About the company

Our client is an international digital learning organization that is building a new AI Centre of Excellence. The organization is moving from separate AI experiments towards reusable, secure and scalable AI capabilities that can support digital products, content creation, internal workflows and customer-facing solutions.


This is a hands-on role in a team that is still being built. Many AI initiatives have already been identified, but the technical platform, reusable components and standards are still being developed. This makes the role suitable for someone who wants to build real AI solutions and influence how AI is applied across a larger organization.


The role

As AI Software Engineer, you will design, build and operate AI services, platforms and components that product, engineering, data and business teams can use.


This role requires someone who has already delivered AI solutions in a production environment. Experience with experiments, prototypes or personal projects is valuable, but not enough on its own. We are looking for someone who understands how AI products are deployed, maintained and improved inside a company context.


You will work close to product managers, portfolio managers, engineers and business stakeholders. You can clarify business needs, understand business process constraints and translate those needs into concrete AI solutions that engineering teams can build, deploy and operate.


This is not a purely technical execution role. You will also be involved at the front of the process, where ideas, business needs, make or buy decisions and product direction are shaped.


What you will do

1. Translate business and product needs into concrete AI solution designs.
2. Build production-grade AI services, APIs, libraries and reusable components.
3. Develop LLM-powered features where they add value, including RAG, prompt design, system design, tool calling, evaluation and monitoring.
4. Combine LLMs with search, rules, machine learning models, analytics and automation.
5. Integrate AI solutions into existing web products, internal workflows and content creation processes.
6. Work with product owners, product managers, portfolio managers and engineers to move from idea to working solution.
7. Define and implement evaluation, testing and monitoring for AI components.
8. Ensure solutions are reliable, secure, observable, maintainable and cost effective.
9. Contribute to AI platform tooling, CI/CD, infrastructure and engineering standards.
10. Support pragmatic make or buy decisions for AI capabilities and tooling.

Important focus area

One key focus area is content creation. This is a core process for the organization and requires more than generating a first version.


AI solutions in this area need to support feedback loops, quality control, local nuance and collaboration between product, content and engineering teams. You will help create solutions that fit real business processes, not isolated one-off tools.


What you bring

1. Strong software engineering experience, preferably in backend, platform, AI engineering, ML engineering or MLOps.
2. Practical experience with AI solutions that have been deployed in production.
3. Hands-on experience with LLM-based applications, RAG, prompt and system design, tool calling, evaluation and monitoring.
4. Experience building backend services, APIs and integrations.
5. Ability to translate business needs into technical solutions.
6. Experience working with product managers, product owners, portfolio managers and engineering teams.
7. Understanding of reliability, scalability, security, cost, observability and maintainability.
8. Strong communication skills in English.
9. Senior presence in stakeholder conversations.
10. Ability to create structure in an environment where not everything is defined yet.

Technology environment

The environment includes cloud-hosted products and modern software and data stacks. Relevant technologies include Azure, Google AI capabilities, TypeScript, JavaScript, Python, NodeJS, React, REST APIs, GraphQL APIs, Snowflake, dbt, Docker, Kubernetes, Terraform, GitHub and CI/CD.

You do not need to have used every technology listed, but you should be able to work confidently in a modern engineering environment and learn what is needed.

What makes someone successful in this role

You are hands-on, pragmatic and comfortable with ambiguity. You do not force every problem into an AI solution, but choose the right technical approach for the business problem.

You can operate between business stakeholders and engineers. You are able to ask the right questions, challenge assumptions and translate complexity into clear next steps.

You bring enough seniority to work independently, communicate clearly and help accelerate AI adoption across a multicultural organization.

Package

The salary range for this role is up to €90.000,- including benefits, based on a 40-hour workweek. In addition to the salary, the package includes an Individual Choice Budget, profit sharing, a pension plan under the applicable CLA, remote work options and additional employment benefits.