Senior AI Engineer

EPAM Systems, Inc.
Atlanta, GA, United States
2 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

LangGraph Framework Artificial Intelligence Amazon Web Services Automated Storage and Retrieval Systems Microsoft Azure Code Review Computer Programming Cursor Monitoring of Systems Python (Programming Language) Machine Learning Natural Language Processing
+26 more
Open Source Technology Systems Development Life Cycle OpenAI Cloud Services Search Technologies Systems Architecture Tokenization TypeScript Web Application Frameworks Scripting Chatbots GitHub Copilot Retrieval-Augmented Generation Large Language Models Llamaindex Generative AI Agentic-AI Fastapi LangSmith Arize Phoenix Machine Learning Operations Model Context Protocol Streamlit Framework Document Classification Data Pipelines Databricks

Job description

We are looking for a skilled, innovation-driven Senior AI Engineer to join our team and spearhead the development of cutting-edge Generative AI solutions.

If youre passionate about artificial intelligence and adept at building systems that deliver measurable business impact, this opportunity is ideal for you. You will work with a dynamic group of professionals to create and deploy AI-driven technologies that tackle real-world challenges - all within a highly collaborative, supportive, and forward-focused environment.

As a senior member of our team, you wont just write code; you will architect intelligent systems, consult directly with clients, mentor hungry talent, and turn the latest AI research into production-grade reality.

If you love Python, Natural Language Processing (NLP), and staying on the cutting edge of Generative AI, we want to hear from you!

Responsibilities

  • Architect and implement scalable AI applications, including chatbots, search platforms, and autonomous agent workflows
  • Collaborate directly with business stakeholders to understand their challenges and recommend smart, LLM-driven solutions
  • Create data pipelines, design smart prompt strategies, and build testing frameworks to ensure our AI models are safe, accurate, and cost-effective
  • Establish coding standards, perform code reviews, and mentor junior developers in AI best practices
  • Run quick experiments, build prototypes to test new models, and stay current with emerging AI research and tools

Requirements

Artificial Intelligence (AI), Artificial Intelligence (AI), Building Systems, Team Player, Mentoring, Consulting, Computer Programming, System Architecture, Python Programming/Scripting Language, Natural Language Processing (NLP), * 3+ years of experience as a Senior Software Engineer delivering production-grade AI, Machine Learning, or LLM-based solutions

  • Strong proficiency in Python (especially web frameworks like FastAPI) and a solid grasp of NLP concepts (semantic similarity, tokenization, text classification)
  • Hands-on experience with modern AI patterns, particularly RAG (Retrieval-Augmented Generation) and AI Agents
  • Familiarity with major LLM APIs (OpenAI, Anthropic, Bedrock) and framework tools (like LangGraph or LlamaIndex)
  • Experience deploying AI applications at scale, managing cloud costs, and evaluating model quality (using retrieval metrics or LLM-based evaluation)
  • Ability to quickly spin up user interfaces using Streamlit, Gradio, or similar tools
  • Ability to explain complex technical ideas clearly to both developer teams and non-technical clients
  • Strong English communication skills (B2 level or higher)

Nice to have

  • Development experience with TypeScript
  • Experience incorporating AI into the SDLC (using tools like GitHub Copilot or Cursor to write, test, and review code)
  • Cloud expertise with AWS or Azure (specifically Azure OpenAI or AWS Bedrock)
  • Experience using Databricks (MLflow, Agent Bricks, etc.) for data or model workflows
  • Knowledge of advanced search/retrieval systems (vector databases, semantic search, rerankers)
  • Familiarity with emerging open-source protocols (like Model Context Protocol - MCP) or LLM monitoring tools (like LangSmith or Arize Phoenix)

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