AI & Data Engineer

Are you the AI & Data Engineer who wants to join our team to develop innovative data pipelines and state-of-the-art AI solutions?

As an AI & Data Engineer at iO, you are first and foremost an experienced software engineer who builds, integrates, and operationalizes AI and data solutions within clients’ existing IT ecosystems.

You will work on a wide variety of AI challenges: from intelligently leveraging or fine-tuning Large Language Models, agent and multi-agent setups, and applying RAG patterns, to building ETL pipelines that feed a data platform. A recurring pattern in your work is integrating existing cloud services and APIs into an efficient, scalable, and reliable solution. The focus lies on building production-grade systems that function correctly within complex, often enterprise-level IT landscapes.

Prompt engineering is an art form to you. You think creatively about how to achieve the best results, while paying attention to preventing hallucinations and implementing smart guardrails. You evaluate your solutions systematically to gain insight into output quality.

In your work, you will encounter many forms of AI: from statistical models to Large Language Models, from Generative AI in the domains of image, video, and audio to Natural Language Processing. The emphasis is mainly on applying and integrating existing models and services, and building the infrastructure around them.

You will work on a wide range of client challenges: from automatically analyzing documents to detecting events in audio or video data, building agents and orchestration solutions, generating graphical output based on data, or creating and validating content. Wherever AI can add value, you design and implement the complete solution as an engineer.

You collaborate with various AI experts within iO and with technical teams on the client side. Your solutions are based on modern (cloud) platforms, SaaS services, and programming languages such as TypeScript and Python.

What Are Your Responsibilities as an AI & Data Engineer?

• Designing AI & Data solutions: Analyze client challenges related to AI and data and define solutions, approaches, and architecture

• Software engineering & integration: Develop backend components, APIs, and services to ensure AI solutions integrate seamlessly with existing applications and platforms

• Data Pipeline Development: Design and build robust ETL/ELT processes and real-time data streams

• Data Platform Architecture: Set up modern data warehouses, data lakes, and analytics platforms

• AI Integration: Implement machine learning pipelines and integrate AI services into data workflows

• Data Quality & Governance: Ensure data quality, security, and compliance within data ecosystems

• Performance Optimization: Optimize data processing performance and scalability

• Cloud Data Services: Work with cloud-native data services such as AWS Glue, Azure Data Factory, or Google Dataflow

• Monitoring & Observability: Implement monitoring and alerting for data pipelines and AI workloads

• You hold a Bachelor’s or Master’s degree with a focus on software engineering

• You have several years of experience as a software engineer and have worked on data- and/or AI-driven systems in a professional, preferably enterprise, environment

• You have experience with different LLM architectures and understand the strengths and weaknesses of various AI solutions

• You are familiar with the principles of modern data architectures, data modeling, and big data processing

• You are proficient in modern data processing languages such as Python and SQL, and have experience with frameworks such as Apache Spark, Pandas, or Dask

• You are familiar with AWS or Azure cloud data platforms

• You have a strong foundation in software engineering, including knowledge of CI/CD, unit testing, Git (flow), secure development, error handling, asynchronous operations, and real-time data streams

• You are able to translate your ideas into technical architecture diagrams, data flow schemas, and documentation, while also clearly explaining your solutions to less technical stakeholders (clients and colleagues)

• You enjoy sparring with colleagues about ideas and solutions and working collaboratively to achieve better results