Are you a visionary technologist ready to transform experimental AI models into scalable, enterprise-grade applications? We are partnering with a premier technology solutions provider seeking a Senior AI Engineer to lead the architecture and deployment of cutting-edge, cloud-based commercial AI products. In this pivotal role, you will bridge the gap between data science prototypes and production software, ensuring that complex AI solutions ar[ "What you'll be doing in this role:Lead the implementation of rigorous evaluation frameworks to monitor model performance, drift, and cost in real-time. Architect and develop high-performance backend services and APIs using Python (Fast. API) to serve large language models at scale. Design advanced Retrieval-Augmented Generation (RAG) systems, selecting and managing vector databases and optimizing embedding strategies for accuracy and speed. Establish comprehensive model observability and guardrail systems to monitor real-time performance, detect distribution drift, and implement automated safety filters that mitigate hallucinations, bias, and toxic outputs in production environments. Build robust integration layers that connect AI agents securely to external enterprise systems, CRMs, and legacy databases. Conduct code reviews, provide technical guidance, and foster a culture of continuous learning and innovation within the engineering team. Collaborate with infrastructure teams to define deployment strategies, ensuring solutions scale dynamically under load. Define the end-to-end architecture for AI products on cloud platforms (preferably Google Cloud Platform), ensuring high availability, security, and cost-effectiveness." ][ "6 years of professional software engineering experience, with at least 3 years explicitly dedicated to AI and Machine Learning application development.\r\n\r\n. Expert-level proficiency in Python application development and modern API architecture (REST, Graph. QL, g. RPC) utilizing enterprise standards like static type checking.\r\n\r\n. Extensive hands-on experience building production-grade applications using modern LLM frameworks (such as Lang. Chain, Lang. Graph, or Llama. Index).\r\n\r\n. Deep understanding of vector databases (e.g., Pinecone, Weaviate, Postgre. SQL) and advanced search algorithms.\r\n\r\n. Strong command of LLM - Ops principles, including model registry, versioning, and serving infrastructure within a cloud environment (specifically Google Cloud).\r\n\r\n. Familiarity with Type. Script for rapid prototyping and building robust integration layers.\r\n\r\n. Solid understanding of standard application development lifecycles and Git workflows." ]