Looking for experienced AI Engineer with exposure to application backend engineering and Dev Ops mindset
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Maintain and enhance CI/CD pipelines using tools like Git Hub Actions, AWS Code Pipeline, Jenkins, or Argo CD.Developed backend architecture for the AI Verification and Az Chat GPT Services using Python, Fast APIUnderstand, develop and optimise highly scalable classifiers and tools leveraging machine learning, encoders and rule-based modelsDesign and build solution using Domain-Driven-Design (DDD) and Test-Driven-Design (TDD) best standardsDesign, develop and maintain a LLM-as-a-judge production service for verification of AI content generated from source documents: Hugging Face, Transformers, Spacy, Nltk, BM25Design, build and maintain a high-load RAG service with an ingestion service, message broker andPerform 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, Py Torch, BERT...)Provide technical expertise in xpzdshu at least one AI specialism (graph recommendation, deep learning, natural language processing) Requirements:
Backend stack: Python, Fast API, Mongo DB, Postgre SQL, message queue, JWT-based authenticationAI Stack: Python, Lang Chain (or Pydantic AI), Azure / AWS / Google model AI endpointsDev Ops: Azure, Docker, CI/CD, Git Hub Actions, TerraformTesting: pytest, Deep EvalEnglish C1