Generative AI Engineer

For a major Dutch financial institution, we are looking for an experienced Agentic Hub Engineer to join a newly formed internal engineering team focused on building AI tooling for software development teams. The team’s mission is to develop AI assistants and agents that support developers across the software delivery lifecycle, including backlog refinement, code generation, code review, testing and delivery efficiency. Solutions built by this team will be rolled out across development teams throughout the organization, meaning successful improvements can have significant enterprise-wide impact. This is a largely greenfield environment. The team is newly established, strategically sponsored, and offers the opportunity to define standards, patterns and ways of working from the start. Role Description As an Agentic Hub Engineer, you will design, build and improve AI-powered tools and agents for internal software engineering teams. You will work hands-on with modern GenAI and agentic tooling, while applying strong software engineering fundamentals. This role is best suited for an engineer-first profile: someone with deep software delivery experience who has also developed strong practical knowledge of coding agents, AI-assisted development and agentic workflows. Key Responsibilities Build AI assistants and agents that support the software delivery process.Develop tooling for refinement, code generation, code review, testing and backlog support.Turn prototypes into robust, reusable building blocks for wider adoption.Make architectural and engineering trade-offs around speed, cost, reliability and governance.Define reusable standards and patterns for agentic tooling.Coach fellow engineers on using coding agents effectively.Support adoption of AI-assisted engineering practices across development teams.Help define how the impact and value of AI developer tooling should be measured.Experiment with new approaches while ensuring solutions are scalable, maintainable and fit for enterprise use. Required Experience and Skills The ideal candidate has: 5+ years of experience in software engineering, DevOps, ML engineering or data science.Proven experience delivering software end-to-end, from design through production and operations.Strong software engineering fundamentals.Cloud experience.Experience with Infrastructure as Code, such as Terraform or Bicep.Ability to work across different languages, frameworks and technology stacks.Hands-on experience with coding agents and agentic tooling.Experience using AI tools in production environments or serious side projects.A demonstrable prototype, hobby project, repository or build that shows practical maker energy.Residence in the Netherlands and the right to work there. Preferred Profile The strongest candidates are experienced engineers who were building and shipping software before the current GenAI wave and have since become deeply involved in coding agents and AI-assisted development. Prompt engineering alone is not sufficient for this role. The ideal candidate combines strong engineering depth with hands-on curiosity, experimentation and practical experience in building agentic solutions. Competencies The candidate demonstrates: Strong engineering ownership.Practical, prototype-driven mindset.Ability to move quickly while balancing reliability and governance.Curiosity and enthusiasm for AI-assisted software delivery.Strong problem-solving skills.Ability to coach and influence other engineers.Comfort working in a greenfield environment.Pragmatic decision-making across speed, cost, quality and scalability.Strong collaboration skills within technical teams. Candidate Profile This assignment is ideal for a senior engineer who enjoys building practical AI tooling that improves how software teams work. You are technically strong, hands-on and comfortable experimenting with new agentic tooling, but you also understand what it takes to bring software into production within a complex enterprise environment. You bring maker energy, solid engineering fundamentals and the ability to turn promising AI prototypes into reusable, scalable tools that create measurable value for development teams.