We are on the lookout for a Lead GenAI Engineer to join our team. In this role, you will oversee the full development, deployment, and operational cycle of enterprise-grade AI-powered applications. The position merges backend engineering, LLM integration, cloud infrastructure, and AI platform operations to deliver scalable GenAI solutions in live production environments. You will collaborate closely with AI/DS, Product, and DevOps teams to build and grow AI-driven applications, upholding reliability, observability, performance optimization, and operational excellence across the complete AI SDLC. The role also involves supporting GenAI-assisted development practices, helping expand the client's enterprise AI SDLC processes, contributing to AI Beauty Chat initiatives through agentic micro-pod delivery models, and carrying out System Steward duties across AI platform initiatives. Responsibilities Design, construct, deploy, and maintain backend services that power AI/LLM-driven applications Hold full accountability for GenAI feature delivery, from initial build through to production support Connect and manage LLM APIs, including OpenAI, within enterprise production environments Develop APIs, orchestration layers, and microservices that enable agentic AI workflows Tune LLM systems for latency, resiliency, retries, fallbacks, and cost efficiency Set up CI/CD pipelines, observability, monitoring, and logging for AI services Work alongside AI/DS, Product, DevOps, and platform teams to simplify delivery and boost reliability Operate within Azure cloud environments alongside distributed systems, including Redis, Kafka, and SQL/NoSQL databases Facilitate MCP integrations, agentic memory initiatives, and AI orchestration frameworks Advocate for GenAI-assisted development practices and support scaling of the client's AI SDLC processes Assist with AI Beauty Chat delivery through agentic micro-pod execution models Carry out System Steward duties within agentic micro-pods Requirements A minimum of 5 years of experience in a relevant field At least one year of experience in a team leadership or management capacity Main area of specialization in AI Engineering, with an emphasis on backend systems Well-developed background in Python backend development Track record of building and running enterprise-grade GenAI/LLM applications from start to finish Direct experience working with OpenAI or other LLM APIs in live production settings Competence in prompt engineering and various orchestration approaches Experience tackling operational hurdles tied to LLMs, including latency, retry logic, fallback handling, observability, and cost control Deep familiarity with distributed systems and scalable backend architecture Background in CI/CD practices, DevOps tooling, and Azure-based cloud environments Experience embedding GenAI into the software development lifecycle, spanning AI-assisted coding, testing, deployment, and release processes Practical knowledge of SQL/NoSQL databases, along with Redis and Kafka Strong ability to communicate effectively with varied audiences Excellent English proficiency (B2 level or higher) Nice to have Exposure to agentic workflow design Hands-on background with Databricks and MCP
