Requirements:

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical discipline.
• Total 12+ years of experience with 3+ years of hands-on experience in machine learning or AI application development, with a proven track record of delivering production-grade solutions.
• Strong programming proficiency in Python, with demonstrated experience in API development using FastAPI or Flask.
• Solid experience in developing AI solutions within the AWS ecosystem, including hands-on use of the following services:Amazon Bedrock, SageMaker, Lambda, API Gateway, and S3 etc.
• Practical knowledge and implementation experience with Large Language Models (LLMs) and Generative AI frameworks, such as: LangChain, Llama Index, or custom RAG (Retrieval-Augmented Generation) architectures.
• In-depth understanding of RAG systems, including embedding generation, document chunking, retrieval, and response synthesis.
• Experience with vector databases (e.g., Pinecone, FAISS, OpenSearch), text embeddings, and prompt engineering is added advantage.
• Strong understanding of cloud security, including OAuth 2.0-based authentication, IAM policies, and secure API design.
• Familiarity with DevOps practices and tools, including CI/CD pipelines, Docker, and Infrastructure as Code (IaC) tools such as CloudFormation, AWS CDK, or Terraform.
• Proficiency in relational databases (e.g., SQL) and data modelling.
• Solid grasp of machine learning algorithms and techniques, including deep learning architectures.
• Skilled in data preprocessing, feature engineering, and data manipulation using modern data science tools and libraries.
• Demonstrated experience working across the full AI/ML project lifecycle — from business requirements analysis to model deployment and productization.
• Strong analytical and problem-solving skills, with a structured approach to debugging and optimization.
  • Excellent communication and collaboration abilities, with experience working in cross-functional and agile teams.