AI Engineer | Python + GenAI + Data | 8+ Years Experience 8+ years of engineering experience with Python as the primary language across data, AI, and backend systems Strong proficiency in Generative AI — LLMs, prompt engineering, fine-tuning, and deploying AI models in production Hands-on experience with Context Engineering — designing context windows, retrieval pipelines, and memory management for LLM applications Experience building and optimizing RAG (Retrieval-Augmented Generation) pipelines using vector databases Proficient in Knowledge Graph design and implementation — Neo4j, RDF, SPARQL, and graph-based reasoning for AI applications Strong background in Data Engineering — ETL/ELT pipelines, data modeling, and orchestration tools (Airflow, Prefect, or Dagster) Experience designing Semantic Layers — ontologies, embeddings, and semantic search to connect structured and unstructured data Hands-on building AI Chatbots and conversational agents Proficient with LLM APIs — OpenAI, Anthropic, Gemini, and open-source models (LLaMA, Mistral, Falcon) Experience with vector search, semantic similarity, and embedding strategies (OpenAI Embeddings, Sentence Transformers) Strong understanding of data pipelines — ingestion, transformation, enrichment, and serving layers at scale Familiarity with cloud AI services — AWS Bedrock, Azure OpenAI, GCP Vertex AI Experience with MLOps practices — model versioning, monitoring, and deployment using MLflow, Weights & Biases Proficient with SQL and NoSQL databases alongside graph and vector stores for hybrid data architectures