20 publicaciones de empleo destacadas de ai security architect en madrid provincia (¡Están contratando!)

AI Architect (AI for Security)
Neurons Lab —Madrid, Madrid provincia
- Jornada completa
- Teletrabajo
- Máster
- AWS
- Inteligencia artificial
Security Architect - AI Trainer - Freelance - 8-20hrs/week - Remote
10x Team —Madrid, Madrid provincia
- De 103 € a 159 € por hora
- Teletrabajo
- Inteligencia artificial
Solicitud rápida
AI Security Architect
Beam Inc. —Madrid, Madrid provincia
- Español
- Azure
- Grado
Senior AI Architect - Microsoft Technologies (relocation to the Netherlands)
EPAM Systems, Inc. —Madrid, Madrid provincia
- Azure
- DevOps
- AWS
- Programa de recomendación
- Plan de pensiones
2d
AI & SaaS Security Expert / Cybersecurity Professional (f/m/d)
Siemens —Tres Cantos, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Inglés
- Máster
- Inteligencia artificial
8d
Lead AI Architect
The Cigna Group —Madrid, Madrid provincia
- Jornada completa
- Azure
- Informática
- Inglés
Senior Generative AI Tech Lead / Architect (m/f/d)
Siemens —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Azure
- Doctorado
- Informática
Enterprise Security Architect - Security Detection and Response
ING —Madrid, Madrid provincia
- Azure
- Inglés
- Oficina
- Seguro de vida
- Plan de pensiones
Associate Security Architect, Madrid (M, ES)
Swiss Re —Madrid, Madrid provincia
- De 41.000 € a 68.000 € al año
- Jornada completa
- Informática
- Inglés
- Desarrollo de software
- Teletrabajo opcional
AI Architect (Agentic AI)
Kyndryl —Madrid, Madrid provincia
- Jornada completa
- Azure
- Doctorado
- Máster
Senior Security Architect, Madrid (M, ES)
Swiss Re —Madrid, Madrid provincia
- De 60.000 € a 100.000 € al año
- Jornada completa
- Trabajo híbrido
- Servicios financieros
- Inteligencia artificial
Senior AI Platform Engineer/AI Architect - Microsoft Technologies (relocation to the Netherlands)
EPAM Systems, Inc. —Madrid, Madrid provincia
- Azure
- DevOps
- Java
- Programa de recomendación
- Plan de pensiones
7d
Lead AI Architect, Madrid (M, ES)
Swiss Re —Madrid, Madrid provincia
- De 60.000 € a 100.000 € al año
- Jornada completa
- Azure
- Java
- Inteligencia artificial
Forward Deployed AI Engineer
Keyrus Spain —Alcobendas, Madrid provincia
- De 70.000 € a 85.000 € al año
- Jornada completa
- Trabajo híbrido
- Azure
- Informática
- Inglés
Solicitud rápida
AI Solutions Architect
MSX International —Madrid, Madrid provincia
- De 35.000 € a 55.000 € al año
- Jornada completa
- Trabajo híbrido
- Informática
- Inglés
- Máster
Solicitud rápida
AI Systems Architect
Kyndryl —Madrid, Madrid provincia
- Jornada completa
- Español
- Inglés
- Máster
SAP AI Consultant | Multiple Modules | All Levels (1+ Years Experience)
Accenture —Madrid, Madrid provincia
- Jornada completa
- Ventas
- Inglés
- Máster
10d
Senior Product Engineer / AI Solution Architect
SCH Banco Santander, S.A. —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Español
- Azure
- Informática
- Abono gimnasio
- Seguro de vida
13d
Gestor de Cambios
Kyndryl —Tres Cantos, Madrid provincia
- Jornada completa
- DevOps
- Sistema operativo Windows
- AWS
Solutions Architect (AWS AI/ML, Data & Cloud Modernization)
RevStar —Madrid, Madrid provincia
- Jornada completa
- Teletrabajo
- AWS
- Grado
- Machine learning
- Seguro dental
- Vacaciones pagadas
Solicitud rápida
23h

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AI Architect (AI for Security)

Neurons Lab
Madrid, Madrid provincia

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Detalles del empleo

Jornada completa

Cualificaciones

Pentest
Derecho
Máster
AWS
Respuesta a incidencias
Metasploit
Burp Suite
Cloud
SIEM
Inteligencia artificial
Python

Descripción completa del empleo

About the project (description, duration, stage)

Hands-on AI-for-Security engagement with a regulated iGaming / online-gaming group. The client's security team is genuinely advanced: they already run an AI-driven offensive-security capability — continuous external-perimeter scanning feeding an LLM agent that plans exploitation, sources and validates exploits, and executes them in sandboxed environments — plus a runtime anomaly-detection layer watching for intrusion and privilege-escalation patterns across their products. They built this themselves and have explicitly asked us to challenge and improve it, not just rubber-stamp it.

This is not a generalist AI project. Neurons Lab brings the AI-architecture and engagement depth; what's missing is the offensive-security domain lead who can sit across the table from a hands-on CISO team as a peer, pressure-test their pipeline, and own the methodology. You are that expert. The early work is concrete and consultative: understand what they've built, find where it's wrong or expensive, and propose a better way.

Stage: pre-engagement / discovery (the immediate next step is a joint technical session with the client's CISO / security engineers). Duration: discovery advisory / PoC, with strong extension probability as the security program scales across the group.

Reporting: Neurons Lab CTO / engagement lead (@Alex Honchar); partners with the Neurons Lab AI Architect on the account. You are the security domain owner for this track.

What you'll actually do (example tasks)

Join joint working sessions with the client's hands-on security engineers; challenge and harden their AI-driven offensive pipeline end-to-end (recon verification AI-planned exploitation sandboxed execution).
Design and refine the exploitation agent: how the LLM plans attack paths, selects and validates exploits, and orchestrates parallel sandboxes safely and reproducibly.
Optimise cost-per-finding of the existing exploitation pipeline: benchmark local / sovereign open models (Kimi, GPT-OSS, MiniMax, DeepSeek) against frontier models for the recon, exploitation and analysis loops; quantify accuracy / latency / cost trade-offs and recommend hardware sizing.
Shape the runtime anomaly-detection layer: define which intrusion / privilege-escalation precursor patterns are worth collecting (signal over raw-log volume), and design the missing pieces — automated response (kill a malicious process / disable an account on detection) and triage routing by criticality.
Stand up a quick-win PoC to anchor the engagement — e.g. an automated dependency / PR vulnerability-scanning pass, or a head-to-head local-vs-frontier benchmark of the exploitation agent.
Turn findings into a defensible technical proposal and roadmap; present methodology and trade-offs to a technical CISO / CTO audience.
Keep all sensitive work build-time and in-perimeter — no pushing intellectual property, configs, or recon-enabling data to external model providers; respect regulated-gaming certification constraints (no uncertified AI in runtime-critical paths).

Skills (hands-on first)

Hands-on offensive security: vulnerability research, exploit development and chaining, web + network penetration testing; fluent with Nmap, Nuclei, Katana, Acunetix, Metasploit, Burp Suite and Kali tooling.
Building and operating LLM agents for security work — agentic tool-use, sandbox orchestration, prompt / flow design for recon and exploitation, guardrails for autonomous exploitation.
Local / self-hosted open models: running and tuning open weights (Kimi, GPT-OSS, MiniMax, DeepSeek) on rented or private GPU; quantization, throughput and the agentic-performance trade-offs that matter for security automation.
Exploit & threat intelligence: sourcing and validating exploits (including from underground / forum sources), CVE triage, exploitability and severity assessment.
Runtime detection: designing intrusion / privilege-escalation pattern detection, anomaly detection, and automated response.
Cloud security (AWS preferred): sandboxing, container isolation, secure inference hosting.
Writes their own code (Python + shell) and can explain methodology to non-security executives.

Knowledge

Modern offensive-security methodology and the current exploit / zero-day landscape.
Strengths and limits of frontier vs. local LLMs for security automation (agentic tool-use, reasoning depth, cost-per-task).
Data-egress / sovereignty constraints: why IP and recon-enabling data must stay in-perimeter; private-cloud (AWS Bedrock) vs. rented-hardware trade-offs.
iGaming / regulated-infrastructure context and certification constraints (build-time vs. run-time AI) — strong plus.
Defensive side — SIEM, anomaly detection, incident response — plus.

Experience

Key characteristics (ideally 4/4):

Hands-on offensive security
Built or operated AI / LLM-driven security automation (agents, pipelines), not just used a chatbot
Cloud hyperscaler experience (AWS preferred)
Technology consulting / client-facing delivery — can lead a CISO-level technical conversation

Role-specific characteristics:

3+ years hands-on offensive security / vulnerability research / red-team
Demonstrable exploit development and chaining; comfortable with zero-day research and exploit intelligence
Has wired LLMs into real security workflows (recon, exploitation, triage)
Has run self-hosted / local open models in a real engagement, with a view on cost and hardware
Comfortable being the sole domain expert in the room and owning the methodology

Terms & conditions

Allocation: ~0.25 – 0.5 FTE initially (discovery/advisory + joint CISO sessions), scaling with the engagement

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