EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential. We are building scalable, production-ready GenAI services and need a Senior GenAI Engineer to drive backend delivery, LLM integration, and platform operations. You will partner with AI/DS, Product, and DevOps to ship reliable AI applications with strong observability, performance, and cost controls across the AI SDLC—apply now. Responsibilities Design and build backend services for AI/LLM-powered applications, then run and evolve them in production Own end-to-end delivery of GenAI features from implementation through release and ongoing production support Integrate and operate LLM APIs (e.g. OpenAI) in enterprise-grade production environments Develop APIs, orchestration layers, and microservices that enable agentic AI workflows Optimize LLM systems for latency, resiliency, retries, fallbacks, and cost efficiency Implement CI/CD pipelines plus observability, monitoring, and logging for AI services Collaborate with AI/DS, Product, DevOps, and platform teams to streamline delivery and raise reliability Work within Azure cloud environments and distributed systems using Redis, Kafka, and SQL/NoSQL Support MCP integrations, agentic memory initiatives, and AI orchestration frameworks Drive GenAI-assisted development practices and help scale enterprise AI SDLC processes Contribute to AI Beauty Chat delivery via agentic micro-pod execution models Execute System Steward responsibilities within agentic micro-pods Requirements 3+ years of Python backend engineering experience Proven expertise building and operating production-grade GenAI/LLM applications end-to-end Hands-on experience running OpenAI or other LLM APIs in production environments Deep proficiency in prompt engineering, agentic workflows, and orchestration patterns Demonstrated ability to manage LLM operational challenges such as latency, retries, fallbacks, observability, and cost optimization Solid understanding of scalable backend architecture and distributed system design Hands-on skills in CI/CD, DevOps workflows, and Azure cloud environments Background applying GenAI across the SDLC, including AI-assisted development, testing, deployment, and delivery workflows Working knowledge of SQL/NoSQL databases, Redis, and Kafka Familiarity with Databricks and MCP We offer International projects with top brands Work with global teams of highly skilled, diverse peers Employee financial programs Paid time off and sick leave Upskilling, reskilling and certification courses Unlimited access to the LinkedIn Learning library and 22,000+ courses Global career opportunities Volunteer and community involvement opportunities EPAM Employee Groups Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn #J-18808-Ljbffr