Apply for Software Engineer AI Jobs UK in 2026 with visa sponsorship available. Explore this high-paying AI Reliability Engineering role offering a salary of £325,000–£390,000, hybrid working, career growth, and excellent benefits.
Software Engineer AI Jobs UK 2026 – High-Paying Visa Sponsorship Opportunity
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Software Engineer, AI – Visa Sponsorship Available
About Anthropic
Anthropic is focused on improving the development of dependable, interpretable, and steerable artificial intelligence systems. Our objective is to ensure that AI technologies are safe, beneficial, and compatible with our society’s ideals. We’re a growing team of researchers, technologists, policy experts and business executives working together to develop AI solutions that benefit the greater good. We want to build AI systems that are not only able to perform but also transparent and controlled, to ensure that AI deployment is trustworthy and safe across a wide range of applications.
About the Job
The AI Reliability Engineering (AIRE) team at Anthropic is essential to maintaining and improving the reliability of our AI systems, especially the Claude language model. As a Reliability Engineer, working at AIRE you will work with cross-functional teams to ensure the robustness and reliability of our AI serving infrastructure. You will design and execute monitoring solutions, build highly available systems, and lead incident response activities to ensure systems perform at their best. This post is an exciting chance to impact the whole lifecycle of AI deployment, making sure our systems are robust during normal operation and during crisis response. You will be responsible for designing robust infrastructure that supports our safety commitments and user trust. You’ll be working fast and need both technical skill and strategic thought.
Qualifications
Bachelor’s degree or equivalent in a relevant field (Computer Science, Electrical Engineering or other related fields).
Deep experience in distributed systems, infrastructure or reliability engineering.
Experience hands-on with large-scale model serving or training infrastructure with 1000+ GPUs.
Knowledge of ML hardware accelerators (GPUs, TPUs, Trainium).
ML specialised networking optimisations such as RDMA and InfiniBand.
Experience with observability tools and frameworks for AI systems.
Experience in chaotic engineering and resilience testing methods.
Contributions to open source infrastructure or ML tooling is a bonus.
Strong communication and teamwork skills, with the ability to develop relationships across teams.
Demonstrated ownership and user focus in system reliability.
Duties
Develop and manage Service Level Objectives (SLOs) for big language model serving systems, balancing availability, latency and velocity of development.
Design, build and upgrade monitoring and observability systems across the token processing pipeline.
Design and install high-availability serving infrastructure across different geographies and cloud providers.
Lead incident response for key AI services with rapid recovery, detailed incident analysis, and systematic improvements.
Ensure the safeguard model’s version is trustworthy and safe, according with Anthropic’s safety commitments.
Work with engineering teams to improve system performance and resiliency.
Identify potential system threats and take proactive actions to minimise risks.
Help establish the best practices and standards for reliability engineering in AI systems.
Comprehensive health, dental and vision insurance.
Hybrid Work Policy, with at least 25% office presence, flexible work arrangements.
Visa sponsorship possible for qualified candidates.
Opportunities for career growth and development in a leading AI firm.
A collaborative and inclusive work atmosphere that fosters creativity and diversity.
Equal Opportunity
Anthropic is committed to fostering an inclusive and diverse workplace. We are an equal opportunity employer and do not discriminate based on race, ethnicity, gender, sexual orientation, age, handicap, religion or any other protected status. We believe that a diverse staff makes us better at innovating and fulfilling our aim of constructing safe and beneficial AI systems. All competent applicants shall be considered for employment without regard to any protected feature.
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