DESCRIPTION #### **At Kenos Technology, we are seeking an AI Engineer with extensive experience to develop and evolve the generative AI capabilities of two strategic initiatives in cybersecurity and infrastructure\&operations.** ### **About the position** Responsible for the intelligence layer of solutions: GenAI architecture, model selection and integration, RAG, agents, information processing, evaluation, guardrails, observability, and continuous improvement. You will collaborate with the development team to integrate these capabilities into robust, secure, production-ready applications. Experience with AWS and Amazon Bedrock is especially valued. Development will be conducted using AI-assisted IDEs while maintaining quality and security standards. We seek an agile professional who leverages AI to accelerate development and has experience in "AI-powered development for AI". ### **Key responsibilities** * RAG architectures, agents, tool calling, and AI workflows. * Model selection and evaluation (accuracy, latency, cost, security). * Prompt strategies, memory, context, and tool usage. * Processing of unstructured information (documentation, APIs, feeds, etc.). * Semantic search, embeddings, chunking, reranking, and evidence retrieval. * Agents with tools, validations, and traceable results. * Vulnerability analysis, CVEs, dependencies, and exploitability assessment. * Model evaluation: accuracy, relevance, consistency, security. * Guardrails against hallucinations, prompt injection, and information leakage. * Integration with observability (Dynatrace): tokens, latency, errors, costs. * Python APIs to expose AI capabilities. * Collaboration with Cybersecurity, Data, Cloud, DevOps, and product teams. * Participation in the AI roadmap and evaluation of emerging techniques. REQUIREMENTS * End-to-end experience in GenAI applications. * Solid Python proficiency. * LLMs, prompt engineering, embeddings, RAG, agents. * LangChain and LangGraph. * Agent workflows, tool calling, and controlled reasoning. * Model integration via APIs (context, latency, cost, caching). * Commercial LLMs. * GitHub, testing, CI/CD. * Vector databases and information retrieval. * Chunking, embedding, retrieval, and reranking strategies. * NLP (classification, extraction, clustering, summarization). * Evaluation of models and GenAI applications. * Production-grade Python backend APIs and services. * Dynatrace (observability). * Ability to translate functional and security requirements into scalable solutions. * Critical thinking and effective communication. ### **Preferred qualifications** * AWS (Lambda, ECS, API Gateway, S3, DynamoDB, OpenSearch, IAM, Secrets Manager, CloudWatch). * Terraform, Docker, serverless. * LLMOps, tracing, GenAI evaluation. * AI-assisted IDEs. * CVEs, large volumes of unstructured data. * Regulated environments (security, privacy). * ServiceNow, Wiz, or other IT/Security systems. ### **Competencies** * Product mindset and results orientation. * Converting experiments into production-ready solutions. * Rigor and critical thinking. * Multidisciplinary collaboration. * Documentation and risk communication. #### **What do we offer?** * **Flexible compensation** (meal vouchers, transportation, health insurance, childcare) * **Training:** technology and English * **Work arrangement:** hybrid in Madrid or at central offices. * **Continuous learning:** Professional development and upskilling opportunities * **Flexible working hours and condensed workweek in July, August, and Fridays.** * **Subsidized psychotherapy service.** * **Referral rewards:** Incentives for recommending talent.
David Muñoz
Indeed · HR
David Muñoz
Indeed · HR
