Senior AI Developer with LLM Orchestration, Intelligent Knowledge Platform

Project overview This project focuses on building a next generation enterprise knowledge platform powered by large language models, semantic search, and graph technologies. The solution converts expert content into structured knowledge and enables advanced reasoning through agent driven workflows. Team You will collaborate within a cross functional team of AI engineers, backend developers, data engineers, and product specialists. The team operates in an agile environment with close collaboration, knowledge sharing, and iterative delivery practices. Position overview We are looking for an experienced AI Engineer to design and deliver advanced LLM powered solutions that transform unstructured information into scalable, searchable knowledge systems. You will work on building high quality retrieval and generation pipelines, enabling intelligent applications with strong evaluation, observability, and performance optimization practices. Technology stack Python, LangChain or similar orchestration frameworks, vector databases, embedding models, Google Cloud Spanner Graph, Gemini Enterprise Agent Platform, REST APIs, Docker, Kubernetes, ML evaluation frameworks, observability and tracing tools Responsibilities Develop and maintain end to end LLM orchestration and retrieval pipelines Design and implement embedding generation and chunking strategies with effective context window management Optimize retrieval quality through tuning techniques and evaluation driven improvements Build entity extraction pipelines that transform unstructured content into graph structures using entity resolution and relationship normalization Implement semantic search solutions and prompt engineering patterns Develop agentic workflows to support complex reasoning tasks Integrate graph databases with LLM based platforms and services Create and maintain evaluation frameworks including ground truth datasets and regression testing processes Measure and improve system performance using metrics such as recall, precision at K, answer relevance, and faithfulness Improve observability, tracing, and cost efficiency across LLM pipelines Collaborate with team members to design scalable and reliable systems Requirements Experience developing applications with large language models and retrieval augmented generation Strong proficiency in Python and backend development practices Hands on experience with vector databases and semantic search implementations Understanding of embedding techniques, chunking strategies, and context management Experience building or maintaining data pipelines for unstructured content processing Familiarity with graph data modeling and knowledge graph concepts Experience implementing evaluation methodologies for AI systems including precision and recall metrics Experience working with cloud platforms and containerized environments such as Docker and Kubernetes Ability to design scalable and maintainable system architectures Strong collaboration and communication skills Nice to have Experience with Google Cloud services including Spanner Graph Familiarity with Gemini Enterprise Agent Platform or similar tools Experience with LangChain, LlamaIndex, or similar frameworks Knowledge of entity resolution and graph based reasoning techniques Experience with observability tools for ML or AI systems Understanding of cost optimization strategies for LLM usage