AI Engineer (Backend)

We are looking for an AI Engineer (Backend) to join our organization. In this role, you will be responsible for building, deploying, and supporting robust AI\-driven backend systems, with a strong emphasis on integrating OpenAI APIs into live environments. You will work alongside data science, DevOps, and cloud specialists to automate deployment, monitor system health, and optimize AI\-powered processes. **Responsibilities** * Design and improve backend infrastructure for AI and LLM\-based applications * Deploy, scale, and oversee LLM\-powered solutions in cloud platforms * Create and maintain CI/CD pipelines to streamline deployment activities * Oversee the performance and reliability of AI services, making necessary adjustments * Establish observability and logging frameworks to monitor LLM API usage and performance * Work in partnership with DevOps and data science teams to enhance workflow efficiency and system dependability * Leverage cloud services, with a focus on Azure, for hosting and expanding AI solutions * Develop APIs and microservices to deliver AI functionalities **Requirements** * At least 2 years of experience as a backend AI Engineer * Strong proficiency in Python backend development, particularly using FastAPI * Background in integrating and managing LLM APIs (such as OpenAI) in production settings * Understanding of prompt engineering and orchestration strategies for LLMs * Skills in mitigating LLM challenges, such as latency, cost efficiency, retries, and fallback mechanisms * Experience architecting scalable backend systems for LLM\-based APIs * Working knowledge of SQL and NoSQL databases, including Redis and Kafka * Practical experience with Databricks for data engineering and analytics * Acquainted with Model Context Protocol (MCP) for model management and integration * English language proficiency at B2\+ level or higher, both written and spoken **Nice to have** * Exposure to agentic workflows for advanced AI process automation * Knowledge of Model Context Protocol to support model interoperability