AI Engineer

🕒 May 8

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

TryHackMe

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2018

🔒 Cybersecurity

📚 Education

☁️ SaaS

Cybersecurity • Education • SaaS

TryHackMe is an online learning platform that makes learning and teaching cybersecurity accessible and practical through prebuilt courses, cloud-hosted virtual machines (VMs), and hands-on labs designed for CTFs, workshops, assessments, and training. Launched in 2018, the platform emphasizes practical, deployable environments so users can avoid local VM configuration, and it serves millions of learners while supporting both individual and organizational training needs.

📋 Description

• You'll build and own the AI systems that make Live Breach feel like a real incident rather than a scripted exercise. • The AI attacker agent - an autonomous LLM-powered agent that receives a threat actor profile, a network briefing, and a configured attack chain, then executes it against a live environment. • The exercise orchestration layer - a parallel system that monitors the network during a live exercise, recognises which attack techniques have executed, listens for correct containment and eradication actions from participants, and surfaces investigation tasks tied to real attacker behaviour. • Prompt engineering for both red and blue team agent components, in close collaboration with our content engineering team • Integration with adversary emulation tooling for realistic technique execution • User emulation and noise generation — simulating realistic background activity so participants must distinguish real attacker behaviour from normal log volume • Documentation and architecture that allows the broader engineering team to operate and debug the AI layer without dependency on any single person.

🎯 Requirements

• Hands-on experience building LLM-powered agents — planning loops, tool use, memory, state management • Strong Python engineering; able to ship production-quality agentic systems, not just prototypes • Ability to design prompts and agent architectures that are reliable and predictable under adversarial conditions • Comfortable working autonomously on problems that aren't fully defined — you'll need to make good technical decisions with limited hand-holding • Strong async communication; the team is distributed and documentation matters • Working familiarity with cybersecurity concepts — attack techniques, MITRE ATT&CK, network fundamentals (Active Directory, lateral movement, persistence). • Experience with adversary emulation frameworks (MITRE CALDERA or similar) • Experience building event-driven systems that monitor and react to real-time state changes • Familiarity with cloud infrastructure (we provision VMs and networks dynamically per exercise) • Prior work in the cyber range, red team tooling, or security simulation space • Experience with multi-agent architectures where agents observe and react to each other

🏖️ Benefits

• Remote work options • Professional development opportunities