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Lead Generative AI Developer

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Onsite

Lead Generative AI Developer

EPAM Systems

Lead Generative AI Developer

Skills

ReactNodePythonMicroservicesAmazon EC2AWS LambdaAIAWSAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Coimbatore, Tamil Nadu, India

Work mode:

Onsite

Published on:

2 September 2026

What they need


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

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