Senior Data & AI Analyst at F5, Inc. in Dublin

Job description

At F5, we strive to bring a better digital world to life. Our teams empower organizations across the globe to create, secure, and run applications that enhance how we experience our evolving digital world. We are passionate about cybersecurity, from protecting consumers from fraud to enabling companies to focus on innovation. Everything we do centers around people. That means we obsess over how to make the lives of our customers, and their customers, better. And it means we prioritize a diverse F5 community where each individual can thrive. Position Overview The Senior Data & AI Analyst for Resilience Assurance is a hands-on engineering role designed to embed real-time analytics and agentic AI into the organization’s assurance framework. You will build the applications, data pipelines, and AI agents that move traditional compliance monitoring toward continuous, intelligent validation of policies and standards, helping ensure resilience is maintained and strengthened as risks evolve. Resilience expertise is not required; you will work with SMEs who will help you build domain knowledge. Key Responsibilities Real-time policy validation: Build AI-driven systems that continuously monitor and validate adherence to policies, standards, and regulatory requirements, and apply AI tools to evaluate system architectures for resiliency, scalability, and compliance alignment. Predictive analytics for resilience: Develop models that forecast compliance risks, resiliency gaps, and emerging vulnerabilities before they materialize. Agentic AI enablement: Build and deploy autonomous AI agents to simulate resiliency scenarios, monitor controls, and recommend corrective actions in real time. AI-augmented audits: Build pipelines and tooling that make compliance audits continuous and data-driven, with anomaly detection, automated reporting, and predictive insights. Dynamic maturity assessments: Build AI-powered benchmarking tools to track organizational resiliency maturity and project future readiness. Automated control testing: Implement AI frameworks that validate control effectiveness instantly, reducing manual overhead and increasing accuracy. Full-stack delivery: Develop APIs, services, and front-end interfaces that surface analytics and AI outputs to assurance teams, with solid testing, CI/CD, monitoring, and security practices. AI quality and guardrails: Implement evaluation, guardrails, and human-in-the-loop review so AI outputs are accurate, explainable, and auditable. Stakeholder collaboration and roadmap: Work with technical, business, and regulatory partners to turn requirements into working solutions, explain analytics and AI results clearly, and contribute to the 3–5 year plan for embedding AI into assurance. Required Skills & Qualifications Experience: 6+ years of professional software engineering experience. Software engineering: Strong full-stack development experience, including back-end (Python, plus TypeScript/Node or similar), API design, and a modern front-end framework (e.g., React). Data engineering: SQL, data modeling, and pipelines; experience with big data platforms (e.g., Spark, Snowflake); practical machine learning experience. LLM models: Strong understanding of current LLM models, integrations, prompt engineering, RAG, and tool/function calling, for example OpenAI, Claude, Gemini. AI delivery: Experience building and deploying AI-enabled automation, ML models, or agent workflows in a business setting. Technical depth: Understanding of IT architecture and cloud environments (AWS, Azure, or GCP), containers, and CI/CD. Communication: Ability to explain technical trade-offs and data-driven findings to senior stakeholders. Nice to Have Understanding of resilience and compliance frameworks such as ISO 22301 and ISO 27001, and regulatory standards Background in risk, audit, compliance, or IT operations Knowledge of resiliency engineering Data visualization or dashboarding experience (Power BI, Tableau) Advanced AI/ML or clou