AWS Bedrock Developer+Python

Job description

Educational Requirements - Bachelor of Engineering, BTech, BSc, BCA, MTech, MSc, MCA Service Line - Data Analytics Unit Responsibilities - AWS Bedrock Generative AI: Design and build GenAI solutions using AWS Bedrock and foundation models (FM) such as Amazon Titan, Anthropic Claude, etc. - LLM-based applications: Implement LLM-based applications like chatbots, summarization engines, recommendation systems, and document intelligence - Prompt engineering, fine-tuning, and model evaluation: Apply advanced prompt engineering, fine-tuning, and model evaluation techniques - RAG pipelines: Design RAG (Retrieval-Augmented Generation) pipelines and integrate vector databases - Python Development: Develop scalable backend systems using Python (FastAPI, Flask, Django) - APIs and microservices: Build APIs and microservices to integrate AI/ML services into business applications - Data preprocessing, automation, and orchestration: Write efficient scripts for data preprocessing, automation, and orchestration - AWS Cloud Architecture: Design cloud-native solutions using AWS services (Lambda, API Gateway, S3, EC2, IAM, CloudWatch, Step Functions) - Security, scalability, and availability: Architect secure, scalable, and highly available systems - Cost optimization and performance: Optimize cloud cost and performance - Data privacy and compliance: Ensure data privacy and compliance for AI workloads - Data AI Integration: Work with structured unstructured datasets for AI applications - Data pipelines: Build pipelines to integrate external data sources with LLMs - Vector search and semantic capabilities: Implement vector search, embeddings, and semantic search capabilities - Collaboration Leadership: Collaborate with data scientists, ML engineers, product teams, and business stakeholders - Leadership in design discussions: Lead design discussions and provide technical guidance to junior developers - Agile/Scrum: Participate in Agile/Scrum development cycles Additional Responsibilities - Preferred Skills: Experience with LangChain, LlamaIndex, or similar frameworks - Knowledge of vector databases (FAISS, Pinecone, Weaviate, OpenSearch) - Exposure to Docker, Kubernetes, and containerization - Understanding of ML lifecycle, MLOps, and model deployment - Experience in big data or data engineering tools (Glue, Redshift, Spark) Technical and Professional Requirements - Primary skills: Technology- >Geographical Information System- >Spatial Databases- >SQL Server,Technology- >OpenSystem- >Python - OpenSystem Preferred Skills - Technology- >OpenSystem- >Python - OpenSystem- >Python - Technology- >AI-Generative AI- >Generative AI - Basic- >closed models (aws bedrock)