About the role

Anthropic's Detection Platform team is building the next-generation Linux endpoint security system that protects our AI research and production infrastructure. We're looking for a senior engineer to architect and implement node-layer security sensors, develop kernel-based detection systems for ML workloads, and build tooling that leverages Claude to transform how security operations work.

This is a high-ownership role on a small team. You'll design systems that run across our rapidly growing fleet with minimal performance overhead, partner closely with security and infrastructure engineers, and help shape the technical direction of endpoint detection at Anthropic.

Key responsibilities

• Build kernel-level security detections for our AI platform, including eBPF-based sensors for Linux endpoints
• Design and implement scalable data pipelines for ingesting and processing security telemetry across our infrastructure
• Architect monitoring solutions for production systems that minimize performance impact on ML workloads
• Prototype new security tooling and analytics capabilities, including applications of Claude to detection and response workflows
• Partner with security and infrastructure teams to translate requirements into reliable, maintainable systems
• Contribute to the growth of the Security team through code reviews, mentorship, and hiring
• Participate in an on-call rotation

Minimum qualifications

• Background in software engineering with a focus on security, infrastructure, Linux internals, and/or operating systems
• Ability to write maintainable and secure code in Rust and/or C/C++
• Strong understanding of operating system internals and OS security primitives
• Experience with test-driven development and CI/CD workflows
• Experience partnering with security teams to translate requirements into technical solutions
• Track record of leading technical projects with minimal guidance and bringing clarity to ambiguous problems

Preferred qualifications

• 7+ years of software engineering experience, with significant time spent on security, infrastructure, or operating systems work
• Direct experience with eBPF and kernel-level instrumentation
• Experience with detection-as-code workflows
• Experience with infrastructure-as-code tools such as Terraform or CloudFormation
• Background building security tooling from the ground up
• Experience implementing security monitoring solutions (SIEM, log aggregation, EDR)
• Background in detection engineering or security operations
• Experience with SOAR platform or security automation development
• Experience with data lake and database architecture, or query optimization over large datasets
• Experience with API design and internal platform development
• Track record of applying ML or AI to security problems
• Experience scaling security operations in a high-growth environment
• Experience contributing to hiring, mentorship, and engineering culture on a security team

About the Role: 

The Detection & Response (D&R) team plays a critical role in protecting our systems, users, and data from security threats. We’re looking for an experienced Technical Program Manager to own and evolve incident management within D&R. This is a senior-level specialization on the Technical Program Manager ladder, focused on how we detect, respond to, and learn from security and operational incidents.

You’ll be the driving force behind maturing and scaling our incident response lifecycle—from detection and triage through containment, remediation, and post-incident review. Critically, some of the highest-impact work in this role happens after the immediate response: gathering data on incident trends, reporting on patterns and root causes, and working cross-functionally across engineering, security, infrastructure, and product teams to ensure that broad fixes and systemic improvements are actually implemented. 

You won’t just manage incidents—you’ll make sure we get meaningfully better after each one.

Responsibilities: 

• Own the end-to-end D&R incident management program: detection workflows, response processes, escalation paths, communication standards, and remediation tracking.
• Serve as incident commander for security incidents, driving clear coordination across executive, engineering, security, legal, and other appropriate stakeholders.
• Establish and run incident commander rotations within D&R, ensuring clear ownership and effective coordination during incidents of varying severity.
• Drive post-incident accountability by defining how action items are captured, assigned, tracked, and completed across teams—ensuring follow-through on both tactical fixes and strategic improvements.
• Gather, analyze, and report on incident trends and patterns to surface systemic risks, recurring root causes, and areas where the organization is most vulnerable.
• Translate trend analysis into actionable cross-functional initiatives: partner with engineering, infrastructure, security, and product teams to prioritize and implement broad fixes and preventive improvements that address root causes rather than symptoms.
• Lead incident review forums (post-mortems, retrospectives) and ensure learnings are captured, socialized, and acted upon across the organization.
• Develop and maintain D&R incident response documentation, playbooks, runbooks, and training materials; keep them current as the threat landscape and our systems evolve.
• Partner with detection engineering to improve alert fidelity, reduce noise, and shorten time-to-detection for security events.
• Define, develop, and track incident management KPIs and report regularly to D&R and Security leadership.
• Support broad cross-functional training and initiatives to uplevel security awareness across the company (e.g. Tabletop exercises, training, talks).

You may be a good fit if you:

• Have 7+ years of experience in technical program management, incident management, or security operations, with significant time spent in a detection & response or security incident response context.
• Have led or built incident response programs at a technology company, ideally in a high-growth or security-intensive environment.
• Have a demonstrated track record of turning incident data into organizational improvements—not just writing post-mortems, but driving the cross-functional work to implement systemic fixes.
• Are comfortable participating in on-call responsibilities and leading incident response during high-severity security events, including off-hours.
• Have experience building and scaling operational processes from the ground up in environments where structure didn’t previously exist.
• Excel at driving accountability and follow-through across multiple teams without direct authority—you know how to influence, track, and close the loop.
• Have strong analytical skills and experience with incident trend analysis, metrics reporting, and data-driven prioritization.
• Are highly organized with a knack for bringing structure to ambiguous, fast-moving situations.
• Have excellent communication skills, especially under pressure and when coordinating across technical and non-technical stakeholders, including executive leadership.
• Thrive in fast-paced environments where priorities shift and you’re often working with incomplete information.

About the team

We are seeking passionate Research Scientists and Engineers to join our growing Pre-training team in Zurich. We are involved in developing the next generation of large language models. The team primarily focuses on multimodal capabilities: giving LLMs the ability to understand and interact with modalities other than text.

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.

Responsibilities

In this role you will interact with many parts of the engineering and research stacks.

• 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 & Experience

We encourage you to apply even if you do not believe you meet every single criterion. Because we focus on so many areas, the team is looking for both experienced engineers and strong researchers, and encourage anyone along the researcher/engineer spectrum to apply.

• Degree (BA required, MS or PhD preferred) 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 deep learning frameworks

• Have worked on high-performance, large-scale ML systems, particularly in the context of language modeling

• Familiarity with ML Accelerators, Kubernetes, and large-scale data processing

• Strong problem-solving skills and a results-oriented mindset

• Excellent communication skills and ability to work in a collaborative environment

You'll thrive in this role if you

• Have significant software engineering experience

• Are able to balance research goals with practical engineering constraints

• Are happy to 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

• Have ambitious goals for AI safety and general progress in the next few years, and you’re excited to create the best outcomes over the long-term

Sample Projects

• Optimizing the throughput of novel attention mechanisms

• Proposing Transformer variants, and experimentally comparing their performance

• Preparing large-scale datasets for model consumption

• Scaling distributed training jobs to thousands of accelerators

• Designing fault tolerance strategies for training infrastructure

• Creating interactive visualizations of model internals, such as attention patterns

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

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

We are seeking a Detection and Response Engineering Manager to lead our Detection and Response teams in creating comprehensive Security Observability, Detection Lifecycle, and Security Incident Response programs for Anthropic. You will collaborate closely with teams and leaders across Anthropic, focusing on the observability, detection, investigation, incident response, and intelligence portions of the security lifecycle. You will collaborate closely with preventative security engineering teams and other cross-functional teams.

What you’ll do:

• Manage and grow a high-performing D&R team, planning strategy and hiring to support Anthropic's rapid growth and unique AI safety requirements
• Navigate prioritization in a fast-paced frontier environment, balancing operational demands with building innovative, scalable solutions for the future
• Collaborate across security engineering teams to build comprehensive prevention, observability, detection, and response capabilities throughout the security lifecycle
• Facilitate development of scalable, AI-leveraged D&R solutions that enable self-service observability and detection capabilities across Anthropic
• Build partnerships with product, infrastructure, and research teams to instill security monitoring best practices
• Own and continuously improve Security Incident Response, Data Management, and Detection Engineering policies and playbooks
• Operate our threat intelligence program and maintain relationships with external security partners and information sharing communities
• Continuously drive capability maturity across the detection lifecycle, establishing metrics and KPIs to measure effectiveness

Who you are:

• 10+ years building detection and response capabilities in a cloud-native organization
• 5+ years of engineering management experience with a proven track record of building and scaling security teams
• Deep understanding of security monitoring, threat detection, incident response, and forensics best practices
• Experienced in securing complex cloud environments (Kubernetes, AWS/GCP) with modern detection technologies
• Knowledgeable in AI/ML security risks, detection patterns, and response strategies
• Strong verbal and written communication skills with the ability to distill complex security topics
• Skilled at collaborating cross-functionally and effectively balancing security requirements with business objectives
• Able to drive high-impact work while incorporating feedback and adapting to changing priorities
• Passionate about building diverse, high-performing teams and growing engineers in a fast-paced environment
• Low ego, high empathy, and have a track record as a talent magnet who attracts and retains top security talent

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