Senior AI Platform Engineer

About the job Core Responsibilities • Vector Infrastructure: Design and maintain Amazon OpenSearch (k-NN) indices for semantic search • LLM Orchestration: Implement low-latency intent interpretation using Claude. • Agentic Tooling (MCP): Develop Model Context Protocol (MCP) servers to bridge our AI agents with real-time baggage, fare, and seat-map data. • Data Pipelines: Build sliding-window semantic chunking for chat logs and enrichment engines for clickstream-to-text transformation. • Identity Mapping: Integrate identity metadata into vector stores to enable personalized, household-level travel recovery. Technical Requirements • Languages: Expert-level Python (Boto3, LangChain, FastAPI). • AI Stack: Experience with Amazon Bedrock, Vector Databases (OpenSearch/FAISS/Milvus), and RAG (Retrieval-Augmented Generation). • Infrastructure: Deep understanding of AWS Serverless (Lambda, EventBridge, S3). • Protocols: Familiarity with MCP (Model Context Protocol) for building agentic toolsets. • Data Modeling: Experience with JSON-LD, Metadata tagging, and mapping unstructured data to Graph nodes (Amazon Neptune)