Minimum of 6 to 9 years of experience in AI/ML solution implementation
Minimum of 3 years of experience in Data Engineering (data pipelines, ETL/ELT, data warehousing, batch/streaming processing)
Multi-Agent System Design & Orchestration
Full-stack AI Integration (Frontend to Backend)
Multi-Cloud AI Infrastructure (AWS Bedrock, Vertex AI, Azure AI, Snowflake Cortex)
Advanced Prompt Engineering & LLM Fine-tuning
Agentic Retrieval Augmented Generation (RAG)
AI Safety, Guardrails & Governance
Enterprise Application Integration & AI Orchestration
Semantic Modeling & Knowledge Graph Construction
High-Scale Vector Database Management
LLM Observability, Evaluation & Monitoring (LLMOps)
Data pipeline design & orchestration (Apache Airflow, Prefect, Dagster)
ETL/ELT development and optimization
Data warehousing & lake architecture (Snowflake, BigQuery, Redshift, Databricks)
Batch and streaming data processing (Spark, Kafka, Flink)
Data modeling and schema design
SQL proficiency and query optimization
Python (FastAPI / Pydantic)
Edio & Render (Deployment & Hosting)
Streamlit & Gradio (UI/UX for AI)
OpenAI & Open-Source Models (Llama 3, Mistral)
Vector Databases (Pinecone, Milvus, Weaviate)
Cloud Platforms: AWS Bedrock, Google Vertex AI, Azure AI Studio
LLM Monitoring Tools (LangSmith / Arize Phoenix)
Data Tools: Apache Spark, Airflow, Kafka, dbt, Snowflake
