Gen Ai Engineer / Senior Gen Ai Engineer

Generative AI Engineer (LLMs & RAG) – Healthcare SaaS Location : Remote / Hyderabad (preferred) Experience : 5+ years Employment Type : Full-time Domain : Generative AI, Healthcare, SaaS About the Role We are looking for a hands-on Generative AI Engineer with expertise in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). In this role, you will architect and deliver production-grade AI systems that combine unstructured and structured healthcare data to power a next-generation clinical assistant. You will work at the cutting edge of Generative AI and healthcare innovation, helping design safe, scalable, and impactful solutions that directly influence real-world patient outcomes. This is a chance to take ownership of core AI systems in a fast-moving, high-impact product. Key Responsibilities - Architect and optimize RAG pipelines – ingestion, embedding, retrieval, grounding, and generation.

• Experiment with LLMs – open-weight models (LLaMA, Mistral, Falcon) and API-based models (OpenAI, Anthropic).
• Implement evaluation & monitoring frameworks (retrieval precision, grounding accuracy, hallucination checks, latency, safety).
• Work with diverse healthcare datasets – PDFs, EHR / EMR data, CSVs, structured knowledge bases.
• Deploy AI services to cloud-native environments (AWS, GCP, or Azure) with observability and security in mind.
• Collaborate cross-functionally with product, clinicians, DevOps, and QA to ship production-ready features. Must-Have Skills - 5+ years of experience in software / ML engineering with strong Python skills (backend + API development).
• Proven expertise building LLM-powered applications and RAG pipelines.
• Strong understanding of embeddings, transformers, prompt engineering / orchestration, and NLP techniques.
• Hands-on experience with vector databases (FAISS, Pinecone, Qdrant, Weaviate, Milvus).
• Familiarity with LangChain, LLMOps, and ML deployment workflows.
• Experience with containerized deployments (Docker / Kubernetes) and cloud platforms.
• Exposure to both open-weight LLMs and hosted APIs. Nice to Have - Experience in healthcare / healthtech;

knowledge of HIPAA-compliant systems.