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# AI Engineer

- **Company:** Faktion Bv
- **Location:** Belgium
- **Experience:** Starter
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Computer Vision, Microsoft Azure, Cloud Computing, Software Quality, Code Review, Continuous Integration, Data Cleansing, Github, Python (Programming Language), Machine Learning, Object Detection, OpenCV, Pair Programming, Tensorflow, Cloud Platform System, Pytorch, LangChain, Evaluation Pipelines, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Deep Learning, Kaggle, Reliability of Systems, Generative AI, Fastapi, Containerization, Infrastructure Automation Frameworks, Information Technology, Performance Monitor, Free and Open-Source Software, Build Tools, Machine Learning Operations, Feature Extraction, Terraform, Docker, Data Generation
- **Published:** October 30, 2026
- **Apply:** https://startup.jobs/junior-ai-engineer-faktion-bv-8387727

## About the Role

* You have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Master degree is a plus.
 * You have a strong curiosity about new technologies and you are a fast learner.
 * You are proficient in Python and have experience with relevant frameworks such as PyTorch, TensorFlow, OpenCV, LangChain, or LangGraph.
 * You are comfortable working across the AI stack, from prompt engineering and RAG architecture to model training, evaluation pipelines, and cloud deployment.
 * You are familiar with cloud-based platforms and services, such as Azure.
 * You have experience with containerisation tools such as Docker and API development frameworks such as FastAPI.
 * You possess strong problem-solving skills and can think critically and creatively to develop innovative AI solutions.
 * You have strong communication skills and can effectively convey complex technical concepts to a diverse audience.
 * You possess a proactive mindset and can work independently and collaboratively in a fast-paced, dynamic environment.
 * Excellent communication skills in English (Dutch is a strong plus).

Following experiences are a plus:

 * You have solid hands-on experience building and deploying AI systems, whether GenAI, classical ML, computer vision, or a combination.

 * Showing your passion through GitHub repos, open-source contributions, or prior engagements in Kaggle competitions.
 * Experience with computer vision techniques such as synthetic data generation, object detection, or image segmentation.
 * Experience with MLOps tooling, including CI/CD pipelines, Azure DevOps, GitHub Actions, or infrastructure-as-code tools like Terraform.
 * Exposure to agentic frameworks and multi-agent system design.
 * Publications in relevant AI/ML conferences and journals.
 * Experience in one of our focus domains: Data Quality, Retail, Manufacturing, Finance.

## Description

* End-to-End AI Engineering: Design and implement end-to-end AI solutions spanning GenAI, classical ML, computer vision, and agentic systems tailored to enterprise customers, working alongside senior architects.
 * Architecture & Scoping: Work with senior engineers and product managers to translate client problems into concrete technical architectures and clear technical requirements.
 * Production Backends: Develop and deploy production-ready AI backends using Python, FastAPI, and Docker, focusing on scalability, code quality, and system reliability.
 * Evaluation Pipelines: Build and maintain continuous evaluation frameworks (including LLM-as-a-Judge agents) to track model quality from development to production.
 * MLOps & Pipeline Maintenance: Build and maintain reliable MLOps workflows covering data preprocessing, feature extraction, model training, and performance monitoring.
 * Continuous Learning & Research: Research emerging advancements in Generative AI, machine learning, computer vision, and deep learning, identifying practical applications for client projects.
 * Cross-Functional Collaboration: Collaborate closely with software engineers, designers, and business stakeholders to ensure technical implementations match customer goals.
 * Technical Documentation: Author clear technical documentation, architectural notes, and presentations to explain complex AI concepts to both technical and non-technical stakeholders.
 * Mentorship & Professional Growth: Actively participate in structured 1-on-1 mentorship, code reviews, and pair programming sessions with senior team members to continually elevate your engineering practices.