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