We are seeking a GenAI Engineer to lead the end-to-end development, deployment and operation of enterprise-grade AI-powered applications. The role combines backend engineering, LLM integration, cloud infrastructure and AI platform operations to deliver scalable GenAI solutions in production environments. You will work closely with AI/DS, Product and DevOps teams to build and scale AI-driven applications, ensuring reliability, observability, performance optimization and operational excellence across the full AI SDLC. The role also includes contributing to GenAI-assisted development practices, scaling enterprise AI SDLC processes, supporting AI Beauty Chat initiatives through agentic micro-pod delivery models and performing System Steward responsibilities across AI platform initiatives.

Responsibilities

• Design, develop, deploy and maintain backend services for AI/LLM-powered applications
• Own E2E delivery of GenAI features from implementation to production support
• Integration and operation of LLM APIs (e.g. OpenAI) in enterprise production environments
• Development of APIs, orchestration layers and microservices supporting agentic AI workflows
• Optimization of LLM systems for latency, resiliency, retries, fallbacks and cost efficiency
• Implementation of CI/CD pipelines, observability, monitoring and logging for AI services
• Collaboration with AI/DS, Product, DevOps and platform teams to streamline delivery and improve reliability
• Work with Azure cloud environments and distributed systems (Redis, Kafka, SQL/NoSQL)
• Support for MCP integrations, agentic memory initiatives and AI orchestration frameworks
• Drive GenAI-assisted development practices and scale AI SDLC processes
• Contribution to AI Beauty Chat delivery through agentic micro-pod execution models
• Execution of System Steward responsibilities in agentic micro-pods

Requirements

• 2+ years of Python backend engineering experience
• Expertise in building and operating production-grade GenAI/LLM applications end-to-end
• Hands-on experience with OpenAI or other LLM APIs in production
• Proficiency in prompt engineering, agentic workflows and orchestration patterns
• Capability to handle LLM operational challenges: latency, retries, fallbacks, observability and cost optimization
• Strong understanding of scalable backend and distributed system architecture
• Skills in CI/CD, DevOps workflows and Azure cloud environments
• Background in applying GenAI across the SDLC (AI-assisted development, testing, deployment and delivery workflows)
• Working knowledge of SQL/NoSQL databases, Redis and Kafka
• Familiarity with Databricks and MCP
• Excellent English communication skills (B2+ level)

We offer

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• 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