AIEngineer

**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, production‑ready engineering solutions. * **Developing** production‑ready GenAI and agentic solutions by leveraging GitHub GenAI tools (GitHub Copilot, prompts, agent skills, and instruction files) and working with Python‑based services on Google Cloud (GCP) using Vertex AI, FastAPI, LangChain, and Google ADK to deliver real business impact. * **Designing** intelligent, cloud‑native AI workflows and multi‑agent systems that are reliable, secure, observable, and cost‑efficient in production, integrating GitHub‑based 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 Infrastructure‑as‑Code (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 you’ll stay curious. Keep learning. Take on responsibility. In return, we’ll 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, step‑by‑step 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)