Looking for experienced AI Engineer with exposure to application backend engineering and DevOps mindset Maintain and enhance CI/CD pipelines using tools like GitHub Actions, AWS CodePipeline, Jenkins, or ArgoCD. Developed backend architecture for the AI Verification and Az ChatGPT Services using Python, FastAPI Understand, develop and optimise highly scalable classifiers and tools leveraging machine learning, encoders and rule-based models Design and build solution using Domain-Driven-Design (DDD) and Test-Driven-Design (TDD) best standards Design, develop and maintain a LLM-as-a-judge production service for verification of AI content generated from source documents: HuggingFace, Transformers, Spacy, Nltk, BM25 Design, build and maintain a high-load RAG service with an ingestion service, message broker and Perform prompt engineering including different options like Chain-of-Thoughts, Few-shot-learning for different tasks using different LLMs (Open AI, Anthropic, Google, including reasoning models) Provide working knowledge & support to one or more specific AI specialism frameworks (Tensorflow, Keras, PyTorch, BERT…) Provide technical expertise in at least one AI specialism (graph recommendation, deep learning, natural language processing) Requirements: Backend stack: Python, FastAPI, MongoDB, PostgreSQL, message queue, JWT-based authentication AI Stack: Python, LangChain (or PydanticAI), Azure / AWS / Google model AI endpoints DevOps: Azure, Docker, CI/CD, GitHub Actions, Terraform Testing: pytest, DeepEval English C1