Application Guide

How to Apply for Senior Software Engineer

at Recordedfuture

🏢 About Recordedfuture

Recorded Future is the world’s largest and most advanced intelligence company, serving over 1,900 clients globally. Its unique value lies in combining vast data sources—from technical data to threat actor monitoring—with cutting-edge AI to provide actionable threat intelligence. Working here means contributing to a mission-critical platform that defends organizations from cyber threats at scale.

About This Role

As a Senior Software Engineer, you will design and build the next generation of AI Agentic systems that autonomously process and enrich threat intelligence data using LLMs. Your work will directly enhance the speed and accuracy of threat detection, impacting thousands of clients. You’ll also mentor junior engineers and drive technical excellence in a remote-first environment.

💡 A Day in the Life

You’ll start your day with a stand-up to sync with your distributed team, then dive into coding on agent orchestration pipelines or reviewing pull requests. Afternoons might involve collaborating with data scientists on prompt optimization, mentoring a junior engineer, or debugging a production issue. You’ll end the day documenting a new framework or exploring a paper on autonomous agents.

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Interview Prep

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🎯 Who Recordedfuture Is Looking For

  • Experienced in building production-grade, scalable systems with a focus on AI/ML, particularly LLMs and autonomous agents.
  • Proficient in Python and frameworks like LangChain or similar for agent orchestration; hands-on with vector databases and prompt engineering.
  • Strong understanding of software engineering best practices (CI/CD, testing, monitoring) and ability to mentor others.
  • Familiarity with cybersecurity concepts or threat intelligence is a plus, but not required—willingness to learn the domain is key.

📝 Tips for Applying to Recordedfuture

1

Highlight specific projects where you deployed LLM-based agents in production, including challenges like latency, cost, or safety.

2

Showcase your experience with evaluation frameworks for AI agents (e.g., unit tests for prompts, A/B testing for agent behavior).

3

Mention any work with threat intelligence or security data, even if tangential—connect your experience to Recorded Future’s mission.

4

In your resume, quantify impact: e.g., 'Reduced processing time by 40% using autonomous agents'.

5

Tailor your cover letter to emphasize your passion for building reliable AI systems that operate in high-stakes environments.

✉️ What to Emphasize in Your Cover Letter

['Your experience designing and deploying LLM-based autonomous agents in production, with concrete examples of system reliability and scalability.', 'How your technical leadership and mentoring have improved team practices, especially around AI safety and evaluation.', 'Your interest in cybersecurity and how your skills can directly enhance Recorded Future’s threat intelligence capabilities.', 'Your comfort with remote collaboration and asynchronous communication, with examples of distributed team success.']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Read Recorded Future’s blog posts or white papers on AI and threat intelligence to understand their current tech stack and challenges.
  • → Explore their public documentation or API to get a sense of the data types and scale they work with.
  • → Look into their culture and remote work policies on Glassdoor or LinkedIn to align your application with their values.
  • → Familiarize yourself with the competitive landscape (e.g., CrowdStrike, Palo Alto Networks) to understand Recorded Future’s unique position.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Design a system for an autonomous agent that enriches threat intelligence data—walk through architecture, data flow, and failure handling.
2 How do you evaluate the quality and safety of LLM outputs in a production agent? Describe metrics and testing strategies.
3 Discuss a time you optimized a machine learning pipeline for latency and cost. What trade-offs did you make?
4 Explain your approach to mentoring a junior engineer on building reliable software for AI systems.
5 How would you handle an agent that produces incorrect or harmful outputs? Describe monitoring and rollback strategies.
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⚠️ Common Mistakes to Avoid

  • Submitting a generic application that doesn’t mention AI agents, LLMs, or threat intelligence—tailor every section.
  • Overemphasizing academic research without production experience; focus on deployed systems and real-world impact.
  • Neglecting to discuss safety and evaluation of AI systems, which is critical for a company dealing with security data.

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

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 Recordedfuture!

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