AI Engineer

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 from early concept to production by leveraging GitHub-based engineering tools, including GitHub Copilot, prompts, agent skills, and instruction files, and building Python-based services on Google Cloud using Vertex AI, FastAPI, LangChain, and Google ADK to deliver measurable engineering impact.
• Designing intelligent, cloud-native AI workflows and distributed multi-agent systems that are reliable, secure, observable, scalable, and cost‑efficient in production, integrating GitHub-based CI/CD workflows and automation for sustainable operation and evolution.
• Collaborating daily with SREs, software engineers, product partners, and subject‑matter experts 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 through CI/CD pipelines, GitHub workflows, and Infrastructure as Code, such as Terraform.
• Shaping GenAI engineering standards and best practices across ING, helping teams apply responsible AI to strengthen digital services that support customers and society.

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 from early concept to production by leveraging GitHub-based engineering tools, including GitHub Copilot, prompts, agent skills, and instruction files, and building Python-based services on Google Cloud using Vertex AI, FastAPI, LangChain, and Google ADK to deliver measurable engineering impact.
• Designing intelligent, cloud-native AI workflows and distributed multi-agent systems that are reliable, secure, observable, scalable, and cost‑efficient in production, integrating GitHub-based CI/CD workflows and automation for sustainable operation and evolution.
• Collaborating daily with SREs, software engineers, product partners, and subject‑matter experts 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 through CI/CD pipelines, GitHub workflows, and Infrastructure as Code, such as 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 to design, build, document, test, review, and evolve production‑ready solutions. Python, GitHub‑based version control, RAG, vector databases, Docker, Terraform, and cloud-native patterns are common foundations; GitHub Copilot, Vertex AI, FastAPI, LangChain, and Google ADK are technologies used by the team.
• Design and deliver reliable, scalable APIs and asynchronous services, using appropriate interface patterns such as REST or gRPC, and take them into production with robust testing, documentation, code review, and CI/CD practices.
• Take ownership of running systems, balancing reliability, security, performance, and cost, and contributing to smooth delivery through modern DevOps practices and GitHub‑based workflows.
• Learn and adapt continuously, staying curious and comfortable experimenting with evolving GenAI concepts such as agent orchestration, LLMOps, or AI‑assisted development tools, even if your experience comes from adjacent technologies.
• Work effectively with others, combining clear communication, collaboration, and technical judgment to turn AI‑enabled solutions into measurable outcomes that support ING’s purpose and positive societal impact.

Nice to have

• Experience with Kubernetes, OpenShift, or equivalent container orchestration p