Generative AI Engineer

AI & LLM Expertise

12+ years in AI/ML with at least 3 years hands-on LLM and GenAI development. Strong experience with LLM APIs — OpenAI GPT-4o, Anthropic Claude, LLaMA, Google Gemini. Hands-on RAG architecture — vector databases (Pinecone, Weaviate, ChromaDB), chunking, reranking, hybrid search. Agentic AI frameworks — LangChain, LlamaIndex, AutoGen, or CrewAI. LLM fine-tuning using LoRA / QLoRA / PEFT on domain-specific datasets. Prompt engineering — chain-of-thought, few-shot, instruction tuning for clinical contexts. Healthcare Domain (Must Have)

Strong knowledge of healthcare data — EHR/EMR, clinical notes, lab results, imaging, and claims. Proficiency in interoperability standards — HL7, FHIR R4, DICOM, ICD-10, SNOMED CT, LOINC. HIPAA compliance expertise — PHI handling, de-identification, and audit controls. Familiarity with FDA AI/ML SaMD guidelines and GxP compliance for life sciences. Experience with clinical NLP — medical entity extraction, summarisation, and coding automation. Architecture & Platform

Cloud AI platforms — AWS SageMaker / Bedrock, Azure OpenAI / ML, GCP Vertex AI. MLOps — MLflow, Weights & Biases, CI/CD for ML, model drift monitoring. Containerisation and orchestration — Docker, Kubernetes, model serving (FastAPI, Triton). Python (expert), SQL (strong), REST API design, Spark for healthcare data pipelines.