SeniorFull TimeEN
At ING, Customer Journey Experts drive end‑to‑end improvements across journeys by combining deep customer empathy, data‑driven decision making, and cross‑functional collaboration. ING’s CJE role emphasizes bridging business and IT to deliver seamless omnichannel journeys and digitized customer experiences. As an AI Customer Journey Expert, you’ll extend this core CJE mission by identifying, designing, and delivering AI‑powered solutions—from generative AI chatbots to intelligent automation—aligned with ING’s responsible AI governance and “first nail it, then scale it” approach.
You will operate within ING’s Agile structure of Squads and Tribes, collaborating with data scientists, engineers, UX, operations, and risk to ensure AI is built safely, responsibly, and close to the customer—consistent with ING’s innovation philosophy.
1. Customer Journey Mapping & Opportunity Discovery
Map and analyze customer journeys end‑to‑end to identify friction, inefficiencies, and automation opportunities—core CJE responsibilities across ING.
Identify where AI (LLMs, NLP, chatbots, predictive models) can materially improve customer experience or operational efficiency.
2. AI Solution
Translate customer problems into clear AI use cases: e.g., enhanced chat & voice interactions, intelligent routing, document automation, journey personalization.
Work with data scientists and IT engineers to design safe, secure, and compliant AI workflows—directly reflecting ING’s emphasis on responsible AI and risk frameworks. Define user stories, acceptance criteria, and model guardrails consistent with Generative AI governance at ING.
Design conversation flows and fallback mechanisms for AI-driven interactions, following ING’s chatbot development learnings.
Communicate value, risks, and limitations of AI solutions to business, tech, and compliance stakeholders.
3. Delivery Within ING’s Agile Structure
Work as part of a Squad, contributing to sprint planning, refinement, and delivery in close collaboration with IT, Data, Operations, and Risk.
Validate AI features through iterative testing, rapid experimentation, and PACE‑style MVPs.
Support controlled rollout of AI solutions, mirroring ING’s approach to safe deployment of generative AI (e.g., testing with 10% of users).
Ensure journey improvements comply with Non‑Financial Risk (NFR), RCSA, IT risk, and regulatory standards—core CJE responsibilities.
4. Monitoring, Optimization & Scaling
Monitor AI performance using ING’s “first nail it, then scale it” principle for model rollout and value realization.
Evaluate customer feedback, operational metrics, and risk indicators to refine and optimize AI solutions.
Who are you?
You speak up and advocate for our interests - even when they conflict with others—and you’re not afraid to initiate difficult but necessary conversations.
You are results-driven and decisive. You take ownership, follow through, and make things happen. Decisiveness is one of your key strengths.
You step up, even outside your comfort zone. You’re not afraid to tackle challenges head-on, demonstrating resilience and a strong sense of responsibility.
You know how to structure projects, you understand where to start and are able to implement changes successfully end to end.
You have an eye for organizational sensitivity, you are able to understand what the different interests are, can relate things to each other and are able to manage them.
Required Skills & Qualifications
Ability to bridge business and IT, translating user needs into technical requirements.
Understanding of LLMs, NLP, machine learning concepts, or automation workflows.
Prior experience with chatbots, GenAI tools (e.g., Microsoft 365 Copilot), or data-driven decision automation preferred—mirroring ING’s internal AI adoption.
Awareness of AI risks, data privacy, and regulatory constraints in banking.
Experience:
3–7 years in customer journey, business analysis, digital product development, or operations.
Experience in banking, financial services, or highly regulated industries is preferred.
Experience with AI transformations or automation initiatives.
Experience collaborating with data scientists, engineers, or risk functions.
