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Solution Architect - WB AI / Data & Analytics @ING Hubs Romania

Solution Architect - WB AI / Data & Analytics @ING Hubs Romania at ING scores 8 out of 100 on AI centrality, which makes it AI Level 1 of 4 (Little AI) on this board. The level measures how much of the work is AI, not seniority.

Bucharest - Dacia OnemidFull time

AI in this role

ragllm-integrationai-agentsml-ops

Discover ING Hubs Romania


ING Hubs Romania offers 130 services in software development, data management, non-financial risk & compliance, audit, and retail operations to 24 ING units worldwide, with the help of over 2000 high-performing engineers, risk, and operations professionals. 


We started out in 2015 as ING’s software development hub, then steadily expanded our range to include more services and competencies. Now we provide borderless services with bank-wide capabilities and operate from Bucharest.


Our tech capabilities remain the core of our business, with more than 1800 colleagues active in Data and Analytics Tech, Tech Foundation and Channels, Retail Core Banking and Architecture, and Global Products and Technology Services. 


We enjoy a flexible way of working and a highly collaborative environment, where fair and constructive feedback is encouraged.  


For us, impact isn't a perk. It's the driver of our work. We are guided and rewarded by a shared desire to make the world a better place, one innovative solution at a time. Our colleagues make it their job to do impactful things and they love doing it in good company. Do you?  


Here’s a sneak peak of what our colleagues say about working within ING Hubs Romania:

  • At ING, we're building the solutions of tomorrow, today | 80% of our colleagues in Romania agree

 

The Mission


ING Wholesale Banking is looking for a Solution architect to support the Centre of Excellence (CoE) Gen AI. At ING we aim to unleash the value of our data to the business and our clients, while staying safe and compliant. To do so ING WB leverages bank wide platforms to create advanced analytic capabilities. The CoE GenAI supports teams from WB in their discovery and proof of concepts.


Your day to day


You will be joining an experienced team of 40 Enterprise, Domain, and Solution Architects that work closely together with business and technology colleagues. The role is primarily based in Bucharest and is part of a global organisation. As the solution architect for the GenAI CoE, you will work with the selected initiatives across the Wholesale Bank.


What you’ll bring to the team


As Solution Architect in the GenAI CoE you:

  • Create the solution architecture and technical designs for new initiatives. Preferably with experience in the area of GenAI solutions, including LLM integration patterns, RAG architectures, agentic workflows, prompt orchestration, model selection and AI platform capabilities.
  • Guide and support the development squads during the discovery and subsequent productization of the initiatives.
  • Identify potential synergies and shared components across the initiatives.
  • Promote the technical standards and guidelines for the area
  • Review deliverables of the squads to ensure conformance with the technical standards and guidelines
  • Develop and maintain relevant architectural artifacts, including (technical) application architectures, architecture decisions, roadmaps, data models, and other relevant documentation
  • Make sure our applications are reliable, available, secure and resilient
  • Align with stakeholders across multiple departments and locations (EU / Asia and US)


We hire smart people like you for your potential. Our biggest expectation is that you’ll stay curious and take on responsibility. In return, we’ll back you to develop into an even more awesome version of yourself. Ideally you recognize yourself in most of the below points:

  • A master’s degree in Computer Science, Information Systems, Business Administration, or related field/equivalent work experience. 
  • You have at least 3 years of experience as an IT architect or extensive IT experience as a (lead) engineer within the AI domain.
  • Proven track record of design and development of production grade GenAI solutions in a corporate environment on one of the major cloud ecosystems using capabilities like vector databases, LLMs and RAG.
  • You are proficient in modelling and modelling languages (UML, Archimate)
  • Ideally you have experience within a Wholesale Banking environment and are familiar with the products and processes used to support corporate clients in a highly regulated environment.
  • A deep understanding of Gen AI solutions, including their (technical or ethical) limitations and strengths. Preferably experience designing production-grade GenAI solutions using technologies such as LLMs, RAG, vector databases, semantic search, agentic frameworks.
  • Curious mindset: you stay up to date with the architecture trends, data market developments, and IT technology. Ideally you are up to date with the latest developments in the (gen) AI space. Understanding of MLOps and LLM Ops principles including deployment, monitoring, model lifecycle management, CI/CD integration.
  • Excellent communication skills & team player, capable of conveying complex architecture topics to various audiences
  • Ability to develop strong and collaborative partnerships with organizational leaders from business and technology. 
  • Knowledge of and experience with IT architecture methodologies, processes (e.g., TOGAF), service management processes and an agile way of working.

If you want to deep dive into the processing of personal data conducted by ING Hubs Romania during the recruitment process and your rights related to it, read the privacy notices on our website (make sure to scroll until you reach the Data Protection section/ Candidates tab). 

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RagLlm IntegrationAI AgentsMl Ops

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How have you integrated a large language model into a production application?
  3. How do you decide when an AI agent can act on its own versus asking for approval first?
  4. How do you monitor a model once it's live, and how do you know it needs retraining?

Adapt your resume

  • List these exact terms on your resume: Rag, Llm Integration, AI Agents, and Ml Ops. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.

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