We are looking for a Senior GenAI Engineer to lead the end-to-end development, deployment, and operation of enterprise-grade AI-powered applications. This role combines backend engineering, LLM integration, cloud infrastructure, and AI platform operations to deliver scalable GenAI solutions in production environments, working closely with AI/DS, Product, and DevOps teams to build and scale AI-driven applications while ensuring reliability, observability, performance optimization, and operational excellence across the full AI SDLC.
Responsibilities
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Design, develop, deploy, and maintain backend services for AI/LLM-powered applications
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Own E2E delivery of GenAI features from implementation to production support
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Integrate and operate LLM APIs in enterprise production environments
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Develop APIs, orchestration layers, and microservices supporting agentic AI workflows
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Optimize LLM systems for latency, resiliency, retries, fallbacks, and cost efficiency
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Implement CI/CD pipelines, observability, monitoring, and logging for AI services
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Collaborate with AI/DS, Product, DevOps, and platform teams to streamline delivery and improve reliability
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Support MCP integrations, agentic memory initiatives, and AI orchestration frameworks
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Drive GenAI-assisted development practices and scale AI SDLC processes
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Contribute to AI Beauty Chat delivery through agentic micro-pod execution models
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Perform System Steward responsibilities in agentic micro-pods
Requirements
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3+ years of experience in Python backend engineering
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Experience building and operating production-grade GenAI/LLM applications end-to-end
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Hands-on experience with OpenAI or other LLM APIs in production environments
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Skills in prompt engineering, agentic workflows, and orchestration patterns
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Experience handling LLM operational challenges, including latency, retries, fallbacks, observability, and cost optimization
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Understanding of scalable backend and distributed system architecture
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Experience with CI/CD, DevOps workflows, and Azure cloud environments
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Experience applying GenAI across the SDLC, including AI-assisted development, testing, deployment, and delivery workflows
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Working knowledge of SQL/NoSQL databases, Redis, and Kafka
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Familiarity with Databricks and MCP
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Excellent English communication skills (B2+ level)
We offer
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International projects with top brands
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Work with global teams of highly skilled, diverse peers
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Healthcare benefits
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Employee financial programs
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Paid time off and sick leave
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Upskilling, reskilling and certification courses
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Unlimited access to the LinkedIn Learning library and 22,000+ courses
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Global career opportunities
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Volunteer and community involvement opportunities
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EPAM Employee Groups
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Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn
