AI Engineer – Investigation Data Architect m/f/d

Who we are

Qevlar AI is revolutionizing the SOC with autonomous investigation and, in doing so, solving three key problems for analysts: the cybersecurity talent shortage, alert fatigue, and increasingly complex and sophisticated threats.

Founded in 2023, we’ve already made waves in cybersecurity, AI, and start-up communities. A few highlights:

• Raised $14M in funding led by EQT Ventures and Forgepoint Capital 

• Accepted into Station F’s flagship AI program (Meta, Hugging Face, Scaleway)

• Named by Sifted (Financial Times) as one of Europe’s cybersecurity startups to watch

• Joined Platform 58, La Banque Postale’s premier startup incubator

• Ranked among the top 10 most innovative startups in France by EU-Startups

• Secured early partnerships with major players across EMEA, NAMER, and MENA

• We have some exciting (and impressive) early customers we’re really excited about.

We’re at a pivotal stage — building fast, growing smart, and bringing on sharp minds to shape the future of autonomous cyber defense.

What will you do?

We're looking for an experienced AI Engineer passionate about Data Architecture to help us rethink and rebuild the backbone of our Investigation pipeline — improving performance, scalability, and flexibility.

Your mission in the first 6 months:

• Simplify the Investigation Pipeline
  Refactor or rebuild our existing data flows to reduce complexity and improve maintainability.

• Improve Investigation Speed
  Optimize how we retrieve, process, and serve investigation data to support faster, more responsive systems.

• Enable Multi-LLM Orchestration
  Architect and implement a flexible system that can support multiple LLMs in a single investigation context.

Who we’re looking for

Must-haves

• Proficient in Python

• Strong experience designing data pipelines and working with complex data flows

• Solid understanding of performance optimization (e.g. caching, indexing, parallel processing)

• Comfortable working with and improving legacy systems

• Excellent debugging and problem-solving skills

Nice-to-haves

• Experience with GCP

• Familiarity with Large Language Models (LLMs)

• Background in cybersecurity is a bonus

What success looks like

• Investigations run faster and more reliably

• Developers enjoy a cleaner, more manageable codebase

• Our platform supports diverse LLM use cases efficiently

Our stack

• Backend: Python (FastAPI + SQLAlchemy)

• Infra: GCP

• Pipeline: Custom orchestration system built around LLM-driven investigations

Why Qevlar AI?

• Work on cutting-edge AI infrastructure challenges with a real-world impact

• Contribute to building a secure, AI-native platform changing how cybersecurity is done

• Be part of a tight-knit, high-caliber team that values autonomy and speed

• Opportunity for equity and early-stage ownership

• Remote-friendly, flexible work culture

Hiring process

1. Intro call

2. Technical interview (Python + system design)

3. Problem-solving / investigation deep-dive

4. Meet the team

Sounds like you? Let’s talk.