Senior AI Engineer (Hybrid)

Required

• Solid grasp of software design principles and ability to design and implement AI-powered components or workflows.
• Experience with at least one GenAI framework (e.g., LangChain, LlamaIndex, Semantic Kernel) and one agentic framework (e.g., PydanticAI, LangGraph, AutoGen2).
• Hands-on experience building and optimizing Retrieval-Augmented Generation (RAG) pipelines with vector databases (e.g., FAISS, Pinecone, Weaviate).
• Familiarity with deploying AI solutions on major cloud platforms (AWS, Azure or GCP), with basic use of containers (Docker) and CI/CD pipelines.
• Experience using LLMOps and observability tools (e.g., Langfuse, PromptLayer, OpenTelemetry) in production.
• Exposure to fine-tuning and use of ML/NLP frameworks such as PyTorch or Hugging Face Transformers.
• Ability to independently solve complex, ambiguous technical problems.
• Willingness and ability to guide and mentor junior engineers, sharing knowledge and best practices.
• Strong collaborative skills, working effectively with diverse, cross-functional teams.
• Thrives in a dynamic and fast-paced environment, demonstrating resilience in the face of challenges.