Senior GenAI Engineer

We are searching for a Senior nAI Engineer to become part of our team. This role puts you in charge of the entire development, deployment, and operational journey of enterprise-grade AI-powered applications. It draws together backend engineering, LLM integration, cloud infrastructure, and AI platform operations to bring scalable GenAI solutions into live production settings. You will team up with AI/DS, Product, and DevOps groups to construct and expand AI-driven applications, safeguarding reliability, observability, performance optimization, and operational excellence throughout the entire AI SDLC. This position further includes backing GenAI-assisted development approaches, aiding in the growth of the client's enterprise AI SDLC processes, participating in AI Beauty Chat initiatives via agentic micro-pod delivery models, and handling System Steward obligations across AI platform efforts.
Responsibilities
Craft, build, launch, and support backend services that drive AI/LLM-powered applications
Assume complete responsibility for GenAI feature delivery, starting from initial development all the way to production support
Link and administer LLM APIs, such as OpenAI, inside enterprise production settings
Build out APIs, orchestration layers, and microservices to power agentic AI workflows
Adjust LLM systems to improve latency, resiliency, retry handling, fallback logic, and cost management
Configure CI/CD pipelines along with observability, monitoring, and logging capabilities for AI services
Team up with AI/DS, Product, DevOps, and platform groups to ease delivery and reinforce reliability
Function within Azure cloud settings and distributed systems, spanning Redis, Kafka, and SQL/NoSQL databases
Support MCP integrations, agentic memory efforts, and AI orchestration frameworks
Promote GenAI-assisted development approaches and contribute to scaling the client's AI SDLC processes
Play a role in AI Beauty Chat delivery through agentic micro-pod execution models
Handle System Steward obligations within agentic micro-pods
Requirements
At least 3 years of experience relevant to this role
Primary specialization in AI Engineering with an emphasis on backend systems
Strong background in Python for backend engineering
Proven experience delivering and running production-grade GenAI/LLM applications from end to end
Direct, hands-on work with OpenAI or comparable LLM APIs within production contexts
Proficiency in prompt engineering along with various orchestration techniques
Experience tackling operational issues tied to LLMs, covering latency, retries, fallback strategies, observability, and cost efficiency
Firm grasp of distributed system design and scalable backend architecture
Background in CI/CD practices, DevOps processes, and Azure cloud platforms
Experience weaving GenAI into the SDLC, including AI-assisted coding, testing, deployment, and release workflows
Practical familiarity with SQL/NoSQL databases, Redis, and Kafka
Strong ability to communicate clearly and effectively
Excellent English proficiency (B2 level or higher)
Nice to have
Background working with agentic workflow patterns
Practical exposure to Databricks and MCP
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

Work arrangement
Yes