• Technical reference for enterprise AI solutions, with mastery of the full solution lifecycle. • Expertise in scalability, microservices architecture, and data engineering applied to AI. • Leadership in strategic, high-impact projects with a focus on innovation and digital transformation. • Ability to define technical guidelines, roadmaps and AI strategies aligned with business objectives. • Strong emphasis on security, data governance and algorithmic responsibility. • Influence in organizational decisions, acting as a bridge between technology and executive areas. • Active contribution to the development of an AI culture within the organization, promoting training and knowledge sharing. • Systemic vision and the ability to anticipate technological trends to position the company competitively. • Leads development and integration of AI components (such as LLMs, agents, predictive models) into corporate applications and systems. • Influences architecture, technology and solution roadmap decisions. • Conducts technical diagnostics and assessments, identifying opportunities to improve and evolve existing solutions. • Facilitates communication between business and technology teams, translating strategic needs into high-impact solutions. • Prepares presentations and supporting materials for technical meetings and stakeholder alignment. • Shares knowledge on AI frameworks, APIs, and microservices. • Leads discussions with DevOps, Engineering and Security teams, ensuring solution scalability. • Leads exploration and application of cutting-edge technologies (LLMs, autonomous agents, generative AI), promoting continuous innovation.

Role Description QuoIntelligence turns millions of raw signals into finished Cyber Threat Intelligence (CTI) that security teams across Europe act on every day. The ML team is small (2 people today), and the infrastructure is lean. You will own end-to-end production systems, from improving existing NLP pipelines, fine-tuning LLMs, building evaluation frameworks, and orchestrating AI agents in the cyber domain. What You'll Do - Improve the production ML stack. - Own model evaluation end-to-end. - Ship something the stack can't do today. - Expand agent capabilities. - Work directly with the IntelOps team. AI-First in Engineering - You build with AI-assisted tools daily, but you also know when AI-generated code introduces risk. - You evaluate new AI tools critically, adopting what works and dropping what doesn't. - Every model and pipeline has a clear definition of success before it ships. Qualifications - Production ML deployment. - NLP and LLM grounding. - Comfort with messy data. - Python: It's the team's language. - Open-source mindset. - AI fluency. Nice-to-haves - Experience with agent frameworks (LangGraph, LangChain, or similar). - Fine-tuning experience with open-source models (Qwen, LLaMA, Mistral). - Experience with inference servers and popular backends (e.g. NVIDIA Triton, vLLM, etc). - Familiarity with data orchestration tools (Kestra, Airflow, Prefect). - Cybersecurity or threat intelligence domain knowledge. What We Offer - A small team where your work hits customers. - Ownership, not just tickets. - Constraints that force creativity. - Ethical red lines. - Growth trajectory. The Process - Recruiter Screen. - AI fluency screen. - Take-home task: a real evaluation problem from the team's work. - Hiring manager interview. - CEO/CTO Interview. - Offer and Background Check. We welcome applications regardless of gender, nationality, ethnic origin, religion, disability, age, or sexual identity. Diversity is key to producing high-quality intelligence.

• We're looking for a visionary engineer with an "Automation First" mindset who will rethink our core processes and make our system ecosystem smarter. • Analyze our key value streams (e.g., Purchase-to-Pay), develop the automation roadmap, and deliver measurable business impact (e.g., reducing cycle times and error rates). • Build predictive monitoring and self-healing mechanisms for our critical interfaces to resolve issues before they occur. • Develop systems for automated analysis and resolution of support tickets to reduce manual workload for the team. • Build reusable automation services and expose them to the entire company via our internal AI platform (ChatAPV). • Act as the technical sparring partner for business units and product owners to unlock automation potential across the organization.

• Ayudarás a diseñar, desarrollar y mantener modelos de IA escalables y eficientes, optimizando el rendimiento y reduciendo costos. • Colaborarás estrechamente con científicos de datos, ingenieros de software y gerentes de producto para integrar modelos de IA en sistemas más amplios y garantizar su funcionamiento adecuado. • Analizarás grandes volúmenes de datos para desarrollar modelos predictivos que resuelvan problemas específicos de los clientes. • Trabajarás en la mejora continua de sistemas y algoritmos para maximizar la eficiencia y fiabilidad. • Utilizarás plataformas en la nube (AWS, Google Cloud, Azure) para implementar soluciones de IA, aprovechando los servicios de la nube para mejorar el rendimiento y reducir costos. • Te mantendrás al tanto de las últimas tendencias en IA y aprendizaje automático, aplicando nuevas tecnologías y enfoques en los proyectos de Creai. • Documentarás el proceso de desarrollo y presentarás resultados tanto a públicos técnicos como no técnicos.