Senior DevSecOps Engineer (Porto/Lisboa)

🚀 About the Role We are looking for a Lead DevOps & Platform Automation Engineer to drive the transformation of software delivery, infrastructure management, security automation, and developer experience across CIB. In this role, you will design reusable automation capabilities, build internal self-service platforms, and eliminate repetitive operational work across Development, Security, and Operations. You will also lead experimentation with emerging technologies, including GitOps, policy-as-code, advanced observability, service mesh, and AI agents for DevOps. This is a high-impact position for someone who combines strong technical expertise with architectural vision, an innovation mindset, and the ability to influence engineering practices across multiple teams. 🎯 Your Mission As a Lead DevOps & Platform Automation Engineer, you will: - Eliminate manual development and operational work through automation. - Design enterprise-grade CI/CD and Infrastructure as Code capabilities. - Build an internal self-service platform that enables teams to deploy independently. - Embed security, compliance, and quality controls into delivery pipelines. - Improve developer productivity and reduce friction across the engineering lifecycle. - Lead prototypes and Proofs of Concept for emerging automation technologies. - Use DORA and platform metrics to drive measurable improvements. - Pioneer the responsible use of AI agents for infrastructure, deployment, security, and incident remediation. - Establish standards and reusable practices for automation excellence. 💼 Key Responsibilities CI/CD & Delivery Automation - Design and implement scalable CI/CD frameworks across CIB. - Build reusable pipeline templates and automated delivery workflows. - Automate build, testing, security validation, release, and deployment processes. - Establish fast feedback loops that provide developers with rapid and actionable results. - Reduce deployment lead time while improving reliability and traceability. - Implement deployment strategies that support safe rollbacks and recovery. - Promote consistent delivery practices across multiple engineering teams. Infrastructure as Code & GitOps - Automate infrastructure provisioning using Infrastructure as Code principles. - Build reusable and secure infrastructure modules. - Establish GitOps practices for configuration management and deployment. - Ensure that infrastructure changes are repeatable, traceable, and auditable. - Promote immutable and idempotent infrastructure patterns. - Implement automated validation and testing for infrastructure changes. - Reduce dependence on manual provisioning and configuration activities. Container Platforms & Orchestration - Drive the adoption of containerization using Docker. - Design and improve orchestration capabilities using: - Kubernetes - OpenShift - Create standardized patterns for application packaging and deployment. - Improve workload scalability, availability, and operational resilience. - Implement health checks, autoscaling, restart mechanisms, and automated remediation. - Reduce the operational complexity exposed to development teams. Self-Service Platform Engineering - Design and maintain an internal engineering platform covering: - CI/CD - Infrastructure as Code - Observability - Security scanning - Environment provisioning - Application deployment - Create Platform-as-a-Service abstractions that hide infrastructure complexity. - Build self-service capabilities for: - Environment provisioning - Application deployment - Configuration - Rollbacks - Operational monitoring - Enable developers to deliver applications securely without requiring repetitive manual reviews. - Create reusable platform capabilities for transversal and business IT teams. - Define platform documentation, onboarding materials, and usage standards. Developer Experience & Productivity - Identify and measure developer toil across the delivery lifecycle. - Work directly with development teams to understand engineering pain points. - Simplify onboarding so new engineers can become productive quickly. - Create intuitive platform workflows that require minimal infrastructure knowledge. - Automate repetitive development, operational, and compliance activities. - Collect feedback from platform users and incorporate it into the roadmap. - Improve the usability, reliability, and adoption of internal engineering tools. Security & Compliance Automation - Integrate security controls into the software delivery lifecycle. - Automate: - Static Application Security Testing - Dynamic Application Security Testing - Dependency scanning - Container scanning - Compliance checks - Secrets detection - Implement automated security gates that prevent non-compliant releases. - Work with tools such as: - SonarQube - Checkmarx - OWASP ZAP - Trivy - Aqua Security - Implement secure secrets management using: - HashiCorp Vault - AWS Secrets Manager - Apply policy-as-code using technologies such as: - Open Policy Agent - Kyverno - Support compliance requirements including PCI-DSS, GDPR, and SOX. - Ensure security automation produces traceable and auditable evidence. Observability & Operational Resilience - Design observability capabilities across applications, infrastructure, pipelines, and platforms. - Implement monitoring, logging, tracing, and alerting using: - Prometheus - Grafana - ELK Stack - Datadog - Splunk - CloudWatch - Jaeger - New Relic - Build dashboards that provide real-time visibility into platform health and delivery performance. - Improve root cause analysis using distributed tracing and correlated telemetry. - Implement self-healing infrastructure that minimizes human intervention. - Support incident response, operational troubleshooting, and postmortem activities. Innovation & Technology Prototyping - Lead innovation lab activities focused on DevOps, security, observability, and platform engineering. - Prototype and evaluate technologies such as: - Service Mesh - GitOps Platforms - Policy-as-Code - Advanced Observability - AI4DevOps - Build Proofs of Concept to validate technical value, risks, and integration requirements. - De-risk emerging technologies before wider organizational adoption. - Conduct technology watch across DevOps, cloud, security automation, and AI-assisted operations. - Present findings and recommendations to senior technology stakeholders. - Transfer knowledge and reusable capabilities to development and business IT teams. Automation Standards & Community Enablement - Define platform engineering and automation standards. - Establish reusable reference implementations and engineering patterns. - Promote consistent automation practices across multiple teams. - Create training materials, workshops, and technical documentation. - Mentor engineers on CI/CD, GitOps, Infrastructure as Code, observability, and security automation. - Build an internal community focused on automation and engineering excellence. 🤖 AI4DevOps & Intelligent Automation AI Agent Development - Design and deploy AI agents supporting: - Infrastructure provisioning - Deployment automation - Incident analysis - Remediation recommendations - Operational troubleshooting - Security analysis - Integrate AI capabilities with existing DevOps and platform workflows. - Use LLM-based tooling to improve automation, decision support, and engineering productivity. - Develop infrastructure code that is predictable, idempotent, and safe for AI-assisted execution. AI Agent Governance - Establish governance principles for AI agents operating in engineering environments. - Define permissions and privilege boundaries. - Implement containment and sandboxing strategies. - Create approval and escalation mechanisms for sensitive actions. - Maintain audit trails and decision logs for agent activity. - Define clear boundaries between autonomous actions and human intervention. - Design hybrid human-AI operational workflows. AI-Driven Security - Apply LLM-based approaches to threat modelling and security analysis. - Use AI to identify potential attack paths and weaknesses earlier in the lifecycle. - Support a shift from reactive compliance toward proactive security hardening. - Ensure AI-assisted recommendations are reviewed and controlled appropriately. AI Observability & Data Governance - Implement monitoring and tracing for AI agents. - Capture agent actions, decisions, confidence indicators, and execution outcomes. - Define data governance policies for AI-enabled operational workflows. - Prevent unauthorized data exposure or exfiltration. - Apply redaction and data minimization where required. - Ensure AI agent actions remain explainable, controlled, and auditable. 📊 Metrics & Continuous Improvement DORA Metrics Use engineering metrics to drive improvements in: - Deployment frequency - Lead time for changes - Mean Time to Recovery - Change failure rate The target operating model should progressively enable: - Daily or multiple daily deployments where appropriate. - Reduction of delivery lead time from weeks to days or hours. - A reduction of at least 50% in recovery time. - Fewer failed deployments and faster rollback or remediation. Automation Coverage Drive the engineering organization toward: - 100% Infrastructure as Code coverage - 90%+ automated security validation - 95%+ testing automation - 90%+ adoption of self-service deployments Lean & Continuous Improvement - Identify delivery bottlenecks and formulate improvement hypotheses. - Run controlled experiments and measure their outcomes. - Standardize practices that demonstrate measurable value. - Use metrics to prioritize engineering improvements. - Promote continuous learning through incident reviews and delivery retrospectives. ✅ What We’re Looking For Mandatory Requirements - Bachelor’s degree in Computer Science, Engineering, or equivalent professional experience. - At least 5 years of experience in: - DevOps - Platform Engineering - Infrastructure Engineering - Site Reliability Engineering - A related engineering role - At least 3 years of experience driving technical innovation, prototyping technologies, or leading architectural improvements. - Proven experience reducing manual work and improving engineering delivery. - Expert knowledge of Infrastructure as Code principles. - Strong experience designing CI/CD frameworks. - Deep knowledge of Docker, Kubernetes, or OpenShift. - Strong Linux/Unix administration skills. - Advanced Git and branching strategy knowledge. - Experience with at least one major cloud platform: - AWS - Microsoft Azure - Google Cloud Platform - Experience embedding security and quality controls into delivery pipelines. - Strong understanding of monitoring, logging, tracing, and production operations. - Proficiency in at least one programming or scripting language. - Strong communication and technical leadership capabilities. 🛠 Technical Stack CI/CD & Version Control - Jenkins - GitLab CI - GitHub Actions - Git - GitFlow - Branching Strategies - Release Automation Infrastructure & Platforms - Infrastructure as Code - GitOps - Linux - RHEL - CentOS - Ubuntu - Docker - Kubernetes - OpenShift Cloud - AWS - Microsoft Azure - Google Cloud Platform Security Automation - SonarQube - Checkmarx - OWASP ZAP - Trivy - Aqua Security - HashiCorp Vault - AWS Secrets Manager - Open Policy Agent - Kyverno Observability - Prometheus - Grafana - ELK Stack - Datadog - Splunk - CloudWatch - Jaeger - New Relic Software Engineering - Python - Go - Java - Bash - REST APIs - Microservices - Event-Driven Systems - Automated Testing AI4DevOps - AI Agents - Large Language Models - Prompt Engineering - LangChain - AutoGen - Agent Governance - AI Observability - Human-AI Workflows ⭐ Nice to Have - Experience in Financial Services or other regulated industries. - Open-source contributions or active technical community involvement. - Service mesh experience using: - Istio - Linkerd - GitOps platform experience with: - Argo CD - Flux - Experience designing or operating Internal Developer Platforms. - Incident response and postmortem facilitation experience. - Practical experience developing or governing AI agents. - Experience presenting technical strategy to senior technology leadership. - Previous responsibility for an Automation or Platform Engineering Center of Excellence. 🤝 Soft Skills Innovation Mindset - Curiosity and willingness to experiment with emerging technologies. - Comfortable prototyping quickly and learning from unsuccessful approaches. - Ability to turn relevant innovations into maintainable enterprise capabilities. Entrepreneurial Drive - Strong ownership and bias toward action. - Ability to identify opportunities and execute without excessive direction. - Focus on measurable outcomes rather than technology adoption for its own sake. Communication & Influence - Ability to communicate with both technical and non-technical stakeholders. - Confidence presenting architectural recommendations and technical findings. - Capacity to influence teams without relying solely on formal authority. Collaboration - Strong ability to work across Development, Security, Operations, Architecture, and Business IT. - Comfortable aligning teams with different priorities and maturity levels. - Focus on building reusable solutions rather than isolated team-specific implementations. Teaching & Mentoring - Passion for sharing knowledge and supporting engineering growth. - Ability to explain automation and platform concepts clearly. - Comfortable creating standards, documentation, and practical training.