Ai Engineer

il y a 2 semaines

Paris, France Qevlar AI Temps plein

**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**:

- **Intro call**
- ** Technical interview (Python + system design)**
- ** Problem-solving / investigation deep-dive**
- ** Meet the team**

Sounds like you? Let’s talk.

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