Sr AWS MLOps Engineer for AI team
Start opdracht: zsm
Eind opdracht: een jaar later
ZZP: Nee, ook niet via leverancier
Locatie: Arnhem (woensdag) en hybride
Uren: 32 tot 36 uur

Alliander
Alliander is the operator of the largest energy grid in the Netherlands. Our main task is to manage and expand our network. Alliander also plays a leading role in making the energy transition a reality. Examples include the expansion of our network with solar panels, charging stations for electric transport and heat pumps. To make the energy transition possible, Alliander is digitizing radically. After all, in the next 10 years we need to do more work than in the past 40. We are accelerating the transition to sustainable energy with a data-driven approach.

The Agile Release Train (ART) “Data & Analytics”

The ART Data & Analytics is responsible for delivering a state-of-the-art data landscape: future-proof, flexible, based on high standards and cost-conscious. In addition, we are working towards a situation where data products can be easily produced by data producers, maintained, found and used by data consumers both in our own organization and in the market.

The AI Acceleration Team
The team you will be working in aims to accelerate Alliander in the field of AI. It is a DevOps team with a Product Owner, Scrum Master, Tech Lead and MLOps engineers.

- Our customers are diverse: Mainly data science teams developing internal applications “Digitization teams”, analytics teams and also some business teams. We accelerate them by working on a number of themes:

- A platform that allows teams to run models on AWS (MLOps, for data science teams)
- Insight and control through Al governance tooling
- Increase AI skills of employees through knowledge sharing
- Operations (management, support and continuous improvement on the MLOps tools and services we provide)


The AI Acceleration team is a platform team and as an engineer you do not train models yourself, but support other teams in this. The Team provides a standardized and configured environment with tooling for data analytics, MLOps and access to data.

Your role
The team consists of 5 MLOps engineers of whom most are Medior with regard to the tasks at hand. They are eager to learn new skills. We are looking for a Senior to help coach the team in their personal growth. You take an active role in implementing the platform that lets teams run their models. You are a skilled AWS professional who can help with selection and correct deployment of the required AWS resources, using typescript and CDK for infra-as-code.

You have an affinity for ML/Analytics applications and can therefore relate well to data science teams. You translate customer needs and functional specifications into technical solutions and then develop, test and manage these. In doing so, you use AWS (native) services and know which service is most suitable for which use case. We work in a self-managing team and expect you to develop a vision and influence the (technical) direction of the applications/pipelines and bring our users along with you (demos, documentation and traveler role). 

Who you are
- You like building cloud native AWS solutions.
- You enjoy interacting with our data science users where you actively listen to their needs to translate them into solutions
- Experimenting with new MLOps technology comes naturally to you
- You like to teach other team members and help them reach the next level.
- Affinity with working in an Agile team
- Education level: higher professional education (HBO) or higher.

The experience you bring

Technical Expertise:
- Infrastructure as Code:
Advanced proficiency with AWS CDK using TypeScript to define cloud infrastructure in a programmatic and version-controlled manner
- Serverless Architecture:
Strong experience building and optimizing AWS Lambda functions, configuring API Gateway endpoints, and designing efficient DynamoDB data models
- Automation:
Expert at creating CI/CD pipelines for both application and infrastructure deployment using tools like AWS CodePipeline, GitHub Actions, or GitLab CI
- TypeScript:
Professional-level programming skills for developing applications and infrastructure code


Affinity with:
-Knowledge of security best practices for AWS cloud environments
-Explaining complex technical solutions to non-technical stakeholders
-Building user-friendly self-service platforms
-Team collaboration and knowledge sharing
-Knowledge of containerization technologies (Docker, ECR)

Nice to have:
-Demonstrated ability to design and implement model versioning, experiment tracking, and model registry solutions
- AWS SageMaker:
-Proven track record implementing end-to-end ML workflows using SageMaker, including notebooks, training jobs, model deployment, pipelines, and feature stores
-Experience building automated ML pipelines that handle data preparation, model training, validation, and deployment
-Understanding of ML performance monitoring and implementing feedback loops


The Technical Platforms business unit is leading Alliander's transition to a multilingual organization. Here we use English as a bridge language. Within the AI Acceleration team, the working language is English. Alliander offers English language courses if required.

Your workplace
We generally work 2 days at the office (in Amsterdam and Arnhem) and 3 days at home. At least 4 working days per week.