts

• Partner with Enterprise AEs to develop account plans, coordinate multi-threaded outreach, and ensure quality opportunity handoffs

• Establish and track KPIs focused on opportunity quality, deal size, and strategic account penetration

• Create comprehensive training programs on enterprise prospecting, stakeholder mapping, and complex qualification

• Develop deep understanding of enterprise buying processes and coach team on navigating procurement, legal, and security requirements

• Own Pipeline Reviews with sales leadership covering enterprise pipeline health, account penetration, and competitive positioning

• Build strong relationships with cross-functional leaders and partners including Sales, RevOps, Strategy, and Marketing

• Coach and mentor BDRs on strategic prospecting, executive engagement, and career development toward enterprise AE roles

Qualifications:

• 5+ years of experience managing BDR/SDR or New Business AE teams, with significant experience in enterprise-focused organizations

• Proven track record of building teams that successfully prospect into complex enterprise organizations

• Personal closing experience strongly preferred (former AE, Account Manager, or hybrid IC/management role)

• Experience with account-based marketing/selling strategies and tools

• Strong analytical skills with experience developing sophisticated prospecting systems

• Experience with Claude, Claude Code, Salesforce, Apollo, AI Prospecting Tools, HubSpot, LinkedIn Sales Navigator, and other enterprise sales tools

• Demonstrated ability to coach reps on navigating complex organizational structures and multi-stakeholder deals

• Excellent communication skills with ability to engage at executive level

• Experience in API-first, consumption-based, or platform business models preferred

• Bachelor's degree or equivalent work experience

Preferred Experience:

• Experience managing teams prospecting to Fortune 500 or Global 2000 accounts

• Background in AI/ML, cloud infrastructure, or developer platforms

• Track record of developing BDRs who successfully transition to enterprise AE roles

• Experience building enterprise prospecting playbooks from scratch

• Familiarity with enterprise procurement, security reviews, and legal processes

About the Team

Safeguards Labs is a new team operating at the intersection of research and engineering, chartered to investigate novel safety methods that protect Claude and the people who use it. We prototype new approaches to safe models, usage safeguards, and production safety — pressure-testing ideas through offline analysis and subsets of traffic before they graduate into production systems run by our partner Safeguards teams. Our work overlaps closely with account abuse, model behavior safeguards, and other safeguard subteams, and we serve as a research arm that can take on ambitious, ambiguous problems and turn them into deployed defenses.

About the Role

We're hiring research engineers to define and execute the Labs research agenda. You'll scope your own projects, run experiments end-to-end, and decide when an idea is ready to hand off to a production team — or when to kill it and move on. The team is small and being built deliberately around a roughly 3:1 mix of researchers to software engineers, so each person has substantial latitude over what they work on and high leverage on the team's direction.

Responsibilities:

• Lead and contribute to research projects investigating new methods for detecting misuse of Claude, identifying malicious organizations and accounts, strengthening model safeguards, and other safety needs.
• Design and run offline analyses over model usage data to surface abuse patterns, build classifiers and detection systems, and evaluate their effectiveness.
• Develop and iterate on prototypes that could eventually feed signals into the real-time safeguards path, partnering with engineers on tech transfer.
• Contribute to a broader research portfolio investigating methods for detecting abusive behavior in chat-based or agentive workflows, and for training the model to robustly refrain from dangerous responses or behaviors without over-refusing.
• Build evaluations and methodologies for measuring whether safeguards actually work, including in agentic settings.
• Write up findings clearly so they inform decisions across Trust & Safety, research, and product teams.

You may be a good fit if you:

• Have a track record of independently driving research projects from ambiguous problem statements to concrete results, ideally in AI, ML, security, integrity, or a related technical field.
• Are comfortable scoping your own work and switching between research, engineering, and analysis as a project demands.
• Have working familiarity with how large language models operate — sampling, prompting, training — even if LLMs aren't your primary background.
• Are proficient in Python and comfortable working with large datasets.
• Care about the societal impacts of AI and want your work to directly reduce real-world harm.

Strong candidates may also have: 

• Experience building and training machine learning models, including classifiers for abuse, fraud, integrity, or security applications.
• Knowledge of evaluation methodologies for language models and experience designing evals.
• Experience with agentic environments and evaluating model behavior in them.
• Background in trust and safety, integrity, fraud detection, threat intelligence, or adversarial ML.
• Experience with red teaming, jailbreak research, or interpretability methods like steering vectors.
• A history of taking research prototypes and transferring them into production systems.

About the team

Anthropic's mission is to ensure the world safely makes the transition through transformative AI.

Our Go-To-Market organization helps enterprises understand, adopt, and scale Claude responsibly. Within GTM, the Partner Enablement team builds the programs, credentials, and learning infrastructure that allow our ecosystem of system integrators, cloud providers, and technology partners to build deep Claude expertise and deliver successful customer outcomes at scale.

We work cross-functionally across Partnerships, Sales, Applied AI, Product, and Marketing to make sure partner-facing programs are clear, consistent, and high-impact.

About the role:

We're looking for a Partner Enablement Lead, System Integrators to define and scale how Anthropic enables its SI ecosystem.

This role is responsible for translating partnership and product strategy into clear, repeatable programs that help system integrators build, sell, and deliver with Claude. You will own enablement for a portfolio of our most strategic global SIs and set the strategy, operating model, and team that extends that work across the broader service provider ecosystem, from global integrators to regional and specialist firms.

This is a highly cross-functional leadership role that combines 0 to 1 building with scaling global programs. You'll work closely with Partnerships leadership and teams across Sales, Applied AI, Product, Marketing, and Enablement to ensure partner-facing initiatives land clearly and drive measurable outcomes.

In this role, you will

• Define and lead Anthropic's enablement strategy for the global system integrator ecosystem

• Serve as the enablement lead for a portfolio of strategic global SIs, accountable for practitioner readiness and certification outcomes

• Build and scale the SI enablement function, including team, operating model, and coverage approach across partner segments

• Design and operationalize repeatable programs across onboarding, technical workshops, train-the-trainer, hackathons, and product launches

• Develop partner learning pathways and certification delivery models that scale across large practitioner populations

• Create high-quality enablement content such as playbooks, solution guides, and technical assets

• Enable Anthropic sellers and partner managers to engage, position, and co-sell effectively with SIs

• Partner cross-functionally to align priorities, share infrastructure, and ensure consistent execution across partner-facing initiatives

• Establish metrics and reporting to track partner activation, certification progress, pipeline contribution, and program effectiveness

• Build feedback loops that bring partner insights back into enablement, product, and GTM strategy

You might thrive in this role if you:

• 7-10+ years of Partner Enablement, Alliance or Sales experience

• Have built and scaled partner enablement or practice development programs in high-growth technology environments

• Have deep experience working with or inside large global system integrators and understand how they build, staff, and grow a technology practice

• Bring existing senior relationships across the SI ecosystem and the executive presence to influence practice and alliance leadership

• Turn complex product and GTM strategy into clear, scalable programs

• Are an effective operator who can lead cross-functional initiatives across complex organizations

• Thrive in fast-paced, ambiguous environments and enjoy building from 0 to 1

• Think in systems, operating models, and tiered coverage rather than one-off efforts

• Are technically curious about AI and credible with both business and technical partner audiences

Strong candidates may also have:

• Experience building or running an authorized training partner or certified instructor network

• Prior ownership of, or close partnership with, a technology certification program

• Time spent inside a GSI's AI, data, or cloud practice, or on a hyperscaler's SI alliance team

• A track record connecting enablement activity to pipeline and revenue outcomes

• Experience scaling programs across multiple regions, including offshore delivery centers

• People management experience with distributed or matrixed teams

Logistics:

This role must be based in one of our hubs: San Francisco, New York, or London. We operate a hybrid model and expect regular time onsite with partners and at Anthropic offices. Expect roughly 25-35% travel.

About the role

Anthropic is seeking an exceptional Contracts Manager to support commercial and technology transactions. We'll rely on you to help review, draft, and negotiate commercial and procurement contracts to support our cutting-edge AI systems. You'll also build scalable contracting processes and collaborate across Product, Sales, Finance, Business Operations, Research, and Procurement teams.

Responsibilities:

• Draft, analyze, negotiate, and complete complex commercial transactions with the company’s enterprise customers, vendors, and strategic partners, including IP licensing agreements 
• Propose and develop scalable solutions to improve contracting efficiency
• Collaborate with business units and legal team members to streamline contract management processes, identify potential risks, and drive continuous improvement in contract handling efficiency
• Collaborate with the Product, Sales, Business Operations, Research, and Procurement teams to achieve key business objectives and deliver strategic, business-minded, and solutions-focused counsel
• As a relatively small legal team supporting big things, each legal team member practices across multiple areas. We’d love to hear where else you’d be interested to pitch in, whether as a function of your experience or interests

You might be a good fit if you have:

• At least 5 years of related contract management experience, with at least 3 years of experience supporting technology transactions, GTM, sales, partnerships, or non-profit organizations
• Experience operating in a fast-paced technology startup in which priorities shift rapidly and schedules "move to the left," thriving in this dynamic environment and priding yourself on your adaptability and ability to pivot with speed and grace
• Initiative and autonomy in managing complex contractual matters, effectively prioritizing competing deadlines
• An understanding of what's important in the context of a contract, the organization's mission, when to be flexible, and when to draw a hard line
• Excitement to grow with an organization and help shape the culture of the commercial function
• A preference for straightforward, concise explanations over legalese and overwrought drafting
• A knack for identifying and implementing efficient processes and policies
• The ability to thrive as a member of cross-functional teams building frontier technologies, with a desire to develop a deep understanding of our technical teams and what we are building
• Comfort operating outside your areas of expertise and in uncharted legal territory
• A "doer" mentality, willing to roll up your sleeves to get things done as a team player who doesn't hesitate to jump in to do work that needs to get done, whether glamorous or not

Strong candidates may have:

• Proven ability to collaborate across various organizational levels and functions to facilitate efficient contracting processes and execution while building strong relationships
• Substantive knowledge of software agreements, reseller agreements, services agreements, strategic partnerships, and general contract terms 
• Excellent verbal and written communication, analytical, collaboration, and interpersonal skills
• Strong self-motivation and ability to multitask and juggle multiple priorities in a dynamic environment
• Authentic integrity and a deep understanding of the importance of ethics in business

Role-specific policy: For this role, we expect all staff to be able to work from our San Francisco or New York office at least 3 days a week, though we encourage you to apply even if you might need some flexibility for an interim period of time.

Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Research Engineer to join our Pre-training team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.

Key Responsibilities:

• Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development
• Independently lead small research projects while collaborating with team members on larger initiatives
• Design, run, and analyze scientific experiments to advance our understanding of large language models
• Optimize and scale our training infrastructure to improve efficiency and reliability
• Develop and improve dev tooling to enhance team productivity
• Contribute to the entire stack, from low-level optimizations to high-level model design

Qualifications:

• Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field
• Strong software engineering skills with a proven track record of building complex systems
• Expertise in Python and experience with deep learning frameworks (PyTorch preferred)
• Familiarity with large-scale machine learning, particularly in the context of language models
• Ability to balance research goals with practical engineering constraints
• Strong problem-solving skills and a results-oriented mindset
• Excellent communication skills and ability to work in a collaborative environment
• Care about the societal impacts of your work

Preferred Experience:

• Work on high-performance, large-scale ML systems
• Familiarity with GPUs, Kubernetes, and OS internals
• Experience with language modeling using transformer architectures
• Knowledge of reinforcement learning techniques
• Background in large-scale ETL processes

You'll thrive in this role if you:

• Have significant software engineering experience
• Are results-oriented with a bias towards flexibility and impact
• Willingly take on tasks outside your job description to support the team
• Enjoy pair programming and collaborative work
• Are eager to learn more about machine learning research
• Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large-scale AI research projects
• Are working to align state of the art models with human values and preferences, understand and interpret deep neural networks, or develop new models to support these areas of research
• View research and engineering as two sides of the same coin, and seek to understand all aspects of our research program as well as possible, to maximize the impact of your insights
• Have ambitious goals for AI safety and general progress in the next few years, and you’re working to create the best outcomes over the long-term.

Sample Projects:

• Optimizing the throughput of novel attention mechanisms
• Comparing compute efficiency of different Transformer variants
• Preparing large-scale datasets for efficient model consumption
• Scaling distributed training jobs to thousands of GPUs
• Designing fault tolerance strategies for our training infrastructure
• Creating interactive visualizations of model internals, such as attention patterns

At Anthropic, we are committed to fostering a diverse and inclusive workplace. We strongly encourage applications from candidates of all backgrounds, including those from underrepresented groups in tech.

If you're excited about pushing the boundaries of AI while prioritizing safety and ethics, we want to hear from you!

About the role

As a Mid-Market Account Executive on Anthropic's Industries team, you'll drive the adoption of safe, frontier AI by securing strategic deals with mid-market companies in key verticals, unlocking new value streams throughout their business. You'll leverage your consultative sales expertise and technical acumen to propel revenue growth while becoming a trusted partner to customers, helping them embed and deploy AI while uncovering its full range of capabilities. In collaboration with GTM, Product, Engineering, and cross-functional teams, you'll continuously refine our value proposition, sales methodology, and market positioning to ensure differentiated value across the landscape.

You will be contributing to the GTM strategy for our Industries team, focusing on sector-specific solutions and strategies within key verticals. In addition, the Mid-Market team is pioneering a new scaled sales playbook, where human AEs direct AI Agents to automate key elements of the buyer’s journey, while maintaining human engagement with prospects in the elements of a sales process that can’t be automated. 

You should be passionate about building a fundamentally new sales motion, by experimenting with new programs and workflows, and ultimately evangelizing the potential of Transformative AI to mid-market companies across verticals. 

Responsibilities:

• Contribute to the Mid-Market GTM strategy, identifying new use cases within your assigned verticals, winning new business, and sharing feedback with cross-functional teams
• Drive strategic expansion within key accounts in established verticals and new logo acquisition within emerging verticals
• Own a revenue target and all aspects of the sales cycle from prospecting to close, including finding key workflows to automate and agentify
• Become a trusted advisor to customers, understanding their unique needs and crafting tailored AI solutions. Co-innovate with customers and sell on the product roadmap while appropriately setting expectations
• Collaborate extensively with cross-functional partners including Product, Customer Success, Legal, Marketing, and Applied AI to help bring new solutions to market and provide feedback to shape roadmaps
• Develop sales collateral, proposals, and presentations to effectively position Anthropic's AI products. Continuously refine sales tactics and share best practices

You may be a good fit if you have:

• 3+ years of enterprise B2B sales experience in technology, preferably in SaaS, API solutions, or emerging technologies
• Experience automating workflows or building automations to handle the repeatable components of a sales process
• Proven experience exceeding revenue targets in fast-paced organizations by effectively managing an evolving pipeline and sales process
• Excellent communication skills and the ability to present confidently and build connections across all customer levels, from ICs to C-level executives
• A knack for bringing order to chaos and an enthusiastic “roll up your sleeves'' mentality. You are a true team player
• A strategic, analytical approach to assessing markets combined with creative, tactical execution to capture opportunities
• A passion for and/or experience with advanced AI systems. You feel strongly about ensuring frontier AI systems are developed safely
• Location: This role does require being in office 4x a week in one of our hubs

About the role

Join Anthropic as a Customer Success Manager supporting our Higher Education initiatives. In this role, you’ll apply customer success practices to higher education institutions. Anthropic’s Beneficial Deployments team is focused on building AI for good through partnerships with high-impact organizations across education, public health, life sciences, economic mobility, and more. As a dedicated Customer Success Manager, you’ll be the strategic partner and trusted advisor to universities - helping them harness Claude’s full potential of all our Claude capabilities - API, Claude for Enterprise, and Claude Code to amplify their social impact. 

You'll develop genuine partnerships with education institutions gaining a deep understanding of their mission, strategic objectives, programmatic goals, and technical capacity. Drawing on your education expertise, business acumen, and technical knowledge, you'll serve as a strategic advisor throughout their journey—helping them identify the right Claude capabilities for their specific objectives while providing best practices tailored to the unique constraints of institutions and education organizations. 

You'll help universities scale their AI usage safely and effectively, implementing change management strategies and driving toward impact for students, faculty, and administrators. 

Responsibilities:

• Build and maintain strategic relationships with key university decision-makers while serving as the primary point of contact between universities and Anthropic, navigating complex academic stakeholder ecosystems including faculty, administrators, IT departments, and procurement offices.

• Become an expert in Anthropic's products across API, Claude for Enterprise, and Claude Code, understanding the technical nuances and best practices for each to guide customers to the right solutions

• Monitor usage patterns and proactively drive adoption—identifying optimization opportunities, addressing underutilization across consumption-based (API) and seat-based products, and discovering new applications for Claude across departments and workflows

• Develop and execute change management strategies appropriate for universities, driving adoption through Train the Trainer programs, Center of Excellence development, and organizational enablement that respects education institutions constraints and decision-making processes

• Create and maintain enablement resources —identifying opportunities to develop scalable assets that drive efficiency across the partner portfolio

• Serve as the customer’s thought partner, enhancing their knowledge of Claude products by socializing Anthropic’s product roadmap, driving awareness on new products and engaging Product PMs

• Identify and create opportunities for thought leadership and community activation, developing 1:many engagement programs such as webinars, cohort-based learning, and peer networking that extend impact beyond individual partner relationships

• Design initiatives that showcase impactful use cases for teaching, learning and research, and helping them embed and deploy AI while uncovering its full range of capabilities in teaching, research, and administration.

You may be a good fit if you have:

• 5+ years of experience in higher education technology, preferably in SaaS or emerging technologies, with a strong background in Customer Success

• Demonstrated ability to navigate academic bureaucracies and build consensus among diverse stakeholders including faculty, administrators, and IT departments

• Deep understanding of higher education buying cycles, decision-making processes, and key pain points, with a track record of driving adoption across academic institutions

• Excellent communication skills with the ability to translate technical concepts for various audiences, from faculty and researchers to senior administration

• Technical fluency with ability to understand and articulate AI/ML concepts, API integrations, and software implementation patterns

• Experience explaining and demonstrating technical products to various audiences

• Strategic mindset to identify growth opportunities and translate them into actionable expansion plans

• Strong cross-functional collaboration skills with ability to advocate effectively for customer needs

• Passion for both AI and social impact work, with strong interest in ensuring frontier AI systems are developed safely, ethically, and deployed to benefit society

• A knack for bringing order to chaos and an enthusiastic “roll up your sleeves'' mentality. You are a true team player

Responsibilities

• Contribute to the Industries team GTM strategy, identifying new use cases within your assigned verticals, winning new business, and sharing feedback with cross-functional teams
• Drive strategic expansion within key accounts in established verticals and new logo acquisition within emerging verticals
• Break into new accounts and cross-sell into existing business alongside our team of Account Executives
• Own a revenue target and all aspects of the sales cycle from prospecting to close, including outbounding and engaging Tier 1 accounts
• Lead with conviction by providing clear recommendations based on deep industry expertise rather than presenting a menu of options
• Prioritize organizations that can serve as lighthouse customers and references within their industries
• Become a trusted advisor to customers, understanding their unique needs and crafting tailored AI solutions. Co-innovate with customers and sell on the product roadmap while appropriately setting expectations
• Collaborate extensively with cross-functional partners including product, engineering, legal, marketing, and Applied AI to help bring new solutions to market and provide feedback to shape roadmaps
• Develop sales collateral, proposals, and presentations to effectively position Anthropic's AI products. Continuously refine sales tactics and share best practices

You may be a good fit if you have

• 8+ years of enterprise software sales experience, with a track record of owning named accounts at large, complex organizations
• Experience managing multi-quarter sales cycles involving multiple stakeholders, technical evaluations, and enterprise procurement
• A history of growing accounts meaningfully beyond the original engagement by creating demand across new divisions and use cases
• Demonstrated ability to independently build and advance relationships at the C-suite and SVP level, including preparing for and leading executive conversations without relying on internal executive sponsorship
• Experience building customer-specific business cases grounded in the customer's own financials and priorities, and defending commercial terms through procurement
• Background selling platform, API, cloud infrastructure, or emerging technology into enterprises evaluating a new category
• Strong executive presence and the ability to hold a credible conversation across both technical and business audiences
• Genuine interest in AI and strong alignment with Anthropic's mission of developing AI systems that are safe and beneficial

What will make you stand out

• Direct experience selling into one or more of our core verticals and fluency in how those businesses operate and measure success
• Experience as an early AE in a vertical or segment, where you helped build the sales motion rather than inherit it
• Background selling developer platforms, cloud infrastructure, or AI/ML tooling into traditional enterprises

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

About the role

Join Anthropic's Customer Success team in a high-impact role driving AI adoption across our Industry segment. As an Enterprise Customer Success Manager for Industries, you'll be the strategic partner and a trusted advisor to our most complex customers with a portfolio spanning Financial Services, Systems Integrators, Semiconductor, Manufacturing and Retail organizations—helping them harness the full potential of all our Claude capabilities - API, Claude for Enterprise, and Claude Code.

You'll work with organizations across diverse industries that are transforming their businesses with AI technology. Developing genuine partnerships with customers, gaining a deep understanding of their business objectives, strategic direction, AI vision, and technical needs. You'll draw on both your business acumen and technical expertise to serve as a strategic advisor throughout their journey with us.

In partnership with the broader account team you will help customers identify the right Claude capabilities for their specific business objectives, working closely with them to provide best practices and guidance while supporting them as their usage (consumption & seat based) grows and evolves.

Your role focuses on helping customers scale their usage effectively, drive model and use case optimizations, implement change management strategies, and maximize the value of their investment through expanded use cases across their organization. The insights you gather from your customers will directly inform our research priorities, product development, and go-to-market strategies — making you a key voice in shaping how we build and deliver ongoing value as a business.

Responsibilities:

• Build trusting, strategic relationships with key customer decision makers to understand their business and objectives, identifying opportunities for optimization and expansion
• Become an expert in Anthropic's products across API, Claude Code and Claude for Enterprise, understanding the technical nuances and best practices for each to guide customers to the right solutions
• Leverage your deep knowledge of the customer and their industry vertical to proactively drive usage planning, understanding current and future consumption/adoption and how it creates realized value for the customer
• Monitor usage patterns and identify optimization opportunities, proactively addressing underutilization across both consumption-based (API) and seat-based (Claude for Enterprise / Claude Code) products to drive full value from contracted commitments
• Serve as the customer's thought partner, enhancing their knowledge of Claude products by socializing Anthropic's product roadmap, driving awareness on new products and engaging Product PMs
• Document and quantify customer value realized through business outcomes, ROI, and impact metrics to build compelling internal business cases for continued and expanded investment
• Identify potential use cases and lines of business not currently onboarded, partnering with customers and Sales to discover new applications for Claude across different departments, teams, and workflows
• Develop and execute change management strategies to drive end-user adoption and maximize value within customer organizations, including Train the Trainer programs, Center of Excellence development, and organizational enablement
• Own the customer experience across their lifecycle — managing comprehensive account and success plans grounded in the customer's business objectives, conducting Quarterly Business Reviews, and serving as the primary conduit between the customer and Anthropic
• Develop scalable engagement strategies and playbooks for your Industry portfolio, balancing high-touch strategic accounts with efficient coverage models to maximize impact across all customers

You may be a good fit if you have:

• 6+ years of experience in Customer Success, Technical Account Management, or Solutions Engineering
• Experience working with enterprises in Financial Services, Systems Integrators, Semiconductor, Manufacturing or Retail industries
• Technical fluency with ability to understand and articulate AI/ML concepts, API integrations, and software implementation patterns across a set of diverse stakeholders—from developers and product managers to executives and end users
• Experience driving success across both consumption-based and seat-based business models, with understanding of different expansion levers and success metrics for each
• Strategic mindset to identify growth opportunities and translate them into actionable expansion plans
• Proven track record managing a portfolio of accounts while maintaining strong relationships and driving measurable outcomes
• Cross-functional collaborator who represents the customer in a positive, proactive manner, rallying everyone around paths forward that solve customer needs
• Passion for AI and interest in responsible development of advanced systems
• A knack for bringing order to chaos and an enthusiastic "roll up your sleeves" mentality—you're a true team player

About the Role

About the role

We are looking for a Research Engineer to help us train Claude specifically for virtual collaborator workflows. While Claude excels at general tasks, a lot of knowledge work requires targeted training on real organizational data and workflows. Your job will be to design and implement reinforcement learning (RL) environments that transform Claude into the best virtual collaborator, training on realistic tasks from navigating internal knowledge to creating financial models.

Responsibilities:

• Training Claude on document manipulation with good taste, including understanding, enhancing, and co-creating (e.g., Office doc formats, data visualization)
• Designing and implementing reinforcement learning pipelines targeted at virtual collaborator use cases (productivity, organizational navigation, vertical domains)
• Building and scaling our data creation platform for generating high-quality, open-ended tasks with domain experts and crowdworkers Integrating real organizational data to create realistic training environments
• Developing robust evaluation systems that maintain quality while avoiding reward hacking
• Partnering directly with product teams (e.g., Cowork, claude.ai) to ensure training aligns with product features

You may be a good fit if you:

• Are a very experienced Python programmer who can quickly produce reliable, high quality code that your teammates love using
• Have 5-8 years of strong machine learning experience
• Thrive at the intersection of research and product, with a pragmatic approach to solving real-world problems
• Are comfortable with ambiguity and can balance research rigor with shipping deadlines
• Enjoy collaborating across multiple teams (data operations, model training, product)
• Can context-switch between research problems and product engineering tasks
• Care about making AI genuinely helpful for everyday enterprise workflows

Strong candidates may also have experience with:

• Creating RL envs for realistic tasks.
• Reward modeling and preventing reward hacking
• Building human-in-the-loop training systems or crowdsourcing platforms
• Working with enterprise tools and APIs (Google Workspace, Microsoft Office, Slack, etc.)
• Developing evaluation frameworks for open-ended tasks
• Domain expertise in finance, legal, or healthcare workflows 
• Creating scalable data pipelines with quality control mechanisms
• Translating product requirements into technical training objectives 

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

About the role

Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with.

You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models.

Note: For this role, we conduct all interviews in Python. This role may require responding to incidents on short-notice, including on weekends.

Responsibilities:

• Implement and optimize post-training techniques at scale on frontier models
• Conduct research to develop and optimize post-training recipes that directly improve production model quality
• Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation
• Develop tools to measure and improve model performance across various dimensions
• Collaborate with research teams to translate emerging techniques into production-ready implementations
• Debug complex issues in training pipelines and model behavior
• Help establish best practices for reliable, reproducible model post-training

You may be a good fit if you:

• Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities
• Adapt quickly to changing priorities
• Maintain clarity when debugging complex, time-sensitive issues
• Have strong software engineering skills with experience building complex ML systems
• Are comfortable working with large-scale distributed systems and high-performance computing
• Have experience with training, fine-tuning, or evaluating large language models
• Can balance research exploration with engineering rigor and operational reliability
• Are adept at analyzing and debugging model training processes
• Enjoy collaborating across research and engineering disciplines
• Can navigate ambiguity and make progress in fast-moving research environments

Strong candidates may also:

• Have experience with LLMs
• Have a keen interest in AI safety and responsible deployment

We welcome candidates at various experience levels, with a preference for senior engineers who have hands-on experience with frontier AI systems. However, proficiency in Python, deep learning frameworks, and distributed computing is required for this role.

About the role

Anthropic's Safeguards team is responsible for the systems that allow us to deploy powerful AI models responsibly — and the data infrastructure underneath those systems is foundational to getting that right. The Safeguards Data Infrastructure team owns the offline data stack that underpins our safeguards work: the storage layer for sensitive user data, the tooling built on top of it, and the interfaces that let the rest of the Safeguards organization access that data safely and ergonomically.

As Engineering Manager of this team, you'll be responsible for ensuring full portability of our safeguards data stack across an expanding set of deployment environments, building privacy-preserving data interfaces that enable ML and training workflows, and driving compliance with data regulations including HIPAA. This is a role at the intersection of infrastructure engineering, data privacy, and enterprise product requirements — and it sits at a critical juncture as Anthropic scales into new cloud environments and geographies

Responsibilities:

• Lead and grow a team of engineers delivering the data infrastructure and tooling that powers Anthropic's safeguards capabilities
• Own the strategy and execution for porting the safeguards offline data stack — including PII storage and tooling — across new cloud and deployment environments as Anthropic expands
• Build and maintain privacy-safe data APIs and interfaces that enable ML and training workflows while respecting data retention and access constraints
• Drive tooling and architecture decisions that maximize data retention within the bounds of our privacy and compliance requirements
• Manage privacy incident response processes and partner with compliance teams on regulatory requirements (e.g. HIPAA, EU privacy regulations)
• Collaborate closely with enterprise customers and product teams on zero data retention offerings, working balancing safety needs with robust enterprise data contracts
• Independently own and drive multiple workstreams, including planning, execution, and cross-team coordination
• Coach, mentor, and support the career development of your direct reports, helping them set and achieve their professional goals
• Partner with recruiting to attract, hire, and retain strong engineering talent

You may be a good fit if you:

• Have 4+ years of front-line engineering management experience
• Have a track record of leading teams that build and operate data infrastructure at scale
• Have hands-on software engineering experience as an individual contributor prior to moving into management
• Have a strong understanding of data privacy principles, PII handling, and compliance frameworks
• Are comfortable driving technical decisions in an ambiguous, fast-moving environment with competing priorities
• Have experience working cross-functionally across infrastructure, product, and compliance or security teams
• Are clear and persuasive communicators, both in writing and in person

Strong candidates may also:

• Have experience with multi-cloud or multi-region data portability, particularly in regulated environments
• Have built privacy-preserving data pipelines or interfaces for ML workloads
• Have experience with enterprise data contracts or zero data retention architectures
• Have explored novel approaches to data processing under strict access constraints, such as in-memory storage and compute for sensitive data
• Have a passion for building diverse and inclusive teams

About the Role

Anthropic's Human Data Interfaces team builds the systems that collect data to improve our models. This includes novel interfaces for data vendors, tooling, and front-end and back-end infrastructure that enables researchers to gather high-quality data at scale. As a Software Engineer, you'll own the architecture and execution of our data collection pipelines — designing systems that are both performant at scale and resilient to the rapidly changing needs of our research teams. You'll work closely with researchers, our cross-functional data operations partners, and the crowdworkers and vendors who use these tools day-to-day.

Responsibilities:

• Architect and build data collection pipelines that support rapid iteration, balancing data quality and system maintainability

• Think deeply about the experience of the crowdworkers and vendors using these systems, building interfaces that are clear, efficient, and lead to high-quality data

• Collaborate closely with research teams to understand evolving data needs and iterate quickly on collection methods

• Partner with our Human Data Operations team to understand the end-to-end data workflow and design interfaces that make their jobs easier

• Prioritize and juggle multiple workstreams, making trade-off decisions in a fast-moving environment where research priorities can shift quickly

You May Be a Good Fit If You:

• Believe that advanced AI systems could have a transformative effect on the world and are interested in helping make sure that transformation goes well

• Are a strong full-stack engineer with broad experience across the stack

• Are very good at building internal tools, including working with users of the tools to understand their needs

• Thrive in fast-moving environments where you need to balance speed of iteration with long-term system health

• Are a quick study—this team sits at the intersection of a large number of different complex technical systems that you'll need to understand (at a high level) to be effective

Strong Candidates May Also Have:

• Experience building human data labelling interfaces, human-in-the-loop systems, or data collection pipelines

• Familiarity with how preference data and reward models are used in AI model training

• Experience working with researchers who are internal users/customers 

• Background in building, and improving the user-experience of user-facing applications, particularly those involving complex UI interactions or annotation workflows

• Strong instincts around system design — building things that evolve gracefully as requirements change

• Experience influencing technical and product direction on a team

About the Team

Our team is organized around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier. Our team likes to think across the whole model stack. Currently the team is focused on improving models' abilities to use computers – as a laboratory for long horizon tasks and a key blocker to many scientific workflows.

About the role

As a Research Engineer on our team you will work end to end, identifying and addressing key blockers on the path to scientific AGI. Strong candidates should have familiarity with language model training, evaluation, and inference, be comfortable triaging research ideas and diagnosing problems and enjoy working collaboratively. Familiarity with performance optimization, distributed systems, vm/sandboxing/container deployment, and large scale data pipelines is highly encouraged.

Join us in our mission to develop advanced AI systems that are both powerful and beneficial for humanity. 

Responsibilities: 

• Working across the full stack to identify and remove bottlenecks preventing progress toward scientific AGI
• Develop approaches to address long-horizon task completion and complex reasoning challenges essential for scientific discovery
• Scaling research ideas from prototype to production
• Create benchmarks and evaluation frameworks to measure model capabilities in scientific workflows and computer use
• Implement distributed training systems and performance optimizations to support large-scale model development

You may be a good fit if you:

• Have 8+ years of ML research experience
• Are familiar with large scale language model training, evaluation, and inference pipelines
• Enjoy obsessively iterating on immediate blockers towards longterm goals
• Thrive working collaboratively to solve problems
• Have expertise in performance optimization and distributed computing systems
• Show strong problem-solving skills and ability to identify technical bottlenecks in complex systems
• Can translate research concepts into scalable engineering solutions
• Have a track record of shipping ML systems that tackle challenging multi-step reasoning problems

Strong candidates may also have:

• Expertise with performance optimization for language model inference and training
• Experience with computer use automation and agentic AI systems
• A history working on reinforcement learning approaches for complex task completion
• Knowledge of containerization technologies (Docker, Kubernetes) and cloud deployment at scale
• Demonstrated ability to work across multiple domains (language modeling, systems engineering, scientific computing)
• Have experience with VM/sandboxing/container deployment and large-scale data processing
• Experience working with large scale data problem solving and infrastructure
• Published research or practical experience in scientific AI applications or long-horizon reasoning

Responsibilities:

• Win new business and drive revenue for Anthropic. Find your way to the right people at prospective customers, educate them about LLMs, and help them succeed with Anthropic. You’ll own the full sales cycle, from first outbound to launch
• Design and execute innovative sales strategies to meet and exceed revenue quotas. Analyze market landscapes, trends, and dynamics to translate high-level plans into targeted sales activities, partnerships, and campaigns
• Spearhead market expansion by pinpointing new customer segments and use cases. Collaborate cross-functionally to differentiate our offerings and sustain a competitive edge
• Inform product roadmaps and features by gathering customer feedback and conveying market needs. Provide insights that strengthen our value proposition and enhance the customer experience
• Continuously refine the sales methodology by incorporating learnings into playbooks, templates, and best practices. Identify process improvements that optimize sales productivity and consistency

You may be a good fit if you have:

• 2-3 years of experience prospecting and closing startup leads, driving adoption of emerging technologies with a consultative, solutions-oriented sales approach
• Familiarity working within complex sales cycles, selling to technical stakeholders, and securing strategic deals by understanding multifaceted technical requirements and crafting tailored solutions
• Success as a strategic business advisor, deeply understanding the needs of startup founders and creating innovative solutions that align with their vision and help them succeed
• Exposure to negotiating complex, customized commercial agreements with multiple stakeholders
• Demonstrated history of exceeding quota by effectively qualifying and advancing opportunities in a fast-paced work environment
• Excellent communication skills and the ability to present confidently and build connections across all customer levels, from ICs to C-level executives
• A knack for bringing order to chaos and an enthusiastic “roll up your sleeves'' mentality. You are a true team player
• Analytical approach to understanding customer needs combined with creative follow-up to advance opportunities
• Passion for emerging technologies like AI, with interest in ensuring they are developed safely and responsibly
• A strategic, analytical approach to assessing markets combined with creative, tactical execution to capture opportunities
• A passion for and/or experience with advanced AI systems. You feel strongly about ensuring frontier AI systems are developed safely

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

At Anthropic, we are building some of the most complex and large-scale AI infrastructure in the world. As that infrastructure scales rapidly, so does the imperative to optimize how we use it. As a Software Engineer for Compute Efficiency on the Capacity team, you will play a central role in making our systems more performant, cost-effective, and sustainable—without compromising reliability or latency.

You will work across the full infrastructure stack, from cloud platforms and networking to application-level performance, and will bridge the gap between high-level research needs and low-level hardware constraints to build the most efficient AI infrastructure in the world. You will help with building the telemetry, cost attribution, and optimization frameworks that ensure every dollar of our infrastructure investment delivers maximum value. This is a high-impact, cross-functional role at the intersection of systems engineering, financial optimization, and AI infrastructure.

Responsibilities:

• Build and evolve telemetry and monitoring systems to provide deep visibility into infrastructure performance, utilization, and costs across our cloud and datacenter fleets.

• Design and implement cost attribution frameworks for our multi-tenant infrastructure, enabling teams to understand and optimize their resource consumption.

• Identify and resolve performance bottlenecks and capacity hotspots through deep analysis of distributed systems at scale.

• Partner closely with cloud service providers and internal stakeholders to optimize cluster configurations, workload placement, and resource utilization across AI training and inference workloads—including large-scale clusters spanning thousands to hundreds of thousands of machines.

• Develop and champion engineering practices around efficiency, driving a culture of performance awareness and cost-conscious design across Anthropic.

• Collaborate with research and product teams to deeply understand their infrastructure needs, and design solutions that balance performance with cost efficiency.

• Drive architectural improvements and code-level optimizations across multiple services and platforms to deliver measurable utilization and performance gains.

You may be a good fit if you:

• Have 6+ years of relevant industry experience, 1+ year leading large scale, complex projects or teams as a software engineer or tech lead

• Deep expertise in distributed systems at scale, with a strong focus on infrastructure reliability, scalability, and continuous improvement.

• Strong proficiency in at least one programming language (e.g., Python, Rust, Go, Java)

• Hands-on experience with cloud infrastructure, including Kubernetes, Infrastructure as Code, and major cloud providers such as AWS or GCP.

• Experience optimizing end-to-end performance of distributed systems, including workload right-sizing and resource utilization tuning.

• You possess a deep curiosity for how things work under the hood and have a proven ability to work independently to solve opaque performance issues

• Experience designing or working with performance and utilization monitoring tools in large-scale, distributed environments.

• Strong problem-solving skills with the ability to work independently and navigate ambiguity.

• Excellent communication and collaboration skills—you will work closely with internal and external stakeholders to build consensus and drive projects forward.

Strong candidates may have:

• Experience with machine learning infrastructure workloads as well as associated networking technologies like NCCL.

• Low level systems experience, for example linux kernel tuning and eBPF 

• Quickly understanding systems design tradeoffs, keeping track of rapidly evolving software systems

• Published work in performance optimization and scaling distributed systems

About the role

As an Enterprise Account Executive at Anthropic, you’ll drive adoption of safe, frontier AI by securing strategic deals with top enterprises, unlocking new value streams throughout their business. You’ll leverage your consultative sales expertise to propel revenue growth while becoming a trusted partner to customers, helping them embed and deploy AI while uncovering its full range of capabilities. In collaboration with GTM, product, and marketing teams, you’ll continuously refine our value proposition, sales methodology, and market positioning to ensure differentiated value across the landscape.

The ideal candidate will have a passion for developing new market segments, pinpointing high-potential opportunities, and executing strategies to capture them. By driving deployment of Anthropic's emerging products, you will help enterprises obtain new capabilities while also advancing the ethical development of AI.

Responsibilities:

• Win new business and drive revenue for Anthropic. Find your way to the right people at prospective customers, educate them about LLMs, and help them succeed with Anthropic. You’ll own the full sales cycle, from first outbound to launch

• Design and execute innovative sales strategies to meet and exceed revenue quotas. Analyze market landscapes, trends, and dynamics to translate high-level plans into targeted sales activities, partnerships, and campaigns

• Spearhead market expansion by pinpointing new customer segments and use cases. Collaborate cross-functionally to differentiate our offerings and sustain a competitive edge

• Inform product roadmaps and features by gathering customer feedback and conveying market needs. Provide insights that strengthen our value proposition and enhance the customer experience

• Continuously refine the sales methodology by incorporating learnings into playbooks, templates, and best practices. Identify process improvements that optimize sales productivity and consistency

You may be a good fit if you:

• 5+ years of enterprise sales experience driving adoption of emerging technologies with a consultative, solutions-oriented sales approach

• A track record of managing complex sales cycles and securing strategic deals by understanding multifaceted technical requirements and crafting tailored solutions

• Demonstrated ability to navigate dynamic stakeholder ecosystems, building consensus and providing innovative solutions to disparate groups

• Extensive experience negotiating highly complex, customized commercial agreements with multiple stakeholders

• Proven experience exceeding revenue targets in fast-paced organizations by effectively managing an evolving pipeline and sales process

• Excellent communication skills and the ability to present confidently and build connections across all customer levels, from ICs to C-level executives

• A knack for bringing order to chaos and an enthusiastic “roll up your sleeves'' mentality. You are a true team player

• A strategic, analytical approach to assessing markets combined with creative, tactical execution to capture opportunities

• A passion for and/or experience with advanced AI systems. You feel strongly about ensuring frontier AI systems are developed safely

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

About the Role

As a Strategic Account Executive focused on cybersecurity, you'll own some of Anthropic's most strategic cybersecurity relationships—companies building the next generation of AI-powered security products. These aren't typical enterprise accounts; they're partners shaping how AI transforms the entire security industry.

You'll drive multi-million dollar commitments by expanding Claude's footprint across customer product portfolios (AI-powered SOC, threat detection, security copilots) and internal operations (Claude Code for engineering teams). You'll work at the intersection of executive relationships and technical depth—one week you're in a CTO strategy session, the next you're helping an engineering team scope an agentic deployment.

This role requires someone who can think like a partner, not just a seller. You'll collaborate closely with our Applied AI team on custom deployments, work with Product on cybersecurity-specific capabilities, and help shape Anthropic's go-to-market in one of our highest-potential verticals.

Responsibilities:

• Win business and drive revenue within a book of strategic cybersecurity accounts.Own the full sales cycle from prospecting to close

• Drive expansion across multiple buying centers within strategic accounts—product teams building customer-facing AI features, platform teams deploying Claude Code to engineering orgs, and security research teams exploring frontier capabilities

• Navigate complex organizational structures across security, product, engineering, and executive teams. Build multi-threaded relationships with CISOs, security architects, product and engineering leaders, and C-suite executives

• Partner with Solutions Architect and Product teams on technical scoping, custom agent development, and enterprise deployments

• Design and execute innovative sales strategies tailored to the cybersecurity market. Analyze account landscape, competitive dynamics, and emerging security trends to inform targeted sales activities

• Identify and develop use cases across security operations (SecOps automation, threat hunting, alert triage), security product development (AI-powered detection, intelligent response), and internal security functions

• Navigate unique considerations of AI in security contexts, including model guardrails, responsible deployment, and emerging use cases like AI red-teaming

• Own sophisticated deal cycles involving security evaluations, red team assessments, and complex procurement processes. Navigate security and compliance requirements with patience and expertise

• Build and maintain accurate pipeline forecasting for complex, multi-workstream accounts. Develop deep understanding of how large security vendors budget for AI infrastructure across product and internal use cases

• Serve as the voice of the cybersecurity customer internally. Inform product roadmaps by gathering feedback on security-specific requirements, compliance needs, and competitive gaps

• Develop cybersecurity-specific sales playbooks, case studies, and best practices. Contribute to building Anthropic's reputation as a trusted partner in the security ecosystem

You May Be a Good Fit If You Have:

• 8+ years of enterprise sales experience with a proven track record of closing complex deals, including at least 3 years selling to or within the cybersecurity industry

• Deep understanding of the cybersecurity landscape including key market segments (endpoint, cloud security, SIEM/SOAR, identity, threat intelligence), major players, and emerging trends

• Experience selling to security-focused buyers (CISOs, security architects, SOC leaders) and navigating security-specific procurement processes

• Strong executive presence with demonstrated ability to engage C-suite executives, board members, and senior security leaders. Ability to articulate both technical value and business impact

• Experience with security and compliance frameworks (SOC 2, FedRAMP, ISO 27001) and comfort discussing data handling, model security, and responsible AI deployment

• Consultative sales approach with ability to understand complex security challenges and craft tailored solutions. Position yourself as a strategic advisor on AI adoption in security contexts

• Strong cross-functional collaboration skills with ability to mobilize internal resources including product, engineering, security, and legal teams for complex deals

• Resourcefulness and creative problem-solving when faced with security objections, compliance requirements, or technical challenges unique to the security vertical

• Passion for both AI and cybersecurity with enthusiasm for helping security organizations transform through responsible AI deployment. Strong alignment with Anthropic's mission of developing safe, beneficial AI systems

Nice to Have

• Prior experience at a cybersecurity vendor or in a security-focused role

• Technical background or certifications in cybersecurity (CISSP, CISM, or similar)

• Existing relationships with CISOs and security leaders at target accounts

• Experience selling AI/ML solutions into security use cases

About the role:

Anthropic’s performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training.  As an Engineering Manager on these teams you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems.  You also will help bring clarity, focus, and context to your teams in a fast paced, dynamic environment.

Responsibilities:

• Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems
• Become familiar with the team’s technical stack enough to make targeted contributions as an individual contributor
• Manage day-to-day execution of the team's work
• Prioritize the team’s work and manage projects in a highly dynamic, fast paced environment
• Coach and support your reports in understanding, and pursuing, their professional growth
• Maintain a deep understanding of the team's technical work and its implications for AI safety

You may be a good fit if you:

• Have 1+ years of management experience in a technical environment, particularly performance or distributed systems
• Have a background in machine learning, AI, or a similar related technical field
• Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
• Excel at building strong relationships with stakeholders at all levels
• Are a quick learner, capable of understanding and contributing to discussions on complex technical topics
• Have experience managing teams through periods of rapid growth and change
• Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level of abstraction) to be effective

Strong candidates may also have experience with: 

• High performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

You may be a good fit if you:

• Have significant software engineering or machine learning experience, particularly at supercomputing scale
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to learn more about machine learning research
• Care about the societal impacts of your work

Strong candidates may also have experience with: 

• High performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

Representative projects:

• Implement low-latency high-throughput sampling for large language models
• Implement GPU kernels to adapt our models to low-precision inference
• Write a custom load-balancing algorithm to optimize serving efficiency
• Build quantitative models of system performance
• Design and implement a fault-tolerant distributed system running with a complex network topology
• Debug kernel-level network latency spikes in a containerized environment

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

About the role:

Anthropic’s performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training.  As an Engineering Manager on these teams you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems.  You also will help bring clarity, focus, and context to your teams in a fast paced, dynamic environment.

Responsibilities:

• Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems
• Become familiar with the team’s technical stack enough to make targeted contributions as an individual contributor
• Manage day-to-day execution of the team's work
• Prioritize the team’s work and manage projects in a highly dynamic, fast paced environment
• Coach and support your reports in understanding, and pursuing, their professional growth
• Maintain a deep understanding of the team's technical work and its implications for AI safety

You may be a good fit if you:

• Have 1+ years of management experience in a technical environment, particularly performance or distributed systems
• Have a background in machine learning, AI, or a similar related technical field
• Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
• Excel at building strong relationships with stakeholders at all levels
• Are a quick learner, capable of understanding and contributing to discussions on complex technical topics
• Have experience managing teams through periods of rapid growth and change
• Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level of abstraction) to be effective

Strong candidates may also have experience with: 

• High performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers