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Job description : MMC Applied AI Engineer (Prompt Engineering & LLM Applications) Healthcare Domain Job Title : Applied AI Engineer Prompt Engineering & LLM Applications Experience : 5-8 Years Location : Bangalore Domain : Healthcare / HealthTech Employment Type : Full-Time Job Summary : We are looking for an experienced Applied AI Engineer with strong expertise in Prompt Engineering, Generative AI, and LLM-based application development for healthcare use cases. The ideal candidate should have hands-on experience building AI-powered solutions using leading LLM platforms, orchestration frameworks, NLP pipelines, and vector databases for intelligent document processing and healthcare workflows. Key Responsibilities : - Design, develop, and optimize prompt engineering strategies for healthcare AI applications. - Build and deploy LLM-powered solutions using models from OpenAI, Anthropic, or similar platforms. - Develop scalable AI applications leveraging LangChain, LlamaIndex, RAG architectures, and agentic workflows. - Process and analyze structured and unstructured healthcare data including clinical documents, prescriptions, medical records, and patient interactions. - Implement document intelligence workflows using NLP, embeddings, semantic search, and vector databases. - Design and manage vector search pipelines using FAISS, Pinecone, ChromaDB, or similar technologies. - Work closely with product, clinical, and engineering teams to identify AI use cases and deliver production-grade solutions. - Fine-tune prompts and optimize model responses for accuracy, hallucination reduction, compliance, and performance. - Develop APIs and backend services for AI integrations and healthcare automation. - Ensure security, scalability, and compliance standards in healthcare AI implementations. Required Skills : - Strong experience in Prompt Engineering and LLM-based application development. - Hands-on experience with OpenAI, Anthropic, Claude, GPT, or similar LLM APIs. - Experience with orchestration frameworks such as LangChain and LlamaIndex. - Strong Python programming skills with Pandas, NumPy, and data processing libraries. - Experience in NLP, unstructured data processing, and intelligent document extraction. - Knowledge of embeddings, semantic search, and Retrieval-Augmented Generation (RAG). - Hands-on experience with vector databases such as FAISS, Pinecone, ChromaDB, or Weaviate. - Experience developing REST APIs and integrating AI services into applications. - Good understanding of AI model evaluation, prompt optimization, and response quality improvement. Preferred Qualifications : - Experience working in Healthcare, HealthTech, Clinical AI, or Medical Document Processing domains. - Familiarity with HIPAA/compliance-aware AI systems. - Experience with OCR tools, document parsing, and medical NLP workflows. - Exposure to cloud platforms such as AWS, Azure, or GCP. - Knowledge of MLOps, model deployment, and monitoring is a plus. Education : Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or related field. Nice to Have : - Experience with multi-agent AI systems. - Exposure to fine-tuning/open-source LLMs. - Knowledge of healthcare interoperability standards such as HL7/FHIR. - Experience with LangGraph, AutoGen, or CrewAI frameworks. Job description : MMC Applied AI Engineer (Prompt Engineering & LLM Applications) Healthcare Domain Job Title : Applied AI Engineer Prompt Engineering & LLM Applications Experience : 5-8 Years Location : Bangalore Domain : Healthcare / HealthTech Employment Type : Full-Time Job Summary : We are looking for an experienced Applied AI Engineer with strong expertise in Prompt Engineering, Generative AI, and LLM-based application development for healthcare use cases. The ideal candidate should have hands-on experience building AI-powered solutions using leading LLM platforms, orchestration frameworks, NLP pipelines, and vector databases for intelligent document processing and healthcare workflows. Key Responsibilities : - Design, develop, and optimize prompt engineering strategies for healthcare AI applications. - Build and deploy LLM-powered solutions using models from OpenAI, Anthropic, or similar platforms. - Develop scalable AI applications leveraging LangChain, LlamaIndex, RAG architectures, and agentic workflows. - Process and analyze structured and unstructured healthcare data including clinical documents, prescriptions, medical records, and patient interactions. - Implement document intelligence workflows using NLP, embeddings, semantic search, and vector databases. - Design and manage vector search pipelines using FAISS, Pinecone, ChromaDB, or similar technologies. - Work closely with product, clinical, and engineering teams to identify AI use cases and deliver production-grade solutions. - Fine-tune prompts and optimize model responses for accuracy, hallucination
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