Anthropic has 145 active AI-related job listings. The majority of these roles are focused on agents, comprising 28% of the total. Engineering is the most frequent function, with 74 listings, followed by Research with 51. The company is primarily hiring in the United States, with 118 positions, and the United Kingdom, with 22. Frequent tech tags include model_serving, evals, and agent_orchestration, suggesting a focus on deployment and evaluation of AI systems. In the last 30 days, Anthropic posted 16 new AI roles, a 47% decrease compared to the previous 30-day period.
Currently tracking 124 active AI roles, with 106 new openings in the last 4 weeks. Primary focus: Agent · Engineering. Salary range $46k–$850k (avg $405k).
Anthropic currently has 132 active AI-related roles in our index. The most common open titles are: Applied AI Architect, Industries (2), Regional Research Economist, Economic Research (2), Research Engineer, Machine Learning (RL Velocity) (2), Research Engineer, Production Model Post-Training (2), Staff Software Engineer, AI Reliability Engineering (2). Most positions are in Engineering and Research.
Anthropic's active AI hiring is concentrated in: agents (28%), serving infrastructure (17%), post-training (14%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Anthropic is hiring AI talent in: United States (106 roles), United Kingdom (20 roles), Canada (6 roles), Ireland (5 roles).
Job postings at Anthropic most frequently reference: model serving, evals, llm observability, agent orchestration, inference infra.
In the past 30 days, Anthropic has posted 29 new AI-related roles. That is a +61% change versus the prior 30 days (18 → 29).
| Title | Stage | AI score |
|---|---|---|
| Staff+ Software Engineer, Inference Runtime Staff+ Software Engineer for Anthropic's Inference Runtime team, focusing on the accelerator-agnostic core of their AI inference serving stack. The role involves setting technical direction, owning the architecture and roadmap, hands-on coding in Rust/Python, optimizing accelerator usage, and building validation systems. Requires deep systems engineering or ML infrastructure background with experience in performance optimization and large-scale distributed systems. | Serve | 9 |
| Security Labs Engineer This role focuses on executing security R&D projects end-to-end, building novel security infrastructure, and driving successful experiments toward production scale. It involves working with research teams to test security controls, evaluating new security technologies, and documenting results to inform future security architecture. The role spans from initial project scoping to potential production deployment, with a focus on high-assurance environments and AI-assisted security tooling. |
| ServeShip |
| 9 |
| Performance Engineer, GPU This role focuses on optimizing GPU performance and systems engineering for large language models, specifically improving utilization and efficiency for inference and training at scale. It involves deep work in GPU programming, custom kernel development, and distributed systems. | ServePretrain | 9 |
| Engineering Manager, GPU (ML Accelerator) Engineering Manager for Anthropic's performance and scaling teams, focusing on optimizing compute resources for inference and training systems. The role involves leadership, technical contribution, bottleneck identification, and ensuring efficiency in large-scale ML systems, with a strong emphasis on GPU/accelerator programming and ML/OS internals. | ServeData | 9 |
| Engineering Manager, ML Performance and Scaling Engineering Manager for ML Performance and Scaling teams, focusing on optimizing inference and training systems, identifying bottlenecks, and maximizing efficiency. Requires management experience, background in ML/AI, and interest in safe AI development. | ServePost-train | 9 |
| TPU Kernel Engineer TPU Kernel Engineer responsible for identifying and addressing performance issues across ML systems (research, training, inference), with a focus on designing and optimizing kernels for TPUs. Provides feedback to researchers on model performance impact. | ServePost-train | 9 |
| Research Engineer, Discovery Research Engineer focused on building and optimizing infrastructure for AI scientist training, evaluation, and inference. The role involves identifying and resolving infra blockers, developing evaluation frameworks, managing data pipelines, and optimizing training/inference for reinforcement learning in distributed environments. | ServeData | 9 |
| TPU Kernel Engineer This role focuses on optimizing ML systems, particularly for TPUs, by designing and implementing kernels to improve performance for research, training, and inference. It involves low-level optimization and providing feedback on model performance impacts. | ServePost-train | 9 |
| Engineering Manager, Cloud Safety Engineering Manager to lead the Cloud Safety team, responsible for scaling and optimizing Claude's serving infrastructure across Cloud Service Providers (CSPs). The role involves owning end-to-end safety, including API, inference, classifiers, fraud detection, data management, and operations, to ensure safe usage and enable the launch of new models and features at scale. | Serve | 8 |
| Staff Software Engineer, Cloud Inference Safeguards Staff Software Engineer to build and operate safety, oversight, and intervention mechanisms for AI models (Claude) on third-party cloud service provider (CSP) platforms. This role ensures requests are monitored for misuse, enforced against policy, and compliant with data residency and privacy commitments. The engineer will integrate Safeguards into the CSP inference serving path, focusing on real-time enforcement, telemetry, and privacy architecture, while maintaining serving-path latency and scale. The work directly impacts the ability to ship frontier models on CSP platforms safely. | ServeEval Gate | 8 |
| Sr. Software Engineer, Inference Software Engineer focused on building and maintaining the critical systems that serve Claude to millions of users worldwide. Responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators, maximizing compute efficiency and enabling research. | Serve | 8 |
| Staff Software Engineer, Inference Staff Software Engineer on the Inference team responsible for building and maintaining systems that serve Claude to millions of users. Focuses on maximizing compute efficiency and providing high-performance inference infrastructure for research, tackling complex distributed systems challenges across diverse AI accelerators. | Serve | 8 |
| Engineering Manager, Cloud Inference AWS Engineering Manager to lead the Cloud Inference team for AWS, responsible for scaling and optimizing Claude's inference, API, load balancing, capacity, and operations on AWS. The role ensures LLMs meet performance, safety, and security standards, and enhances global inference technology deployment. It focuses on increasing operational scale and accelerating the launch of new models and features. | Serve | 8 |
| Staff Software Engineer, Inference Staff Software Engineer on the Inference team responsible for building and maintaining systems that serve Claude to millions of users. Focuses on maximizing compute efficiency and enabling research through high-performance inference infrastructure, involving distributed systems, request routing, and LLM inference optimization. | Serve | 8 |
| Staff Software Engineer, Inference Staff Software Engineer on the Inference team responsible for building and maintaining systems that serve Claude to millions of users. Focuses on maximizing compute efficiency and enabling research through high-performance inference infrastructure, tackling distributed systems challenges across diverse AI accelerators and cloud platforms. | Serve | 8 |
| Staff + Sr. Software Engineer, Inference The Inference team at Anthropic is responsible for building and maintaining the systems that serve Claude to millions of users. This involves managing the entire stack from request routing to fleet-wide orchestration across diverse AI accelerators, with a dual mandate of maximizing compute efficiency and enabling research breakthroughs. The role requires significant software engineering experience, particularly with distributed systems, and experience with LLM inference optimization. | Serve | 8 |
| Engineering Manager, AI Reliability Engineering Engineering Manager for AI Reliability Engineering at Anthropic, focused on managing a team that defines and achieves reliability metrics for internal and external AI products and services, including LLM serving and training systems. The role involves driving SLOs, overseeing monitoring, architecting high-availability infrastructure, leading incident response, and optimizing AI infrastructure costs. | ServePost-train | 8 |
| Engineering Manager - AI Reliability Engineering Manager for AI Reliability at Anthropic, leading a team focused on defining and achieving reliability metrics for large language model serving systems. This role involves overseeing monitoring, high-availability infrastructure, incident response, and cost optimization for AI infrastructure, while also pioneering the use of AI for reliability engineering. | Serve | 8 |
| Software Engineer, Inference Scalability and Capability Software Engineer focused on building and scaling inference systems for LLMs, optimizing compute efficiency, and developing new inference capabilities. This role involves complex distributed systems challenges across the inference stack, including request routing and prompt caching. | Serve | 8 |
| Engineering Manager, Inference Engineering Manager for Anthropic's performance and scaling teams, focusing on improving model performance and scaling inference and training systems. Responsibilities include front-line leadership, managing day-to-day execution, prioritizing work, and coaching reports. Requires management experience in technical environments, background in ML/AI, and interest in safe AI development. | ServeData | 8 |
| Senior Software Engineer, Inference Senior Software Engineer on the Inference team responsible for building and maintaining systems that serve Claude models to millions of users. Focuses on maximizing compute efficiency and providing high-performance inference infrastructure for research. | Serve | 8 |
| Software Engineer, ML Performance and Scaling Software Engineer focused on optimizing the throughput and robustness of large-scale distributed ML systems, requiring expertise in performance engineering and a willingness to learn ML. | Serve | 8 |
| Software Engineer, ML Performance and Scaling Software Engineer focused on optimizing the performance, throughput, and robustness of large-scale distributed ML systems, including implementing low-latency sampling, low-precision inference, and efficient serving algorithms. | Serve | 8 |
| Software Engineer, Inference Scalability and Capability Software Engineer focused on building and scaling inference systems for LLMs, optimizing performance, reliability, and compute efficiency. This role involves tackling complex distributed systems challenges across the inference stack, from request routing to caching, and supporting new model architectures and inference features. | Serve | 8 |
| Staff Software Engineer, AI Reliability Engineering Staff Software Engineer focused on AI Reliability Engineering, responsible for defining and achieving reliability metrics for Anthropic's AI systems, including LLM serving and training infrastructure. The role involves designing monitoring, high-availability serving systems, automated failover, incident response, and cost optimization for large-scale AI infrastructure. | Serve | 8 |
| Engineering Manager, Inference Scalability and Capability Engineering Manager for Inference Scalability and Capability team, responsible for building and maintaining critical systems that serve LLMs, focusing on scaling inference, ensuring reliability, optimizing compute, and developing new inference capabilities. Manages a team of engineers, drives operational excellence, facilitates advanced inference features, and partners with research, infrastructure, and product teams. | Serve | 8 |
| Staff Software Engineer, AI Reliability Engineering Staff Software Engineer focused on AI Reliability Engineering at Anthropic, responsible for defining and achieving reliability metrics for LLM serving and training systems. This includes designing monitoring, implementing high-availability infrastructure, leading incident response, and optimizing costs for large-scale AI infrastructure. | Serve | 8 |
| Software Engineer Software Engineer role focused on building and scaling large ML systems, improving infrastructure, efficiency, and tooling for AI research and development. The role emphasizes making safe, steerable, and trustworthy AI systems, with opportunities to work on various aspects of ML infrastructure and experiments. | Serve | 8 |
| Performance Engineer This role focuses on optimizing the performance, throughput, and robustness of large-scale distributed machine learning systems. The engineer will identify and solve novel systems problems, implement low-latency sampling, adapt models for low-precision inference, optimize serving efficiency, and design fault-tolerant distributed systems. While not directly building ML models, the role is critical for enabling ML algorithms to run efficiently at scale. | Serve | 8 |
| Staff + Senior Software Engineer, Inference Software Engineer focused on building and maintaining the distributed systems that serve large language models (like Claude) to millions of users. The role involves maximizing compute efficiency, enabling research through high-performance inference infrastructure, and integrating new AI hardware and model architectures. | Serve | 7 |
| Staff + Sr. Software Engineer, Cloud Inference This role focuses on building and optimizing backend services and infrastructure for serving large language models (LLMs) like Claude across multiple cloud service providers (CSPs). The engineer will be responsible for API integration, intelligent request routing, inference execution, capacity management, and day-to-day operations, ensuring reliability, cost-effectiveness, and performance at massive scale. The role involves cross-functional collaboration with internal teams and CSP partners, CI/CD automation, and analyzing observability data. | Serve | 7 |
| Performance Engineer, Inference Systems Performance Engineer for Anthropic's inference fleet (Claude), focusing on throughput, latency, reliability, and correctness. The role involves cross-layer performance investigations, improving correctness evaluation pipelines, building observability tools, and partnering with component teams to implement optimizations. Requires strong performance engineering, Python, and data analysis skills, with a genuine interest in correctness as an engineering discipline. | ServeEval Gate | 7 |
| Staff + Sr. Software Engineer, Cloud Inference Launch Engineering Staff + Sr. Software Engineer role focused on scaling and optimizing Claude's inference on cloud platforms (AWS, GCP, Azure). The role involves owning the end-to-end product of Claude on each cloud, including API integration, request routing, inference execution, capacity management, and day-to-day operations. Key responsibilities include validating inference server and load balancer changes, ensuring correctness, performance, and reliability across platforms, and driving down cycle times for model launches and feature integrations. The role requires strong software engineering experience in distributed systems and experience with cloud platforms, with a focus on building automation and test infrastructure for inference services. | Serve | 7 |
| Data Scientist, Supply This role focuses on optimizing compute allocation for AI systems by building testing frameworks, connecting compute decisions to user outcomes, and partnering with infrastructure and research teams. The goal is to ensure efficient use of scarce AI resources and translate data-driven insights into operational changes that impact how AI reaches users at scale. | Serve | 7 |
| Senior / Staff+ Software Engineer, Voice Platform Senior/Staff+ Software Engineer for Anthropic's Voice Platform, focusing on building and operating real-time streaming infrastructure, low-latency serving systems for speech models, and APIs for voice conversations with Claude. The role involves optimizing performance, ensuring reliability, and collaborating with research and product teams to bring audio models from research to production. | ServePost-train | 7 |
| Engineering Manager, Inference Routing and Performance Engineering Manager for Anthropic's Inference Routing and Performance team, responsible for the cluster-level routing and coordination plane for the company's inference fleet. The role focuses on optimizing throughput and efficiency of AI model serving through custom algorithms, quantitative modeling, and deep systems understanding. | Serve | 7 |
| Staff + Sr. Software Engineer, AI Reliability This role focuses on improving the reliability of AI serving systems, including infrastructure, API layers, and accelerators. Responsibilities include developing SLOs, designing monitoring and observability systems, assisting with high-availability infrastructure, leading incident response for critical AI services, and supporting safeguard model serving. The role requires strong distributed systems and reliability backgrounds, with experience in large-scale model serving infrastructure being a plus. | Serve | 7 |
| Technical Program Manager, Infrastructure Technical Program Manager for Anthropic's Infrastructure organization, focusing on coordinating complex programs across developer productivity, tooling, reliability, and operations for AI systems. The role involves driving strategic initiatives, improving developer workflows, ensuring system reliability, and bridging communication between research, engineering, and product teams. | Serve | 7 |
| Staff + Sr. Software Engineer, Inference Deployment This role focuses on building and maintaining the infrastructure for deploying AI inference code to production across various accelerator fleets (GPU, TPU, Trainium). The core responsibility is to create a continuous, unattended deployment system that optimizes for resource constraints, minimizes cycle time, and ensures reliability at scale. It involves capacity-aware scheduling, deployment observability, and self-service onboarding for new models. | Serve | 7 |
| Staff Software Engineer, AI Reliability Engineering Staff Software Engineer focused on AI Reliability Engineering for large language model serving systems. Responsibilities include developing SLOs, designing monitoring and observability systems, implementing high-availability infrastructure, and leading incident response for critical AI services. This role partners with teams across Anthropic to improve reliability across serving paths. | Serve | 7 |
| Technical Program Manager, Inference Performance Technical Program Manager focused on inference performance and efficiency for AI models, coordinating launches, managing dependencies, and optimizing runtime and accelerator performance across multiple hardware targets. | Serve | 7 |
| Staff + Sr. Software Engineer, Cloud Inference Staff + Sr. Software Engineer, Cloud Inference at Anthropic. This role focuses on scaling and optimizing Claude's inference across multiple cloud service providers (AWS, GCP, Azure). Responsibilities include designing and building serving infrastructure, collaborating with CSPs, developing CI/CD automation, creating abstraction layers for cost-effective inference management, capacity planning, and optimizing inference cost and performance. The role requires significant experience in large-scale distributed systems and cloud platforms, with a strong interest in inference. | Serve | 7 |
| Staff Software Engineer, AI Reliability Engineering Staff Software Engineer, AI Reliability Engineering at Anthropic. This role focuses on improving the reliability, robustness, and resilience of AI serving systems, specifically for large language models like Claude. Responsibilities include developing SLOs, designing monitoring and observability, assisting with high-availability infrastructure, leading incident response for critical AI services, and supporting the reliability of safeguard model serving. | Serve | 7 |
| Infrastructure Engineer, Sandboxing Infrastructure Engineer to join the Sandboxing team within the Research organization. This role will build and scale systems for safely executing AI-generated code and interactions in isolated environments, focusing on distributed systems at scale with strong security boundaries. | Serve | 7 |
| Staff Software Engineer, Systems Staff Software Engineer, Systems role at Anthropic focused on building and maintaining the infrastructure that supports AI clusters at massive scale. This includes compute uptime, resilience, networking, and reliability challenges, enabling frontier AI research and safe deployment to millions of users. The role requires deep knowledge of distributed systems, reliability, and cloud platforms, with experience in systems languages and leading infrastructure projects. | Serve | 7 |
| Principal Capacity Engineer, Compute This role focuses on capacity engineering for AI workloads, involving planning, forecasting, and optimization of global infrastructure. The engineer will design and deliver capacity management systems, build usage attribution, oversee planning tools and guardrails, model costs for research and training, identify efficiency opportunities, and partner with Finance and leadership for strategic decision-making. Experience with AI workload capacity, cross-functional projects, LLMs, and observability is preferred. | ServeData | 7 |
| Staff Software Engineer, AI Reliability Engineering Staff Software Engineer focused on AI Reliability Engineering, responsible for defining and achieving reliability metrics for Anthropic's AI products and services, including LLM serving and training systems. This involves designing monitoring, implementing high-availability infrastructure, leading incident response, and optimizing costs for large-scale AI infrastructure. | Serve | 7 |
| Engineering Manager - Privacy Infrastructure Engineering Manager to lead the Privacy Engineering team, responsible for designing and operating privacy infrastructure for user data across AI systems, including training and inference. The role involves building foundational privacy infrastructure, translating regulations into engineering reality, and enabling privacy by default for engineers. This is a management role focused on scaling the team and its charter. | ServeData | 5 |
| Senior Staff+ Software Engineer, Kubernetes Platform Staff Software Engineer on the Kubernetes Platform team at Anthropic, responsible for owning, operating, and extending large-scale Kubernetes clusters (hundreds of thousands of nodes) used for training, research, and serving frontier AI models. This includes custom scheduling plugins, scaling the control plane, and building core cluster services. The role requires deep Kubernetes experience and a track record in production distributed systems. | Serve | 5 |
| Staff+ Software Engineer, Platform Staff+ Software Engineer, Platform at Anthropic. This role focuses on building foundational primitives, infrastructure, and systems that accelerate product development and enable reliable, scaled shipping of AI products. Responsibilities include architecting and optimizing development infrastructure, service mesh, observability, CI/CD, multi-cloud operations, identity and authentication, tool call proxying, and API distributability. The role also involves building training systems for customer workload adaptation and working closely with research and agent platform teams. Requires 8+ years of experience in backend/platform engineering, distributed systems, cloud-native products, and proficiency in languages like Python, Go, or Rust. | Serve | 5 |