Talavera de la Reina, Castile-La Mancha, Spain
I architect and lead cloud, DevSecOps, and AI-driven transformation initiatives that help organizations modernize complex technology environments and turn them into scalable, secure, and high-performing digital platforms. With 20+ years of international experience across startups, scale-ups, and large enterprises, I’ve worked at the intersection of architecture, platform engineering, and business execution—bridging strategic goals with hands-on delivery. My work focuses on enabling teams to move faster with better reliability, stronger governance, and measurable outcomes. I specialize in cloud-native architecture on AWS, microservices ecosystems, CI/CD at scale, infrastructure as code, observability, and resilient platform operations. I also design and implement practical AI workflows that improve engineering productivity, reduce operational overhead, and support better decision-making in real production environments. Throughout my career, I have helped organizations: • Modernize legacy systems into modular, maintainable, and scalable architectures • Increase release velocity through automation, pipeline optimization, and DevSecOps practices • Improve system resilience and operational visibility with robust observability and proactive monitoring • Strengthen security posture by integrating controls early in the delivery lifecycle • Align technology decisions with business priorities, cost efficiency, and long-term platform sustainability My approach is pragmatic and execution-oriented: understand the real bottlenecks, design for scale and maintainability, and deliver incrementally with clear technical ownership. I value clarity, accountability, and engineering discipline, especially in environments where complexity, speed, and reliability must coexist. I’m particularly motivated by initiatives involving enterprise platform modernization, cloud transformation, AI-enabled engineering operations, and cross-functional technical leadership. I work effectively with CTOs, Heads of Engineering, Product leaders, and delivery teams to translate complex requirements into operationally sound solutions. If you are modernizing a digital platform, scaling engineering operations, or accelerating AI adoption with a strong architecture and execution foundation, I’m always open to connecting with leaders who value technical depth and real business impact. Cloud Architecture | AWS | DevSecOps | Platform Engineering | Microservices | CI/CD | Infrastructure as Code | Observability | SRE Practices | AI Integration for Engineering Workflows | Technical Leadership
I lead the product vision, architecture, and technical strategy behind Opsphere, an AI-powered Operational Intelligence platform that enables engineering, DevOps, and platform teams to interact with complex technology ecosystems through natural language. My work combines Platform Engineering, DevSecOps, cloud architecture, observability, AI agents, LLMs, and MCP to improve operational visibility, incident response, deployment governance, productivity, and decision-making across distributed environments. Key responsibilities and achievements: • Designed and led a multi-tenant platform integrating AWS, Kubernetes, Datadog, Cloudflare, Akamai, Vercel, ArgoCD, GitHub, Bitbucket, Jira, and Confluence. • Built an MCP ecosystem providing secure access to infrastructure, deployments, observability data, cloud services, engineering knowledge, and operational context. • Designed multi-agent workflows using OpenAI, Claude, Mistral, Gemini, and local LLMs for troubleshooting, investigations, root cause analysis, and platform operations. • Developed 200+ operational capabilities accessible through natural language across cloud, DevOps, observability, security, deployment, and engineering environments. • Implemented Prompt Engineering, Context Engineering, RAG, structured outputs, tool orchestration, contextual memory, and workflow automation patterns. • Designed AI-assisted workflows for software delivery, platform operations, contextual code generation, incident investigation, and automation. • Defined governance, security controls, and operational guardrails for enterprise AI adoption and safe interaction with production systems. • Integrated Cursor, Claude Code, Codex, and agentic development environments into real-world delivery processes. • Led product decisions balancing scalability, reliability, security, user experience, and long-term platform evolution.
As DevSecOps Lead, I drive the reliability, security, scalability, and operational excellence of business-critical cloud platforms running on AWS and Kubernetes. My role combines platform engineering, cloud architecture, DevSecOps practices, AI-assisted operations, and production governance to ensure engineering teams can deliver quickly without compromising stability or security. I lead the design and operation of cloud-native environments based on AWS and GitOps principles, supporting large-scale distributed systems with strict availability and performance requirements. Key responsibilities and achievements: Designed and standardized zero-downtime deployment strategies including progressive delivery, rolling releases, automated promotion workflows, deployment verification, and rollback mechanisms. Established GitOps operating models using ArgoCD and Infrastructure as Code practices with Terraform, improving deployment consistency, auditability, and environment governance. Architected resilient AWS and Kubernetes platforms with multi-AZ high availability, workload isolation, disaster recovery considerations, and operational guardrails. Implemented observability frameworks combining metrics, logs, traces, synthetic monitoring, and SLO-driven alerting to improve operational visibility and reduce incident resolution times. Integrated security controls across the software delivery lifecycle including dependency scanning, container security, secrets management, policy enforcement, vulnerability management, and secure access patterns. Led modernization initiatives involving platform automation, operational intelligence, AI-assisted troubleshooting, and engineering productivity improvements. Partnered with engineering leadership, product teams, and business stakeholders to balance delivery velocity, operational resilience, security requirements, and platform scalability. AWS, EKS, Kubernetes, Terraform, ArgoCD, Docker, GitOps, Datadog, Vercel, Istio
Led DevOps transformation, cloud modernization, and platform engineering initiatives for organizations across multiple industries, helping teams build secure, scalable, and highly automated cloud-native platforms while improving software delivery performance and operational reliability. My work combined DevOps, Cloud Architecture, Platform Engineering, automation, distributed systems, and technical leadership, supporting organizations through complex modernization programs and large-scale digital transformation initiatives. Key responsibilities and achievements: • Designed and delivered AWS-based platforms using Lambda, API Gateway, DynamoDB, EC2, S3, Cognito, and CloudFormation. • Architected Kubernetes, microservices, event-driven, and serverless solutions focused on scalability, resilience, security, and operational excellence. • Defined DevOps operating models, engineering standards, cloud governance frameworks, and release management practices. • Led Infrastructure as Code, GitOps, CI/CD, deployment automation, observability, and cloud security initiatives across multiple teams and environments. • Implemented delivery pipelines using GitHub Actions, GitLab CI, Jenkins, Azure DevOps, and ArgoCD. • Improved operational visibility through monitoring, logging, alerting, and incident management practices. • Guided distributed engineering teams through architecture reviews, modernization roadmaps, technical decision-making, and delivery planning. • Mentored cloud engineers, DevOps specialists, and software developers, helping establish strong engineering practices and platform standards. • Supported innovation initiatives involving OpenAI integrations, workflow automation, and AI-assisted business processes. Core technologies: AWS, Kubernetes, Docker, Terraform, ArgoCD, Istio, GitOps, CI/CD, GitHub Actions, GitLab CI, Jenkins, Azure DevOps, Node.js, Java, Spring Boot, Serverless and Microservices.
Designed and implemented enterprise AI solutions focused on Large Language Models (LLMs), Prompt Engineering, AI-assisted workflows, Retrieval-Augmented Generation (RAG), and intelligent automation. My work focused on transforming generative AI capabilities into reliable, production-ready solutions that delivered measurable business value. I specialized in bridging the gap between AI models and real-world systems by designing architectures that combined contextual reasoning, structured outputs, business workflows, and backend integrations. Key responsibilities and achievements: • Designed advanced Prompt Engineering frameworks for OpenAI and other LLM providers, improving response quality, reliability, consistency, and contextual understanding. • Built AI-powered assistants, conversational platforms, and business automation solutions integrating backend services, APIs, enterprise systems, and cloud platforms. • Developed context management and retrieval strategies using embeddings, RAG architectures, dynamic context injection, and knowledge enrichment techniques. • Implemented structured output patterns, tool-calling workflows, validation mechanisms, and prompt orchestration frameworks for production environments. • Designed AI interaction models capable of combining user intent, operational context, business rules, and external data sources. • Collaborated with product, engineering, and business teams to align AI behavior with functional requirements, governance standards, and user expectations. • Contributed to early implementations of AI-assisted development workflows, intelligent knowledge systems, and enterprise productivity solutions. • Established reusable patterns for scalable AI integration across web applications, internal platforms, and operational processes. Core technologies: OpenAI, ChatGPT, Claude, Gemini, Prompt Engineering, RAG, Embeddings, AI Agents, Context Engineering, MCP, Node.js, AWS, Automation Platforms.
I served as Academic Program Lead and Cloud Architect, designing and delivering advanced training programs focused on applied AI, cloud architecture, and modern software engineering practices. My responsibilities combined curriculum leadership, technical mentoring, and hands-on architecture guidance. I translated real-world enterprise challenges into practical learning paths that professionals could apply immediately in their own organizations. Key contributions included: • Led the academic and methodological design of advanced AI and cloud programs for technical professionals. • Built applied learning frameworks based on real implementation scenarios, with a strong focus on delivery speed, code quality, and operational reliability. • Trained and mentored engineers and technical leaders on AI-assisted development workflows and modern engineering practices. • Integrated cloud-native architecture principles (AWS, microservices, serverless, CI/CD) into course modules with production-oriented examples. • Standardized content quality and instructional consistency across sessions, improving learning outcomes and participant adoption. With a background as a software/cloud architect and technical instructor since 2001, I brought a practical and execution-oriented perspective to the program: connecting AI, cloud, and DevSecOps capabilities to measurable business and engineering impact.
Cloud Architect responsible for designing, evolving, and delivering scalable software platforms for clients in finance, healthcare, entertainment, and digital services. Focused on cloud-native architecture, microservices, and DevOps-oriented delivery models in AWS environments, balancing performance, resilience, security, and maintainability. Led architecture decisions for distributed systems using C4, DDD, and hexagonal architecture to improve modularity, reduce coupling, and enable faster, safer releases. Built synchronous and asynchronous integration models aligned with high-availability and fault-tolerant requirements in multi-team, multi-country execution contexts. Architecture, cloud, and engineering stack • AWS & Serverless: Lambda, EC2, S3, DynamoDB, DynamoDB Streams, IAM, CloudWatch, Serverless Framework • Backend & APIs: Node.js, Spring Boot, REST services, event-driven workflows • Microservices & Messaging: Kafka, RabbitMQ • Data Layer: Oracle, MySQL, MongoDB, Redis • DevOps & CI/CD: Jenkins, GitLab CI, Maven, Gradle, SonarQube • Containers & Platforms: Docker, Kubernetes, OpenShift, OpenStack • Automation & Configuration: Ansible, Vagrant • Testing & Quality: JMeter, Cucumber, JBehave, LoadUI Execution and delivery scope • Migrated legacy enterprise workloads (Java/Oracle) to AWS-based architectures with CI/CD pipelines and controlled deployment workflows. • Defined backend architecture for large international banking initiatives, coordinating distributed technical teams across LATAM and Europe. • Implemented microservices and SCS patterns with synchronous/asynchronous communication to support throughput, resilience, and service autonomy. • Drove architecture governance, technical standards, and engineering alignment across development and operations stakeholders. • Delivered practical technology enablement through mentoring and training in cloud, DevOps, microservices, and modern software engineering practices.
Senior J2EE Developer in a Social Content Platform is massively-scalable, socially-aware media aggregation platform. It's designed to let users aggregate all of their social content, while our semantic and social analysis engine provides a highly-personalized stream of recommended content. This aggregator is available on Sony devices (tablets and Sony Xperia mobiles) as Social Live app. Functions: Technological proposals elaboration. Experience in pair programming and use of code review metodologies. Integrated and unitary tests (JUNIT and Mockito). Test Drive Development. RESTful development. Working in Amazon EC2 platform Software development in Architecture J2EE using Spring 3x, AOP (components development for security layer), CXF, Hibernate, Groovy. Interations with Facebook, Twitter, Youtube, Google Reader and RSS feeds by API access. Incursion of DEVOPS Methodology using Chef Server (Opscode) automating all the deployment process. MongoDB interaction for big data processing using spring framework. Redis java connections for quick data access using spring framework. Usage of JBehave for Integration test. Deployment applications in Jetty servers. Android development for client applications test. Usage of SOAPUI for testing and QA process. Usage of Git and Maven in the software development process. Usage of continuous integration tools (Jenkins). Highlight: Facebook Graph integration. JTwitter Integration. Chef Server automatization