ING's WBAA Discovery team is seeking a Senior Data Engineer / ML Engineer to explore and validate AI opportunities within Wholesale Banking. You will work end-to-end from problem framing with stakeholders to building rapid proofs-of-concept and handing over to build teams. The role requires strong Python and AI integration skills, including LLMs and RAG, combined with data engineering and cloud deployment expertise.
Responsibilities
Turn ambiguous business questions into feasible analytics solutions through end-to-end work: problem framing, data exploration, feasibility assessment, rapid prototyping, and clear recommendations.
Collaborate with stakeholders to define, validate, and prioritize AI opportunities, ensuring alignment with business impact, re-use, scalability, and strategic fit.
Build rapid proofs-of-concept and prototypes, then prepare handover packages for build teams, ensuring compliance with banking standards.
Manage stakeholder expectations and communicate complex topics to both technical and non-technical audiences.
Requirements
Strong Python programming proficiency.
Demonstrated expertise in AI integration, including working with large language models (LLMs) such as Gemini and Claude, implementing RAG patterns, designing and evaluating prompts, and utilizing vector databases.
Ability to explore data quickly and assess feasibility (data availability/quality, constraints, expected business impact).
ING Bank is a global financial institution offering retail and wholesale banking services. Its offerings include savings, payments, investments, loans, and specialized corporate finance solutions.
Data engineering skills: building scalable data pipelines and optimizing data processing (e.g., Spark, Airflow, partitioning, incremental loads, performance tuning).
Experience building rapid prototypes/PoCs and translating outcomes into clear recommendations.
Experience designing and deploying cloud solutions, including CI/CD, containerization (e.g., Docker) and infrastructure-as-code (e.g., Terraform).
Experience with APIs and service-based architectures (microservices, REST/gRPC, async programming).
Strong stakeholder management and communication skills.
Comfortable with rapidly changing priorities and ambiguity.
Nice to Have
ML model training, validation, and experiment tracking experience.
GCP expertise.
Familiarity with discovery process or design sprints; strong story-telling and visualization skills.
Experience with Kubernetes and container platforms (e.g., OpenShift).
Experience building and maintaining high-load APIs and OpenAPI integration/governance.
Basic networking knowledge and familiarity with event-driven architecture.
Experience working in regulated environments.
Familiarity with agentic frameworks (ADK, LangChain, LangGraph, CrewAI) and multi-agent design patterns.
Basic understanding of Java/Kotlin for connectivity to ING internal systems.