AI Engineer

Responsibilities:

• Design and implement GenAI solutions for medical report understanding and code mapping using LLMs and prompt engineering.
• Build and optimise RAG (Retrieval Augmented Generation) systems for accurate and reliable medical coding.
• Develop and deploy AI agents for multi-speciality medical coding automation.
• Evaluate, benchmark, and select appropriate foundation models (GPT, Claude, Llama, etc. ) for healthcare use cases.
• Implement cost-effective, production-ready GenAI architectures with monitoring and observability.
• Transform existing rule-based systems into GenAI-powered solutions while maintaining accuracy and compliance.
• Collaborate with clinical teams to ensure outputs align with healthcare standards and regulations (HIPAA, ICD-10 CPT, and SNOMED-CT).
• Conduct A/B testing, model evaluation, and continuous performance optimisation.
• Stay updated with the latest GenAI/LLM research and bring relevant techniques into production.

Requirements:

• 3+ years of hands-on experience with LLMs/GenAI (GPT, Claude, Llama, PaLM, etc. ).
• 3+ years overall in data science/ML engineering.
• Strong proficiency in Python with GenAI libraries (LangChain, LlamaIndex, HuggingFace, OpenAI/Anthropic APIs).
• Exposure to healthcare NLP (clinical reports, medical coding, and terminologies).
• Deep understanding of RAG architectures, embeddings, and vector databases (Pinecone, Weaviate, Chroma).
• Production deployment experience: scaling, monitoring, cost optimisation, and MLOps practices.