Agentic SDLC Hub Consultant (the new Hub)

Help shape how more than 1,000 squads build software with AI across Rabobank

You & your role

How do you help engineering teams turn AI potential into everyday impact?

As Agentic SDLC Consultant, you help Rabobank teams improve how they design, build, test and operate software by applying artificial intelligence, coding agents and reusable delivery practices. You guide teams through change, create clarity in complex situations and help scale successful approaches across the engineering organisation.

Who we’re looking for

Tenacious consultants who are passionate about helping teams improve how they deliver software, and able to connect technology, process and people. You understand modern engineering, GenAI and agentic workflows well enough to challenge assumptions, shape solutions and do hands-on work when needed. At the same time, your main strength is creating clarity, building alignment and helping squads adopt new ways of working in a practical, sustainable way.

Your mindset matters

Are you an entrepreneurial change-maker whose ideas deserve to be heard? In the Hub, leadership actively backs fast innovation, removes roadblocks and creates room to experiment, learn and scale what works. This is a place for people who want to help define a new engineering model, bring others along in the transition and turn early potential into repeatable impact.

What makes this role special

• Work in a hub designed for people who want to shape the next era of software engineering adoption.
• Freedom to experiment, learn and move fast—with visible leadership sponsorship.
• A chance to help scale reusable capabilities and adoption patterns across 1000+ squads.
• We value curiosity, resilience, sharp consulting judgment and the ability to turn technology into real organisational change.

Examples from practice

• Helping squads identify where AI assistants and agents can improve backlog refinement, code generation, code review, testing and broader software delivery workflows.
• Coaching engineers, product owners and leaders on effective use of GenAI and coding agents in day-to-day software development.
• Improving developer experience by embedding agentic capabilities into existing tools, platforms, ceremonies and engineering workflows.

Top 3 responsibilities

1. Lead practical adoption of GenAI and agentic software delivery by helping teams translate opportunities into scalable ways of working.
2. Design and guide adoption strategies across developer journeys, AI workflows, operating models and engineering practices that deliver measurable value.
3. Act as a trusted advisor who creates clarity, enables change and helps teams make better technical and organisational decisions.

You will join the new Agentic SDLC Hub, a transformation engine created to accelerate how Rabobank designs, builds, tests and operates software with AI. The Hub combines technology, people and processes to create reusable capabilities and adoption patterns that can be used across the bank.

We’re not looking for GenAI enthusiasts who only talk about the hype, nor for super technical builders who want to spend day and night running agents in isolation. We’re looking for exceptional consultants with solid engineering credibility. People who understand the technology deeply enough to guide teams, prototype where needed and help Rabobank move from experimentation to adoption.

If your career combines software delivery experience with advisory, facilitation or transformation work, you’ll feel right at home. We value people who can speak the language of engineers, understand the fundamentals, and also create the confidence, structure and momentum needed for teams to change how they work.

Together we achieve more than alone

The members of the Agentic SDLC Hub help define the future of software delivery within Rabobank. Collaboration is our way of working; as one entrepreneurial and technical team within Rabobank. Together, you will experiment, learn, create reusable capabilities and help engineering teams adopt new ways of working at scale.

You & your talent

Consulting & Technical Leadership:

• Assess team needs and shape practical GenAI and agent adoption strategies.
• Lead solution and adoption design across APIs, AI workflows, developer journeys and operating models.
• Evaluate tools and frameworks pragmatically, balancing technical value with adoption effort and organisational fit.
• Ensure performance, security, cost-effectiveness and responsible use are considered in GenAI adoption decisions.

Collaboration & Stakeholder Engagement:

• Collaborate with engineering, platform, product and business teams to translate opportunities into scalable capabilities and adoption plans.
• Collaborate on the design and rollout of AI workflows, including prompt engineering, orchestration, tooling, reusable context and change interventions.
• Communicate technical concepts effectively to both technical and non-technical stakeholders, creating clarity and shared direction.
• Act as a trusted advisor on agentic engineering strategy, adoption risks, platform scalability and operational excellence.

Soft Skills & Leadership Qualities:

• You are relentless in helping teams move forward: you create structure, adapt when conditions change and find pragmatic ways to deliver outcomes.
• Entrepreneurial mindset – you spot valuable opportunities, prototype fast and know how to build momentum around ideas that can change how teams work.
• Excellent facilitation and communication skills – able to simplify complex ideas, manage different perspectives and build trust across teams.
• You combine technical credibility with strong product and change intuition.
• You challenge solutions that are complex but low-impact, switch comfortably between strategic and hands-on conversations, and are comfortable making decisions with incomplete information — learning quickly through experimentation.

Required Qualifications:

• 5+ years in roles that combine technology delivery with consulting, transformation, product, DevOps, Software Engineering, ML Engineering or Data Science.
• Proven experience supporting teams across the full software delivery lifecycle: from discovery and architecture through implementation, testing, deployment and adoption.
• Sufficient hands-on engineering ability to prototype, review technical choices and work credibly with engineers across languages, tools and system boundaries.
• Proven experience with coding agents and agentic development tools in practice—whether in delivery work, serious side projects or prototypes—and a strong affinity for how they can transform software engineering.
• Ability to turn ambiguous problems into clear recommendations, practical experiments and adoption roadmaps that deliver measurable value.
• Security and observability awareness: best practices for monitoring, compliance, and reliability in AI systems.
• Excellent communication skills with the ability to mentor, facilitate and lead technical teams through change, and to showcase your maker mindset through a hobby project, side build or prototype.
• Agile experience (SCRUM or Kanban) and strong collaboration across cross-functional teams.