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.
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🌟 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