A day in the life of an AI Engineer

As an AI Engineer in the SRE department of Tech BE, you will help shape and evolve agentic Software Delivery Lifecycle (SDLC) workflows, turning GenAI capabilities into reliable, productionready engineering solutions.

• Developing productionready GenAI and agentic solutions by leveraging GitHub GenAI tools (GitHub Copilot, prompts, agent skills, and instruction files) and working with Pythonbased services on Google Cloud (GCP) using Vertex AI, FastAPI, LangChain, and Google ADK to deliver real business impact.
• Designing intelligent, cloudnative AI workflows and multiagent systems that are reliable, secure, observable, and costefficient in production, integrating GitHubbased CI/CD, workflows, and automation for scalable operation and evolution.
• Collaborating daily with SREs, software engineers, and product partners to translate complex problems into scalable GenAI solutions that improve engineering experience and operational resilience.
• Improving AI agent quality through evaluation, testing, monitoring, and feedback loops, while operating services via CI/CD pipelines, GitHub workflows, and InfrastructureasCode (e.g. Terraform).
• Shaping GenAI engineering standards and best practices across ING, helping teams apply responsible AI to strengthen digital services that support customers and society.

How to succeed

We hire smart people like you for your potential. Our biggest expectation is that youll stay curious. Keep learning. Take on responsibility. In return, well back you to develop into an even more awesome version of yourself.

As an AI Engineer, you will be successful in this role if you can:

• Turn complex and loosely defined problems into clear, stepbystep solutions, knowing when and how GenAI, LLMs, or agentic approaches can meaningfully improve engineering workflows.
• Apply a solid software engineering background (from backend, platform, cloud, data, or similar roles) to design, build, and evolve productionready solutions using GitHub Copilot, Vertex AI, LangChain, Google ADK, Python, FastAPI, RAG, vectorDB, Terraform, docker and cloudnative patterns.
• Deliver reliable, highquality software into production, applying solid engineering principles that may come from backend, platform, data, or cloud roles, with Python, APIs, and cloudnative thinking as common foundations.
• Take ownership of running systems, balancing reliability, security, performance, and cost, and contributing to smooth delivery through modern DevOps practices and GitHubbased workflows.
• Learn and adapt continuously, staying curious and comfortable experimenting with evolving GenAI concepts such as agent orchestration, LLMOps, or AIassisted development tools, even if your experience comes from adjacent technologies.
• Work effectively with others, combining clear communication, collaboration, and technical judgment to turn AIenabled solutions into measurable outcomes that support INGs purpose and positive societal impact.

As an AI Engineer, you will have the opportunity to:

• Grow as an engineer, strengthen your software engineering foundation while developing deep expertise in modern AI and GenAI engineering practices.
• Make a tangible impact across ING Tech Belgium, contributing to shared GenAI platforms, standards, and solutions that are reused across teams and tribes.
• Continuously learn and evolve, gaining handson experience with new AI engineering technologies, tools, and ways of working as ING scales its agentic and GenAI capabilities.

The team

The SRE Belgium Tribe plays a key role in keeping ING Belgiums most important digital services reliable, secure, and scalable, supporting essential sales and servicing journeys used daily by customers. Working closely with engineering teams across the bank, SRE focuses on modern engineering practices that strengthen the stability and quality of INGs technology platforms.

You will join a newly created AI Engineering team within SRE. This team is responsible for building and scaling agentic Generative AI workflows across the Software Development Lifecycle (SDLC). Using GitHubbased technologies, the team develops reusable AI capabilities that help DevOps teams across ING work faster, smarter, and more consistently.

Operating at the intersection of software engineering, reliability, and AI, the teams mission is to scale Generative AI safely, responsibly, and effectively across ING. By providing standardized platforms and tools, such as GitHub Copilot and VISTA (Google Cloud Platform), the team enables engineers to adopt GenAI with confidence.

Would you like to get to know the department better? Book a coffee with the hiring manager, a team member, or the recruiter. In a second phase you could get to know the job content better via a My Job Your Job.