# Applied AI Engineer, Autonomous Defense at Horizon3.ai

- Company: Horizon3.ai
- What the company does: Horizon3 uses real-world attacks to safely show what attackers can actually do in your environment—so you can fix and prove what matters. Backed by NEA.
- Company website: https://horizon3.ai/
- Type: Startups (AI role)
- Level: Mid level
- Location: US, Remote
- Work setup: Remote
- Pay: $313K to $369K base salary per year (USD)
- Posted: 2026-09-14
- Apply by: 2026-10-29
- Apply: https://jobs.ashbyhq.com/horizon3ai/c87e8623-770a-489f-9ab1-1be4a37a3263
- Page: https://www.1752.vc/careers/jobs/horizon3-ai-applied-ai-engineer-autonomous-defense/

## About the role

We're looking for an AI Researcher to build the agents that turn our offensive knowledge into defensive action. You'll build agents that reason from a proven attack path to the specific control changes that break it - EDR policy, firewall and segmentation rules, conditional access, detection content, cloud IAM, GPO - apply or stage those changes in the customer's environment, and then prove the fix by re-running the attack.

## What they're looking for

- Strong ML engineering experience building, evaluating, and deploying production AI systems, with hands-on work in deep learning, transformer models, and PyTorch
- Hands-on experience with at least one of: post-training large language models (supervised fine-tuning, distillation, preference optimization, RL), or designing agentic systems with tool use, planning, and long-horizon execution that hold up outside a demo
- A track record of building evaluation systems for open-ended tasks where there is no clean label and success is judged by outcome
- Experience reasoning over structured, heterogeneous, messy real-world data — configurations, graphs, logs, policy documents — rather than clean benchmark datasets
- Strong software engineering fundamentals and a track record of shipping and maintaining production-quality code in Python, not just scripts and proofs of concept
- Experience with data pipelines, distributed systems, and cloud infrastructure, preferably AWS

Tags: Engineering