Senior Software Engineer, AI Reliability Engineering Dublin, IE

Anthropic; Dublin; On-site; EUR 80,000 - 100,000; Full time

Benefits offered by this job

Competitive compensation

Generous vacation

Flexible working hours

Job summary

A leading AI company in Dublin is seeking a Senior Software Engineer focused on AI Reliability Engineering. The role involves developing Service Level Objectives and designing systems for monitoring AI infrastructure. Ideal candidates have expertise in distributed systems, AI-specific observability, and communication skills. With a Bachelor’s degree required, the position offers a hybrid work model and competitive compensation, encouraging applications from candidates with varying qualifications.

Qualifications

• Extensive experience with distributed systems observability and monitoring.
• Understanding of AI infrastructure challenges including model serving.
• Proven experience with SLO/SLA frameworks.

Responsibilities

• Develop Service Level Objectives for model serving systems.
• Design monitoring systems for availability and latency.
• Lead incident response for critical AI services.

Skills

Distributed systems observability

AI infrastructure operation

SLO/SLA frameworks

Chaos engineering

Excellent communication skills

Education

Bachelor's degree in a related field

Tools

AI-specific observability tools

ML hardware accelerators (GPUs, TPUs)

Job description

Senior Software Engineer, AI Reliability Engineering

Dublin, IE

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. 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

The AIRE Serving team is responsible for elevating the reliability of Anthropic’s token path from client to inference servers and back. The team has wide latitude to drive improvements to our expanding SaaS and product surface, uplevel reliability mindsets across Anthropic, and partner with teams internally to build more robust and reliable systems. The breadth and depth of the technical challenges someone joining this team will encounter will be career defining and we are still writing the playbooks. We are at the center of ensuring our customers have a consistently excellent experience.

Responsibilities

• Develop appropriate Service Level Objectives for large language model serving and training systems, balancing availability/latency with development velocity.
• Design and implement monitoring systems including availability, latency and other salient metrics.
• Assist in the design and implementation of high-availability language model serving infrastructure capable of handling the needs of millions of external customers and high-traffic internal workloads.
• Develop and manage automated failover and recovery systems for model serving deployments across multiple regions and cloud providers.
• Lead incident response for critical AI services, ensuring rapid recovery and systematic improvements from each incident.
• Build and maintain cost optimization systems for large-scale AI infrastructure, focusing on accelerator (GPU/TPU/Trainium) utilization and efficiency.

You may be a good fit if you

• Have extensive experience with distributed systems observability and monitoring at scale.
• Understand the unique challenges of operating AI infrastructure, including model serving, batch inference, and training pipelines.
• Have proven experience implementing and maintaining SLO/SLA frameworks for business-critical services.
• Are comfortable working with both traditional metrics (latency, availability) and AI-specific metrics (model performance, training convergence).
• Have experience with chaos engineering and systematic resilience testing.
• Can effectively bridge the gap between ML engineers and infrastructure teams.
• Have excellent communication skills.

Strong candidates may also

• Have experience operating large-scale model training infrastructure or serving infrastructure (>1000 GPUs).
• Have experience with one or more ML hardware accelerators (GPUs, TPUs, Trainium, e.g.).
• Understand ML-specific networking optimizations like RDMA and InfiniBand.
• Have expertise in AI-specific observability tools and frameworks.
• Understand ML model deployment strategies and their reliability implications.
• 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 sponsor visas; however, we aren’t able to sponsor visas for every role and every candidate. If we make you an offer, we will make reasonable efforts to obtain a visa, with assistance from an immigration lawyer.

We encourage you to apply even if you do not meet every single qualification. Not all strong candidates will meet every qualification as listed. We also acknowledge that people from underrepresented groups may experience imposter syndrome and encourage you to apply if you are 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. We may partner with vetted recruiting agencies who 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 are 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 a few large-scale research efforts and value impact—advancing our long-term goals of steerable, trustworthy AI—over smaller, more specific puzzles. We view AI research as an empirical science and highly value communication skills.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a collaborative office space. This section contains information about our AI usage guidelines and application process.