About Anthropic

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole.

About the Role

Security at Anthropic is not a compliance exercise. It is a core part of how we stay safe as we build increasingly capable systems. Our Responsible Scaling Policy commits us to launching structured security R&D projects: ambitious, time-boxed experiments designed to resolve high-uncertainty questions about our long-term security posture.

Each project runs for roughly 6 months with defined exit criteria. Some will succeed and move toward production. Others will fail, and we'll treat that as useful signals. The questions these projects are designed to answer include:

• Can our core research workflows survive extreme isolation?

• Can we get cryptographic guarantees where we currently rely on trust?

• Can AI become our most effective security control?

As a Security Labs Engineer, you own one or more projects end-to-end: scoping the experiment, building the infrastructure, coordinating across teams, running the pilot, documenting results, and where the experiment succeeds, helping scale it into production. This is 0-to-1 and 1-to-10 work.

Current Project Areas

The portfolio evolves based on what we learn. Current areas include:

• Designing and operating a mock high-assurance research environment: simulating what our infrastructure would look like under extreme isolation and physical security controls, with real measurement of productivity impact

• Exploring cryptographic verification of model integrity using techniques like zero-knowledge proofs to provide mathematical guarantees about what is running in production

• Assessing the feasibility of confidential computing across the full model lifecycle (note: this is an open question, not a committed roadmap item)

• Piloting AI-assisted security tooling including vulnerability discovery, automated patching, anomaly detection, and adaptive behavioral monitoring

• Prototyping API-only access regimes where even internal research workflows never touch raw model weights

Part of your job is helping shape what comes next based on gaps uncovered in the current round.

Responsibilities

• Own the end-to-end execution of a Security Labs project: refine the hypothesis, design the experiment, build the prototype, run the pilot, and write up the results

• Build novel security infrastructure under real time pressure: isolated clusters, hardened access controls, cryptographic verification layers, with a bias toward learning fast

• Where experiments succeed, drive them toward production scale. An experiment that works on one cluster but not a hundred is not a finished result.

• Work embedded with research teams (Pretraining, RL, Inference) to stress-test whether their core workflows can function under extreme security controls, and document precisely where they break

• Evaluate and integrate emerging security technologies through coordination with external vendors and research groups

• Turn experimental results into clear, decision-ready writeups that inform Anthropic's long-term security architecture and RSP commitments

• Maintain a pain-point registry and feasibility assessment for each project, feeding directly into the design of production high-assurance environments

• Help scope and prioritize the next wave of Labs projects based on what the current round uncovers

Requirements

• 7+ years of software or security engineering experience, with a solid foundation in production systems

• Some of that time spent on pilots, prototypes, or applied research work where shipping a working answer to a hard question was the explicit goal

• Strong programming skills in Python and at least one systems language (Go, Rust, or C/C++)

• Hands-on experience with cloud infrastructure (AWS, GCP, or Azure), Kubernetes, and networking fundamentals sufficient to stand up and tear down isolated environments quickly

• A track record of cross-functional execution: you can walk into a room with ML researchers, infrastructure engineers, and vendors and leave with a shared plan

• Clear written communication: you know how to turn six weeks of experimentation into a two-page memo someone can act on

• Comfort with ambiguity and iteration, having run experiments that failed, extracted the lesson, and moved forward

• Genuine curiosity about what it would actually take to defend against a nation-state-level adversary

• Passion for AI safety and a real understanding of the role security plays in making frontier AI development go well

• Bachelor's degree in Computer Science, a related field, or equivalent industry experience required.

Preferred Qualifications

• Prior experience in offensive security, red teaming, or security research, having thought adversarially about systems and knowing which threats actually matter

• Familiarity with airgapped or high-side environments (classified networks, ICS/SCADA, financial trading infrastructure, or similar) and the operational realities of working inside them

• Knowledge of applied cryptography: zero-knowledge proofs, attestation protocols, secure enclaves, TPMs, or confidential computing primitives

• Experience with ML infrastructure (training pipelines, inference serving, model packaging) sufficient for grounded conversations with researchers about what their workflows actually need

• Background building or operating security systems in environments that demand rapid iteration rather than rigid change control

• Prior work at a startup, on an innovation team, or in an applied research group where shipping a working v0 to answer a real question was explicitly the goal

Location

This role is based in our San Francisco office (500 Howard St). Several Labs projects involve physical secure facilities on-site, so expect to be in-office more frequently than Anthropic's standard 25% hybrid baseline.

What We Offer

• Competitive salary and equity package

• Comprehensive health insurance and retirement plans

• Flexible work arrangements, including remote work options

• Professional development opportunities, including training and conference attendance

• Collaborative and dynamic work environment

• Access to cutting-edge technology and resources

• Opportunity to work on challenging and impactful projects

• Recognition and rewards for outstanding performance

If you're excited about the opportunity to join our team and contribute to the development of secure and beneficial AI systems, please submit your application. We can't wait to hear from you!

Deadline to Apply

None, applications will be received on a rolling basis.

Annual Compensation Range

$405,000 - $485,000 USD

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with the process.

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This role is highly operational in nature, with a strong focus on designing a growing organisation, aligning with cross-functional partners on roles, responsibilities, and ways of working, and partnering with senior leadership to further develop Pinterest's partner marketing capability.

As a player-coach, you will lead key partner marketing workstreams while simultaneously setting the vision, managing resources, and developing the capabilities of your team.

Key Responsibilities:

• Architect a long-term vision for the partner marketing function at Pinterest in partnership with XFN teams.
• Roll up your sleeves to lead key partner marketing workstreams, including events, webinars and content marketing campaigns to increase consideration for Pinterest’s advertising solutions and ultimately drive revenue.
• Create a culture that emphasises constructive feedback, ongoing learning and development, and reinforces its value to the organisation.
• Build tracking mechanisms that create an environment of accountability for the working team's progression.
• Project and plan for resourcing needs and recruit where necessary to deliver results and meet functional short-term and long-term strategic goals.
• Collaborate and influence senior-level cross-functional partners on complex business challenges.
• Leverage AI tools to accelerate the development of partner marketing assets, including event materials, webinar content, and co-marketing campaigns.
• Utilise AI-assisted analytics and reporting tools to surface insights on partner marketing performance, identify trends across campaigns and channels, and make faster, smarter decisions about where to invest resources.

Requirements:

• 15+ years of experience in business marketing, with at least 10 years of experience specifically in partner marketing.
• Proven experience leading teams and the partner marketing capability, ideally at a similar or competitive platform to Pinterest.
• Mastery in influencing, mature decision quality, comfort with ambiguity, values differences, and AI fluency and adaptability.
• Bachelor’s degree in marketing, a related field, or equivalent experience.

Relocation Statement: This position is not eligible for relocation assistance.

In-Office Requirement Statement: This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.

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As a Senior Manager, you will lead a team of data scientists and work directly in partnership with engineering leaders to empower them with data-driven insights and solutions. You will promote a data-driven approach to infrastructure decisions, influencing stakeholders across engineering, and support to leverage data science insights for high-impact, aligned strategies.

Key responsibilities include:

• Thought leadership and strategic guidance on infrastructure planning, balancing current needs with future growth projections to ensure scalability and cost-effectiveness.
• Implement data-driven solutions to identify, predict, and mitigate infrastructure risks and failures, reducing downtime and improving system reliability and performance, directly impacting end-user satisfaction and operational continuity.
• Spearhead analyses to improve resource utilisation efficiency, identifying and eliminating inefficiencies across infrastructure usage, resulting in cost savings and optimised performance.
• Establish data frameworks that empower support teams to troubleshoot and resolve product issues faster, decreasing response times and enhancing customer experience and support quality.
• Mentor and manage a team of data scientists, instilling best practices in data science, engineering, and fostering a collaborative environment focused on innovative, scalable infrastructure solutions.

Requirements include:

• 10+ years of infrastructure data science, machine learning, advanced analytics experience in high-velocity, high-growth companies.
• 5+ years of management experience hiring and developing teams.
• Experience developing data science, analytics, and machine learning and AI products and capabilities in a cloud environment.
• Knowledge of statistics and rigorous analytical techniques.
• Experience with data visualisation tools, knowledge of data engineering, data modelling, and big data technologies.
• Leadership skills and experience to lead across functional and organisational lines.
• Strong communication skills to explain and evangelise analytics and data science to executives and the senior management team.
• Bias to action and passion for delivering high-quality data solutions.
• A passion for problem-solving and comfort with ambiguity.
• MS or Ph.D. in quantitative fields (Statistics, Math, CS or Engineering).

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilising the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range $228,600-$314,250 USD

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Responsibilities

You and your team will own three areas:

• Dashboard reliability: infrastructure, monitoring, alerting, incident response, CI/CD pipelines
• Developer experience: tooling, development environment, design system, agentic coding infrastructure
• Platform capabilities: authorization, audit logging, configuration management, and other features that provide horizontal value across the dashboard

You'll lead a small team, spending roughly 50% of your time on technical work, 20% on team leadership, and 30% working across teams. Success looks like: reduced build times, fewer production incidents with lesser impact, and teams reporting that the platform makes them more effective.

Requirements

• Platform engineering experience - you've built internal tools, developer platforms, or infrastructure that other engineers depend on
• Full-stack technical depth - strong hands-on experience with React & TypeScript + Node.js backend experience
• Infrastructure and operations experience - you have experience building & maintaining CI/CD pipelines, monitoring, and alerting; you've been on-call and handled production incidents
• Leadership experience - you've led projects, mentored engineers, or managed a small team; formal management experience preferred but not required
• Systems thinking - you think in tradeoffs and understand how decisions affect multiple teams
• Communication skills - you'll work across 7 teams and need to influence without authority
• Comfort with ambiguity - you can take a vague problem and structure an approach

Nice to Have

• Experience with design systems or component libraries
• Experience with AI-assisted development tools or agentic coding
• Experience in e-commerce or B2B SaaS
• Experience working remotely in a distributed team

Benefits

• Unlimited vacation time - we strongly encourage all of our employees to take at least 3 weeks per year
• A competitive compensation package, including stock options
• Fully remote team - choose where you live
• Work from home stipend! We want you to have the resources you need to set up your home office
• Apple laptops provided for new employees
• Training and development budget for every employee, refreshed each year
• Parental leave for qualified employees
• Work with smart people who will help you grow and make a meaningful impact

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Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Team

As AI training and deployments scale, the volume of data we need to monitor and understand is exploding. Our team uses Claude itself to make sense of this data. We own an integrated set of tools enabling Anthropic to ask open-ended questions, surface unexpected patterns, and maintain meaningful human oversight over massive datasets.

Our tools are widely adopted internally — powering ongoing enforcement, threat intelligence investigations, model audits, and more — and we’re looking for experienced engineers and researchers to both scale up existing applications and go zero-to-one on new ones.

About the Role

As a Research Engineer on our team, you'll design and build systems that let AI analyse large, unstructured datasets — think tens or hundreds of thousands of conversations or documents — and produce structured, trustworthy insights. You'll work across the full stack, from core analysis frameworks through user-facing apps and interfaces.

This is a high-leverage role. The tools you build will be used by dozens of researchers and investigators, and directly shape our ability to measure and mitigate both misuse and misalignment.

Responsibilities:

• Design and implement AI-based monitoring systems for AI training and deployment

• Extend and improve core frameworks for processing large volumes of unstructured text

• Partner with researchers and safety teams across Anthropic to understand their analytical needs and build solutions

• Develop agentic integrations that allow AI systems to autonomously investigate and act on analytical findings

• Contribute to the strategic direction of the team, including decisions about what to build, what to partner on, and where to invest

You May Be a Good Fit If You:

• Have 5+ years of software engineering experience, with meaningful exposure to ML systems

• Are excited about the problem of scaling human oversight of AI systems

• Are familiar with LLM application development (context engineering, evaluation, orchestration)

• Enjoy building tools that other people use — you care about UX, reliability, and documentation

• Can context-switch between deep infrastructure work and user-facing product thinking

• Thrive in collaborative, cross-functional environments

Strong Candidates May Also Have:

• Research experience in AI safety, alignment, or responsible deployment

• Practical experience with both data science and engineering, including developing and using large-scale data processing frameworks

• Experience with productionizing internal tools or building developer-facing platforms

• Background in building monitoring or observability systems

• Comfort with ambiguity — our team is small and growing, and you'll help define what we become

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work.

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