AI Engineer

You will join a team building next-generation AI-powered products based on Large Language Models. The project focuses on transforming LLM prototypes into scalable, secure, and production-grade systems. The role covers the full AI lifecycle – from architecture and backend development to infrastructure, monitoring, and cost optimisation.

✅ Your responsibilities:

Build and maintain production-grade LLM systems (including RAG, semantic search, embeddings, vector databases). Design and develop APIs and microservices in Python (e.g. FastAPI). Develop and maintain CI/CD pipelines for models (LLMOps/MLOps). Deploy and manage infrastructure in AWS (Lambda, ECS/EKS, S3, API Gateway, CloudWatch). Implement containerisation (Docker) and orchestration (Kubernetes). Monitor model quality (latency, drift, hallucinations, cost efficiency). Collaborate closely with Data Science, ML, Data Engineering and Product teams.

Our requirements:

Strong Python skills with experience building production APIs. Hands-on experience deploying LLM-based systems in production. Practical knowledge of RAG, embeddings, vector databases, and semantic search. Experience with AWS and scalable backend system design. Solid understanding of Docker, Kubernetes and CI/CD. Proven ability to move from PoC to stable production solutions.

Preferred Qualifications:

Experience with multimodal models (text, image, video). Familiarity with LLMOps/MLOps tooling and evaluation frameworks. Experience optimising inference performance and managing AI costs at scale. Background in product-led or data-driven organisations. What we offer:

Opportunity to work on advanced AI systems with real product impact. Strong influence on architecture and technology decisions. Collaboration with an experienced Data & AI team in an international environment. Flexible and remote-friendly working mode Health and wellbeing benefits