Looking for experienced AI Engineer with exposure to application backend engineering and DevOps mindset
Todos los candidatos deben asegurarse de leer atentamente la siguiente descripción del puesto y la información antes de enviar su solicitud.
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 xqysrnh 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