Application Guide

How to Apply for Infrastructure Engineer, Technical AI Safety

at Centre for Long-Term Resilience

🏢 About Centre for Long-Term Resilience

The Centre for Long-Term Resilience is a unique independent think tank dedicated to safeguarding humanity against extreme risks, with a current focus on AI and biosecurity. Working here means contributing to high-impact projects that address some of the most pressing existential threats, in a collaborative and mission-driven environment.

About This Role

As an Infrastructure Engineer on the Loss of Control Observatory, you'll build and maintain the technical backbone for monitoring uncontrolled AI systems, including data pipelines, classification systems, and dashboards. This role directly supports early warning systems for AI risks, making your work critical for global safety.

💡 A Day in the Life

A typical day might start with monitoring data pipeline health and triaging any API failures. You'll then refine a Python script for a new social media source, followed by a team standup to discuss classification system updates. Afternoon could involve experimenting with LLM prompts to improve detection of unsafe AI behaviors, and ending with documenting GDPR compliance measures.

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Interview Prep

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🎯 Who Centre for Long-Term Resilience Is Looking For

  • A Python expert experienced in building robust data pipelines for collecting and processing large volumes of social media data from multiple APIs.
  • Skilled in LLM-based classification, with hands-on prompt engineering and evaluation framework design to ensure accurate and reliable model outputs.
  • Knowledgeable in GDPR compliance for data storage and processing, with experience implementing privacy-preserving techniques.
  • Comfortable working with social media APIs (e.g., Twitter, Reddit) and chatbot data sources, and scaling infrastructure to handle growing data streams.

📝 Tips for Applying to Centre for Long-Term Resilience

1

Highlight specific projects where you built Python data pipelines for social media data, including details on data volume, sources, and API integration.

2

Demonstrate your LLM prompt engineering skills by describing a project where you iteratively refined prompts and built evaluation metrics to improve classification accuracy.

3

Explicitly mention your experience with GDPR compliance, such as implementing anonymization, data retention policies, or consent management in a previous role.

4

Tailor your resume to include keywords like 'Loss of Control Observatory', 'AI safety', 'extreme risks', and 'think tank' to show alignment with their mission.

5

Provide a brief, concrete example of how you've scaled infrastructure (e.g., handling increased data load or adding new data sources) in a previous position.

✉️ What to Emphasize in Your Cover Letter

["Express genuine passion for AI safety and long-term resilience, and explain why CLTR's mission resonates with you personally.", "Emphasize your technical expertise in Python data pipelines and LLM classification, with specific examples that match the job's requirements.", 'Show how your experience with GDPR compliance and social media data directly applies to building the Loss of Control Observatory.', 'Convey your ability to work autonomously in a remote setting, and your interest in contributing to a small, impact-driven team.']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Read CLTR's published reports and blog posts on AI risks, especially the Loss of Control Observatory project documentation.
  • → Familiarize yourself with key concepts in AI safety, such as alignment, control, and monitoring, to speak their language.
  • → Research the team members (e.g., on LinkedIn) to understand their backgrounds and the collaborative culture.
  • → Look into CLTR's funding and partnerships to gauge the organization's stability and impact.
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💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Walk through a data pipeline you built: design choices, challenges with API rate limits or data quality, and how you ensured scalability.
2 How would you design a GDPR-compliant storage system for social media data? Discuss anonymization, retention, and consent.
3 Describe your process for evaluating and improving an LLM-based classification system. How do you measure performance and iterate on prompts?
4 What experience do you have with social media APIs? How would you handle adding a new data source like chatbot logs?
5 Why are you interested in AI safety and CLTR specifically? How does this role fit into your career goals?
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⚠️ Common Mistakes to Avoid

  • Don't submit a generic cover letter; it must show specific interest in AI safety and CLTR's mission.
  • Avoid overstating your LLM experience if you lack hands-on prompt engineering or evaluation work—be honest and focus on transferable skills.
  • Don't ignore the GDPR requirement; failing to address it directly can signal a lack of attention to detail.

📅 Application Timeline

⏰ Deadline: August 3, 2026

We recommend applying at least a few days early to avoid last-minute technical issues.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Centre for Long-Term Resilience!

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