Faktion BV

Faktion is seeking a Senior Java Engineer to lead the design and delivery of robust, scalable enterprise backend applications using Java and the Spring ecosystem. The role combines hands-on architecture and development with technical leadership, mentoring, testing, and production operations.

AI Engineer building and deploying production-grade AI solutions across generative AI, classical machine learning, computer vision, and agentic systems. The role combines hands-on engineering, customer collaboration, MLOps, and technical mentorship.

Build practical, scalable AI solutions by translating cutting-edge research into prototypes and production-ready systems. This role combines LLM experimentation, evaluation, agentic workflows, and hands-on engineering for real-world customer applications.

Faktion is seeking a DevOps Engineer to build, automate, secure, and operate scalable Azure-based platforms for applications and ML services. The role combines cloud infrastructure, Kubernetes, observability, disaster recovery, and hands-on production operations.

Lead the engineering strategy and delivery of advanced generative AI, NLP, multi-agent, RAG, and voice AI applications while mentoring an AI engineering team. The role combines hands-on model development, MLOps, scalable deployment, technical leadership, and customer-focused innovation.

Senior Full-Stack Engineer responsible for leading the design, development, and delivery of secure, scalable enterprise applications for AI-focused products. The role combines hands-on TypeScript, React, and Node.js development with technical leadership, architecture, mentoring, and team direction.

Generative AI Engineer developing, integrating, and deploying generative AI solutions such as RAG systems, virtual assistants, and customer-specific AI applications. The role combines model optimization, MLOps, containerized back-end development, and technical guidance for cross-functional teams.

Build and deploy computer vision systems for industrial applications, combining deep learning, production software engineering, and MLOps. You’ll work across the full ML lifecycle, from dataset development and model training to real-time inference and production optimization.