AWS Bedrock Developer+Python

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)