AI ApplydAIAPPLYD

Senior/Lead AI Engineer

EPAM Systems

remote globalPosted Jul 13, 2026
Posting intelligenceActively listedReposted 3×, possible evergreen/ghost posting

Skills

databrickslangchainspringpythonopenaiflaskazurescalajavagooglecloudawsllmgoc#ml

About the role

We are looking for a Senior/Lead AI Engineer to design, build, and scale end-to-end AI applications - including chatbots, agent workflows, and LLM-driven solutions. You will work directly with clients, drive technical decisions, and deliver production-grade AI systems that create real business impact.

Responsibilities

Design and deploy AI/LLM applications at scale (RAG, agentic systems, Q&A platforms)

Architect solutions using agentic frameworks, integrating with vector databases and advanced memory architectures

Build APIs, data pipelines, and enterprise integrations (CRM, ERP, cloud platforms)

Evaluate and refine AI performance using LLM-based evaluation, agent metrics, and A/B testing

Ensure performance, security, observability, and cost-efficiency across deployed solutions

Conduct research, rapid prototyping, and experimentation to validate feasibility and business value

Stay current with emerging AI protocols (MCP, A2A, ACP) and evolving LLM technologies

Requirements

5+ years in AI/ML engineering with production-grade delivery experience

Strong Proficiency in at least one modern programming language and web frameworks (Python, Java, Scala)

Hands-on experience with major LLM platforms, agentic frameworks, and advanced integration patterns (RAG, agent orchestration, tool calling)

Experience with vector databases, semantic/hybrid search, and retrieval/ranking systems

Knowledge of MLOps/AIOps practices, monitoring, and security (including prompt injection prevention)

Strong communication skills - able to translate complex AI concepts for both technical and non-technical audiences

Ability to work independently, lead technical initiatives, and collaborate with cross-functional teams

Technologies

Languages: Python, Java, C#, Go

Web Frameworks: FastAPI, Streamlit, Gradio, Flask, Spring Boot, ASP.NET

LLM Platforms: OpenAI, Anthropic, Amazon Bedrock, Gemini

Agentic Frameworks: LangChain, LangGraph, Semantic Kernel, LlamaIndex, Strands Agents

Vector Databases: Qdrant, FAISS, Chroma, Pinecone, Weaviate

Cloud AI Platforms: Azure OpenAI, Amazon Bedrock, GCP Vertex AI

Enterprise AI: AWS AgentCore, Databricks AgentBricks, Google Agents Space, Azure AI Foundry

On-Premise: vLLM

Protocols: MCP, A2A, ACP

MLOps/AIOps, observability, and security/guardrail tools for AI applications

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