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Sundayy

Software Engineer, AI

England
£325k – £390k/yr
Posted about 17 hours ago
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About Anthropic

Anthropic is dedicated to advancing the development of reliable, interpretable, and steerable artificial intelligence systems. Our mission is to ensure that AI technologies are safe, beneficial, and aligned with societal values. We are a rapidly expanding team comprising researchers, engineers, policy experts, and business leaders who collaborate to build AI solutions that serve the greater good. Our focus is on creating systems that are not only powerful but also transparent and controllable, fostering trust and safety in AI deployment across diverse applications.

About The Role

The AI Reliability Engineering (AIRE) team at Anthropic plays a crucial role in maintaining and enhancing the reliability of our AI systems, particularly the Claude language model. As a Reliability Engineer within AIRE, you will partner with cross-functional teams to ensure the robustness and resilience of our AI serving infrastructure. Your work will involve designing and implementing monitoring solutions, developing high-availability systems, and leading incident response efforts to maintain optimal system performance. This role offers a unique opportunity to influence the entire lifecycle of AI deployment, ensuring that our systems are dependable during normal operations and in times of incident. You will be at the forefront of building resilient infrastructure that supports our safety commitments and user trust, working in a dynamic environment that requires both technical expertise and strategic thinking.

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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Qualifications

  • Bachelor’s degree or equivalent in a relevant field such as Computer Science, Electrical Engineering, or related disciplines
  • Strong background in distributed systems, infrastructure, or reliability engineering
  • Experience operating large-scale model serving or training infrastructure with over 1000 GPUs
  • Familiarity with ML hardware accelerators (GPUs, TPUs, Trainium)
  • Knowledge of ML-specific networking optimizations like RDMA and InfiniBand
  • Proficiency with observability tools and frameworks tailored for AI systems
  • Experience with chaos engineering and resilience testing methodologies
  • Contributions to open-source infrastructure or ML tooling are a plus
  • Excellent communication and collaboration skills with the ability to build cross-team relationships
  • Demonstrated ownership and a user-centric mindset in system reliability

Responsibilities

  • Develop and maintain Service Level Objectives (SLOs) for large language model serving systems, balancing availability, latency, and development velocity
  • Design, implement, and improve monitoring and observability systems across the token processing pipeline
  • Assist in designing and deploying high-availability serving infrastructure across multiple regions and cloud providers
  • Lead incident response efforts for critical AI services, ensuring rapid recovery, thorough incident analysis, and systematic improvements
  • Support the reliability and safety of safeguard model serving, aligning with Anthropic’s safety commitments
  • Collaborate with engineering teams to optimize system performance and resilience
  • Identify potential system vulnerabilities and implement proactive measures to mitigate risks
  • Contribute to the development of best practices and standards for reliability engineering in AI systems

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Benefits

  • Competitive annual salary ranging from £325,000 to £390,000 GBP
  • Comprehensive health, dental, and vision insurance plans
  • Flexible work arrangements with a hybrid policy requiring at least 25% office presence
  • Visa sponsorship available for eligible candidates
  • Opportunities for professional growth and development within a pioneering AI company
  • Collaborative and inclusive work environment fostering innovation and diversity

Equal Opportunity

Anthropic is committed to creating a diverse and inclusive workplace. We are an equal opportunity employer and do not discriminate based on race, ethnicity, gender, sexual orientation, age, disability, religion, or any other protected status. We believe that a diverse team enhances our ability to innovate and achieve our mission of building safe and beneficial AI systems. All qualified applicants will receive consideration for employment without regard to any protected characteristic.

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Skills

Distributed Systems
Reliability Engineering
Model Serving Infrastructure
GPU/TPU/Trainium
RDMA
InfiniBand
Observability Tools
Chaos Engineering
Resilience Testing
SLO Development
Incident Response
Cloud Infrastructure

Location

England, United Kingdom

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