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