Lead Generative AI Developer with AWS

Summary

Lead role designing and building enterprise GenAI solutions on AWS (primarily Amazon Bedrock), integrating foundation models such as Anthropic Claude and Titan, developing RAG architectures, chatbots, copilots and document-processing applications with secure and responsible AI practices.

We are looking for a Lead Generative AI Developer with AWS to design and build cutting-edge GenAI solutions using Amazon Bedrock and similar platforms. In this role, you will develop AI-powered applications, integrate foundation models with enterprise systems and ensure secure, responsible AI practices across business scenarios.

Responsibilities

  • Design and build GenAI solutions using Amazon Bedrock or similar GenAI platforms
  • Integration with foundation models such as Anthropic Claude and Titan
  • Perform prompt engineering and optimization
  • Develop RAG (Retrieval Augmented Generation) architectures
  • Create AI-powered applications such as chatbots, copilots, knowledge assistants and document processing solutions
  • Evaluate and fine-tune LLM-based use cases for business scenarios
  • Integrate GenAI models with enterprise applications and APIs
  • Implement secure AI architectures aligned with enterprise and regulatory standards
  • Ensure data privacy, model governance and responsible AI practices

Requirements

  • Bachelor's or master's degree in Computer Science, Engineering or related field
  • 10+ years of overall experience in IT and 5+ years in cloud architecture
  • Hands-on experience with AWS cloud services such as EC2, S3 and Lambda, as well as RDS, VPC and IAM
  • Proven experience with Amazon Bedrock or similar GenAI platforms
  • Expertise in LLMs, prompt engineering and embeddings alongside RAG frameworks
  • Knowledge of programming languages such as Python, React or Node.js
  • Proficiency in designing API-driven and microservices architectures

Nice to have

  • Familiarity with LangChain, LlamaIndex or similar frameworks
  • Knowledge of vector databases such as OpenSearch, Pinecone or FAISS
  • Understanding of MLOps and model lifecycle management
  • Exposure to multi-cloud environments such as Azure or OpenAI

Benefits

Opportunity to work on technical challenges that may impact across geographies

Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications

Opportunity to share your ideas on international platforms

Sponsored Tech Talks & Hackathons

Unlimited access to LinkedIn learning solutions

Possibility to relocate to any EPAM office for short and long-term projects

Focused individual development

Benefit package:

  • Health benefits
  • Retirement benefits
  • Paid time off
  • Flexible benefits

Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)

See also

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