AI Engineer at Riverflex

Riverflex is building intelligent solutions that blend modern software engineering with state-of-the-art language models and machine learning techniques, designing and deploying scalable AI systems that power next-generation digital products for clients (including IKEA) and internal tools.

As a hands-on lead engineer, you will build scalable AI and GenAI systems using transformer-based models (GPT, Claude, Mistral) and RAG architectures. You will design and implement ML/AI pipelines including model training, evaluation, prompt chaining, embedding retrieval, and context management. You will engineer Python code for AI agents and APIs, apply MLOps practices (MLflow, AzureML, Kubeflow, Docker, Kubernetes), and mentor teammates on AI engineering and responsible AI design.

You will use orchestration tools like LangChain, Semantic Kernel, and n8n to implement agent workflows, work with vector databases (Pinecone, FAISS, Weaviate), and apply MCP (Model Context Protocol) patterns. The role emphasizes production deployment and responsible AI design rather than research.

Requirements:

7+ years software or ML engineering experience, including 2+ years on GenAI/LLM-based products.

Orchestration and agentic frameworks (LangChain, Semantic Kernel, GPT agents).

Hands-on experience with embeddings, vector search, and RAG.

CI/CD environments with MLOps tooling.

Deep understanding of API design, microservices, and distributed systems.