The Platform team creates the technology that enables Spotify to learn quickly and scale easily, enabling rapid growth in our users and our business around the globe. Spanning many disciplines, we work to make the business work; creating the infrastructure, tooling, frameworks, and capabilities needed to welcome a billion customers.

About the Team

We are looking for a passionate Product Manager to join Spotify’s Data Platform Studio. Data Platform’s mission is to enable the application of data in an intuitive and efficient way,helping Spotify extract value from data at scale.

Data Platform is responsible for how data is collected, processed, stored, governed, and made available to the thousands of engineers, data scientists, and analysts who build Spotify’s products. With AI agents increasingly writing data pipelines and powering personalization, this is one of the most consequential infrastructure domains at Spotify.

What You'll Do

• Understand the needs of Spotify’s data community,including engineers, analysts, data scientists, ML engineers, and AI agents,and prioritize the most impactful problems to solve

• Define and drive the strategy and roadmap for your product area, connecting it to the broader Platform and company strategy

• Evaluate solutions across build, buy, or partner approaches to improve how Spotify works with data

• Define success metrics and track adoption, creating a continuous loop of learning and iteration

• Collaborate closely with engineering, design, and data science to deliver intuitive, high-impact solutions

• Build strong relationships with internal teams to gather feedback and co-evolve tooling and capabilities

• Influence stakeholders across the studio and company to align on direction and priorities

• Stay current with trends in data platforms, analytics, and AI/ML tooling

Who You Are

• You have 2+ years of product management experience, ideally in data infrastructure, developer tools, or platform products

• You have a technical background, such as a degree in Computer Science/Engineering or prior hands-on engineering experience

• You are experienced in working with cross-functional teams across engineering, design, and data disciplines

• You know how to translate complex technical concepts into clear product direction and strategy

• You have a strong systems-thinking mindset and can connect workflows, platforms, and business needs

• You care deeply about the experience of people working with data and strive to make their workflows better

• You are curious about AI and excited about its impact on data ecosystems

• You communicate with clarity, bring people together, and build alignment across different audiences

Where You'll Be

• This role is based in London, Stockholm, or Toronto

• We offer you the flexibility to work where you work best! There will be some in-person meetings, but still allows for flexibility to work from home.

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Data Platform is responsible for how data is collected, processed, stored, governed, and made available to the thousands of engineers, data scientists, and analysts who build Spotify's products. With AI agents increasingly writing data pipelines and powering personalization, this is one of the most consequential infrastructure domains at Spotify.

As a Product Manager on the Data Platform team, you will be responsible for defining and driving the strategy and roadmap for your product area, connecting it to the broader Platform and company strategy. You will evaluate solutions across build, buy, or partner approaches to improve how Spotify works with data. You will define success metrics and track adoption, creating a continuous loop of learning and iteration.

Collaboration is key to success in this role. You will work closely with engineering, design, and data science to deliver intuitive, high-impact solutions. You will build strong relationships with internal teams to gather feedback and co-evolve tooling and capabilities. You will influence stakeholders across the studio and company to align on direction and priorities.

To be successful in this role, you will need to have a strong understanding of data platforms, analytics, and AI/ML tooling. You will need to be able to communicate complex technical concepts into clear product direction and strategy. You will need to have a strong systems-thinking mindset and be able to connect workflows, platforms, and business needs.

If you are passionate about data and want to join a team that is shaping the future of music streaming, please apply!

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As a Strategic Account Executive on the GSI team, you'll own a named book of accounts and the full revenue outcome for each. You'll develop a point of view on where Claude creates the most value across a firm's practice areas, advisory services, delivery teams, and internal operations, build relationships with the partners and executives who sponsor transformation at that scale, and expand the partnership well beyond the original buyer.

Responsibilities

• Own all revenue outcomes for a named book of GSI accounts, driving both new logo acquisition and multi-practice expansion through complex, multi-quarter sales cycles involving partner-led approval, global procurement, and custom commercial terms
• Develop a clear thesis for each priority firm , where Claude creates value across knowledge management, advisory workflows, deliverable generation, and client engagements , and execute a sequenced engagement plan across practices, regions, and stakeholders
• Build and independently advance executive relationships with Managing Partners, Practice Leads, MDs, CIOs, CTOs, and Heads of AI/Digital, anchoring every conversation to their strategic priorities: utilization, leverage, realization, and billable productivity
• Proactively create demand in unengaged practice areas and regions, using early wins as proof points to open new doors across decentralized, partner-led organizations
• Build quantified, firm-specific business cases mapped to the GSI operating model , using their own language and metrics , that shape deals rather than justify them after the fact
• Identify and close lighthouse partnerships that become references across the GSI landscape and set up the future sell-with motion
• Partner cross-functionally with Product, Applied AI, Engineering, and Partnerships to inform the roadmap based on GSI buyer needs, and contribute to the playbook, proof points, and commercial structures that become the repeatable GSI motion

Requirements

• 8+ years of enterprise software sales experience with a track record of owning named accounts at large, complex, partner-led organizations (global SIs, strategy consultancies), managing multi-quarter sales cycles through technical evaluations, partner-led approval, and global procurement
• Demonstrated ability to independently build and advance relationships at the Partner, MD, and C-suite level , including practice leadership and innovation/digital executives , and hold credible conversations across both technical and business audience
• Experience building firm-specific business cases grounded in the firm's own operating metrics (utilization, leverage, realization, margin) and defending commercial terms through complex negotiations
• Background selling platform, API, cloud infrastructure, or emerging technology into enterprises evaluating a new category
• Genuine interest in AI and strong alignment with Anthropic's mission of responsible AI development
• A history of growing accounts meaningfully beyond the original engagement by proactively creating demand across new practice areas, regions, and use cases

What Will Make You Stand Out

• Direct experience selling into Global SI’s or strategy consultancies, and fluency in how partner-led firms 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 partner-led services firms

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 this.

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You may be a good fit for this role if you have strong distributed systems, infrastructure, or reliability backgrounds, are curious and brave, think holistically about how systems compose and where the seams are, can build lasting relationships across teams, care about users and feel ownership over outcomes, have excellent communication and collaboration skills, and bring diverse experience.

Strong candidates may also have experience operating large-scale model serving or training infrastructure, experience with one or more ML hardware accelerators, understanding of ML-specific networking optimizations, expertise in AI-specific observability tools and frameworks, experience with chaos engineering and systematic resilience testing, and contributions to open-source infrastructure or ML tooling.

We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. We value impact and believe that the highest-impact AI research will be big science. We work as a single cohesive team on just a few large-scale research efforts and value communication skills.

If you're interested in this role, please submit an application even if you don't believe you meet every single qualification. We encourage diversity and strive to include a range of diverse perspectives on our team.

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You'll define and ship AI-assisted workflows, self-service diagnostics, and platform integrations that reduce time-to-resolution and improve customer experience across our cloud.

Key responsibilities include:

• Design, build, and own support-facing tools for case triage, intelligent routing, and expert engagement, integrating with incident and change management workflows.

• Develop AI-powered assistants and automations that accelerate root-cause discovery, knowledge retrieval, and resolution quality.

• Create and maintain dashboards, alerts, and signals that surface tooling issues early; integrate observability into new tooling to reduce MTTR.

• Build self-service and guided diagnostics that empower Support/CX to resolve common issues and collect high-quality context for escalations.

• Codify reliability and support practices into services, APIs, and Kubernetes-native controllers/operators where appropriate.

• Partner with engineering leadership and internal stakeholders to prioritise roadmap initiatives, land adoption, and measure business impact.

• Participate in an on-call rotation for the tooling you own.

Minimum qualifications include:

• 4+ years of software or infrastructure engineering experience building and operating production services.

• Proficiency in Go or Python (or equivalent experience).

• Strong fundamentals in Linux, containers, and Kubernetes; comfortable debugging in distributed systems.

• Experience with observability (metrics/logs/traces) and using data to improve reliability and support outcomes.

• Demonstrated experience with incident management and steady-state operational excellence (e.g., progressive delivery, testing strategies, error budgets, fault-tolerant design).

• Comfort collaborating with multiple stakeholders (Support/CX, Product, SRE, and service owners).

Preferred qualifications include:

• Experience integrating or building support/operations tooling (e.g., ticketing/incident systems, status page, knowledge management, chat/alerting integrations).

• Experience automating manual workflows and stitching together productivity platforms.

• Familiarity with AI/ML tooling for retrieval, summarization, or copilot-style assistance.

• Experience codifying operational practices into Kubernetes controllers, operators, or platform services.

The base salary range for this role is $139,000 to $204,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

In addition to a competitive salary, we offer a variety of benefits to support your needs, including:

• Medical, dental, and vision insurance - 100% paid for by CoreWeave

• Company-paid Life Insurance

• Voluntary supplemental life insurance

• Short and long-term disability insurance

• Flexible Spending Account

• Health Savings Account

• Tuition Reimbursement

• Ability to Participate in Employee Stock Purchase Program (ESPP)

• Mental Wellness Benefits through Spring Health

• Family-Forming support provided by Carrot

• Paid Parental Leave

• Flexible, full-service childcare support with Kinside

• 401(k) with a generous employer match

• Flexible PTO

• Catered lunch each day in our office and data center locations

• A casual work environment

• A work culture focused on innovative disruption

Our Workplace

While we prioritise a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialised skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.

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Anthropic's Industries team partners with the world's largest enterprises across retail, manufacturing, automotive, consumer goods, hospitality, and commercial real estate to deploy frontier AI into the core of how they operate. As an Enterprise Account Executive on the Industries team, you'll own a named book of accounts and the full revenue outcome for each. You'll develop a point of view on where Claude creates the most value across a customer's business, build relationships with the executives who sponsor transformation at that scale, and expand the partnership well beyond the original buyer.

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

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Key Responsibilities:

AML/CTF Compliance Monitoring (2LoD): Support, maintain, and execute an independent, risk-based AML/CTF compliance monitoring and testing programme across Bridge's EMI and CASP perimeter. Perform thematic and control effectiveness reviews covering Customer Due Diligence (CDD)/Enhanced Due Diligence (EDD), transaction monitoring, sanctions/Politically Exposed Persons (PEP) screening, recordkeeping, and governance arrangements. Independently assess the adequacy and effectiveness of first-line controls and document conclusions with clear ratings and recommendations. Issue formal findings, agree remediation actions with the First Line of Defence (1LoD), and independently validate remediation closure through follow-up testing. Escalate material weaknesses or control deficiencies to senior management and governance committees where required.

Investigations and Escalations: Provide second-line review and challenge of higher-risk cases escalated by the first line (high-risk customers, complex typologies, sanctions/PEP matches, internal escalation); support MLRO decisioning and documentation. Conduct or support independent investigations triggered by red flags, audit/regulatory findings, or intelligence from partners; ensure a consistent audit trail in case management tools.

Law Enforcement / Police Requests: Oversee and coordinate responses to police, law enforcement, and competent authority requests in collaboration with the MLRO and Legal. Provide compliance oversight to ensure responses are timely, complete, proportionate, and aligned with regulatory obligations. Maintain governance-level logs, metrics, and reporting relating to external authority requests. Assess whether information requests or intelligence received may indicate systemic control weaknesses or trigger enhanced monitoring requirements.

Policy, Procedures and Program Maintenance: Draft, maintain, and periodically review AML/CTF policies, procedures, and standards for the EMI and CASP perimeter (risk rating, CDD/EDD, transaction monitoring governance, sanctions/PEP, record retention etc.). Contribute to the AML/CTF Business Risk Assessment and annual compliance plan; support governance committees and management reporting.

Advisory and Training: Provide AML/CTF advisory support to Operations, Onboarding, Product, and Engineering teams (new products/process changes, control design, risk mitigations). Support the development and delivery of AML/CTF training and communications, including targeted guidance for high-risk scenarios.

Regulatory Readiness and Reporting: Support responses to CSSF requests, audits, and inspections; prepare monitoring reports, management information (MI/KRIs), and remediation tracking. Stay up to date on changes to AML/CTF laws, CSSF guidance, and financial crime typologies relevant to payments and crypto-asset services.

Key Requirements:

Education: Bachelor’s degree in Law, Compliance, Finance, Business Administration, or a related field.

Experience: At least 4 years of experience in AML/CTF Compliance (second line of defence/compliance monitoring), preferably within an EMI/PI, CASP/VASP, bank, or regulated fintech environment. Demonstrated experience drafting AML/CTF policies and procedures, executing compliance monitoring/testing, supporting MLRO investigations and STR/SAR processes, and handling police/law-enforcement information requests.

Skills: Strong understanding of AML/CTF governance, the three lines of defence model, and second-line compliance monitoring methodologies. Excellent analytical and investigative skills, with the ability to produce clear written assessments and regulatory-ready documentation. Ability to take full ownership of projects from conception to completion within agreed timelines. Proficiency with AML tooling (case management, screening, transaction monitoring); familiarity with blockchain analytics tools is an advantage. Strong communication skills, both written and verbal, in English; French is an asset; knowledge of German and/or Luxembourgish is an advantage.

Certifications: Relevant certifications such as CAMS (Certified Anti-Money Laundering Specialist) or ICA (International Compliance Association) qualifications are considered an advantage.

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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 Role

Claude has your back. AIRE has Claude's. Help us keep Claude reliable for everyone who depends on it.

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 providers
• 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.

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 engineering as it does with computer science.

XML job scraping automation by YubHub

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 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.

Claude has your back. AIRE has Claude's. Help us keep Claude reliable for everyone who depends on it.

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 providers

• 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.

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 a team sport, where everyone contributes to the overall success of the team.

XML job scraping automation by YubHub

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 Role

Claude has your back. AIRE has Claude's. Help us keep Claude reliable for everyone who depends on it.

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 providers
• 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.

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.

Salary

The annual compensation range for this role is €235.000 - €295.000EUR.

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 engineering as it does with computer science. We strive to build a team that reflects this perspective, with people from a wide range of backgrounds and disciplines.

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