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.