AWS Bedrock & Generative AI
Design and build GenAI solutions using AWS Bedrock and foundation models (FM) such as Amazon Titan, Anthropic Claude, etc.
Implement LLM-based applications like chatbots, summarization engines, recommendation systems, and document intelligence
Apply advanced prompt engineering, fine-tuning, and model evaluation techniques
Design RAG (Retrieval-Augmented Generation) pipelines and integrate vector databases
Python Development
Develop scalable backend systems using Python (FastAPI, Flask, Django)
Build APIs and microservices to integrate AI/ML services into business applications
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)
Architect secure, scalable, and highly available systems
Optimize cloud cost and performance
Ensure data privacy and compliance for AI workloads
Data & AI Integration
Work with structured & unstructured datasets for AI applications
Build pipelines to integrate external data sources with LLMs
Implement vector search, embeddings, and semantic search capabilities
Collaboration & Leadership
Collaborate with data scientists, ML engineers, product teams, and business stakeholders
Lead design discussions and provide technical guidance to junior developers
Participate in Agile/Scrum development cycles

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)

* Primary skills:Technology->Geographical Information System->Spatial Databases->SQL Server,Technology->OpenSystem->Python - OpenSystem