A leading AI research organization is seeking a Commercial Counsel to join its founding Commercial Legal team in Dublin. The role involves drafting and negotiating commercial agreements, partnering with sales teams, and guiding legal strategies for AI deployment in the EMEA region. Ideal candidates will have a law degree with at least 4 years of legal experience in technology transactions. The position requires strong communication skills and a collaborative approach. You must work onsite at least 3 days a week. #J-18808-Ljbffr
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. Anthropic is seeking an exceptional Commercial Counsel to join our founding Commercial Legal team in EMEA! You'll serve as a strategic legal partner to our sales teams, supporting complex deal negotiations and commercial activities that fuel our expansion with leading EMEA companies and organizations across all market segments, from SMB to large enterprises. In this highly impactful role, you'll guide sophisticated technology transactions across diverse industries and client sizes while providing strategic counsel on the unique legal and regulatory considerations for responsible AI deployment throughout the EMEA region. Responsibilities: Draft, review, and negotiate commercial agreements, with a primary focus on GTM/Sales transactions in EMEA, including enterprise customer contracts Partner closely with Sales and Go-to-Market teams to support deal velocity and provide practical legal guidance Help build and maintain our commercial legal infrastructure, including contract templates, playbooks, and process improvements Identify and elevate legal risks appropriately while supporting business momentum Stay current on legal developments affecting AI technologies Foster relationships with external stakeholders, including clients of all sizes, regulatory bodies, and industry partners across the EMEA region You might be a good fit if you have: Law degree and qualification to practice law in a relevant EMEA jurisdiction At least 4 years of legal experience, ideally with exposure to commercial contracts, SaaS agreements, or technology transactions Clear communication skills and comfort translating legal concepts for non-lawyer audiences A low-ego, collaborative approach to working with colleagues and external partners Curiosity about AI technology, AI Policy, and commitment to responsible AI development Experience navigating multi-stakeholder agreements involving technical and policy considerations Comfort in fast-paced environments with shifting priorities and tight deadlines A "doer" attitude—willingness to roll up your sleeves and pitch in where needed Strong candidates may have: In-house experience at leading technology companies with EMEA operations Previous experience with AI, machine learning, or other experimental technologies in commercial contexts Experience supporting sales teams across diverse client segments in deal negotiations Role-specific policy: For this role, we expect all staff to be able to work from our Dublin office at least 3 days a week, though we encourage you to apply even if you might need some flexibility for an interim period of time. Application Deadline : 4pm GMT on March 23, 2026. We encourage all interested and qualified applicants to submit their materials before this date to ensure full consideration. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. 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. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. 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 at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. 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 lovely office space in which to collaborate with colleagues. Guidance on Candidates’ AI Usage: Learn about our policy for using AI in our application process. #J-18808-Ljbffr
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. #J-18808-Ljbffr
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. #J-18808-Ljbffr
A technology company in Dublin is seeking an experienced software engineer to join their Inference team. The role involves building and maintaining critical AI systems that serve numerous users worldwide. Candidates should have significant experience with distributed systems, as well as a solid grasp of Kubernetes and cloud infrastructure. The ideal applicant will also possess a Bachelor's degree in a related field. We offer competitive compensation and promote a hybrid working model. #J-18808-Ljbffr
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: Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next‑generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Strong candidates may also have experience with: Implementing and deploying machine learning systems at scale Load balancing, request routing, or traffic management systems LLM inference optimization, batching, and caching strategies Kubernetes and cloud infrastructure (AWS, GCP) Python or Rust You may be a good fit if you: Have significant software engineering experience, particularly with distributed systems Are results‑oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Want to learn more about machine learning systems and infrastructure Thrive in environments where technical excellence directly drives both business results and research breakthroughs Care about the societal impacts of your work Representative projects across the org: Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads Building production‑grade deployment pipelines for releasing new models to millions of users Integrating new AI accelerator platforms to maintain our hardware‑agnostic competitive advantage Contributing to new inference features (e.g., structured sampling, prompt caching) Analyzing observability data to tune performance based on real‑world production workloads Managing multi‑region deployments and geographic routing for global customers Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Our total compensation package for full‑time employees includes equity and benefits. 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. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. 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 at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT‑3, Circuit‑Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. 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 lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process. #J-18808-Ljbffr
