- 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
- Primary skills Technology Geographical Information System Spatial Databases SQL Server Technology OpenSystem Python OpenSystem
- 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
Technology->AI-Generative AI->Generative AI - Basic->closed models (aws bedrock),Technology->OpenSystem->Python - OpenSystem->Python
