AWS Bedrock & Generative AI Development Design and develop applications using AWS Bedrock (LLMs, Foundation Models) Integrate models like Anthropic Claude, Amazon Titan, or other Bedrock-supported models Build prompt engineering strategies and AI workflows Implement use cases such as chatbots, summarization, recommendations, and NLP pipelines Python Development Develop backend services and APIs using Python (FastAPI, Flask) Implement AI/ML pipelines and integrate model responses into applications Build reusable libraries for LLM interaction and automation Infrastructure as Code (Terraform) Design and implement cloud infrastructure using Terraform Build reusable modules for deploying AWS resources Manage Terraform state and automate deployments via CI/CD Provision services like Bedrock, Lambda, API Gateway, S3, IAM AWS Cloud Development Work with key AWS services: Lambda, API Gateway (serverless apps) S3 (data storage) DynamoDB / RDS (data persistence) IAM & VPC (security & networking) Build scalable and secure cloud-native applications DevOps & Automation Implement CI/CD pipelines using GitHub Actions, Jenkins, or AWS CodePipeline Automate deployments and testing of AI applications Monitor applications using CloudWatch, X-Ray Security & Governance Implement secure access to Bedrock models using IAM policies Ensure compliance, data privacy, and secure prompt handling Manage API authentication and authorization Required Skills & Qualifications Core Skills 3–6 years of experience in Python development / Cloud engineering Hands-on experience with AWS (mandatory) Experience or exposure to AWS Bedrock / Generative AI services Programming & Frameworks Strong proficiency in Python Experience with: FastAPI / Flask REST API development Familiarity with AI/ML libraries (optional: LangChain, Transformers) Terraform & DevOps Hands-on experience with Terraform (IaC) Experience with: Infrastructure automation CI/CD pipelines Git version control AWS Services Core services: Lambda, API Gateway S3, DynamoDB/RDS IAM, VPC Exposure to serverless architecture
Experience with LLM frameworks (LangChain, LlamaIndex) Knowledge of prompt engineering and RAG (Retrieval-Augmented Generation) AWS Certifications (Solutions Architect / AI Specialty) Experience with Docker / Kubernetes
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