Tech Lead - Tech4Dev AI Hub

Driving the next generation of engineering capabilities for Rabobank

Within Tech4Dev, we build and operate the engineering capabilities that enable thousands of engineers to design, build, test and operate software in a secure, compliant and efficient way. The Agentic SDLC Hub extends this mission by introducing AI-driven capabilities and agentic workflows, enabling teams to fundamentally change how software is built across Rabobank. These capabilities represent the next step in Rabobank’s software development lifecycle—where AI supports engineers throughout the entire process, from idea to production.

As Tech Lead for the Tech4Dev AI Hub, you play a key role in shaping and delivering these capabilities, while building strong teams and driving adoption of AI-powered ways of working at scale.

You & your role

As Tech Lead for the Tech4Dev AI Hub, you are responsible for the delivery and evolution of AI-driven engineering capabilities that enable software development across Rabobank. Within the Hub, squads build standardized capabilities, reusable building blocks and adoption patterns that support AI-assisted software delivery—from development and testing to deployment and operations. Your mission is to ensure these capabilities are scalable, reliable and easy to adopt, so teams can turn AI potential into real impact.

You lead multiple DevOps squads with a multidisciplinary composition (engineering, consulting and analysis) and are integrally responsible for IT delivery (24/7), ensuring continuity, performance and control of the capabilities you own. Within the organisation, you are part of the Area Triangle (Tech Lead, Senior Tech Lead, Area Lead, Business Architect) and contribute to the direction and priorities of the Tech4Dev area and the AI Hub.

Examples for practices

• Building capabilities for AI-assisted software development, such as code generation, testing and review
• Turning GenAI and agent-based prototypes into reusable, production-ready capabilities
• Embedding AI-driven capabilities into existing engineering tools, platforms and workflows
• Enabling teams to adopt AI capabilities in a scalable and practical way across the SDLC
• Defining standards for agent design, usage and integration within the engineering landscape

Facts & figures

• Leadership of multiple DevOps squads
• Span of control: approximately 30–40 engineers and specialists
• Impact across a large part of the engineering organisation
• Focus on both innovation and scaling adoption

Top responsibilities

IT Delivery & continuity

• End-to-end responsibility for stable and reliable delivery of AI-driven capabilities (24/7)

People leadership & capability building

• Hiring, coaching and developing a multidisciplinary team

Capability ownership

• Ensure AI capabilities are scalable, maintainable and widely adopted

Engineering culture

• Enable autonomous, high-performing teams and continuous improvement

Standardisation & simplification

• Turn experimentation into reusable and standardised capabilities

Risk, security & compliance

• Ensure responsible, secure and compliant use of AI within engineering capabilities

Stakeholder management

• Navigate a complex environment and align across Tech, Architecture, Data and Business

Financial steering

• Manage budgets and sourcing, including external partners

You & your talent

• Academic working and thinking level
• 5–10+ years experience in complex IT environments
• Experience with DevOps, Agile and large-scale engineering environments
• Strong leadership skills across people, process and technology
• Affinity with AI, GenAI or advanced automation in software development
• Understanding of risk, security and compliance in enterprise environments
• Strong stakeholder management skills
• Entrepreneurial mindset with the ability to drive change