AI Engineer

Responsibilities:

• Lead the architecture and implementation of enterprise-scale GenAI solutions for healthcare NLP and intelligent medical coding.
• Design, develop, and optimize Retrieval-Augmented Generation (RAG) pipelines using modern vector databases and embedding models.
• Build production-grade AI agents capable of automating complex clinical workflows.
• Evaluate, benchmark, fine-tune, and deploy foundation models, including GPT, Claude, Llama, Gemini, and open-source LLMs.
• Design scalable prompt engineering frameworks and agent orchestration pipelines.
• Develop robust evaluation frameworks for LLM quality, hallucination detection, and model reliability.
• Drive production deployment, monitoring, observability, scalability, and cost optimization for AI applications.
• Lead migration of legacy ML and rule-based systems into modern GenAI architectures.
• Collaborate with clinical, product, and engineering teams to ensure regulatory compliance with HIPAA, ICD-10 CPT, and SNOMED CT.
• Mentor junior AI engineers through code reviews, technical guidance, and architecture discussions.
• Stay current with advancements in LLMs, AI agents, multimodal AI, and reasoning models, and introduce relevant innovations into production.

Requirements:

• 6+ years of experience in machine learning, artificial intelligence, or data science.
• 4+ years of hands-on experience developing production-ready Generative AI and LLM applications.
• Strong expertise in Python and modern AI frameworks.
• Strong experience with LangChain, LangGraph, LlamaIndex, Hugging Face Transformers, OpenAI APIs, Anthropic APIs, Google Gemini APIs, vLLM, Ollama, and FastAPI.
• Deep expertise in Retrieval-Augmented Generation (RAG) AI agents, prompt engineering, fine-tuning embeddings, vector databases (Pinecone, Weaviate, Chroma, Milvus, FAISS), and production.
• Experience with Kubernetes, Docker, CI/CD pipelines, AWS, Azure, or GCP ML Ops model monitoring, observability, performance optimization, and cost optimization.
• Preferred Experience: Healthcare NLP, clinical documentation, medical coding, ICD-10 CPT, SNOMED CT, and HIPAA compliance.

Preferred Qualifications:

• Experience building enterprise AI platforms.
• Experience deploying multi-agent AI systems.
• Experience with multimodal LLMs.
• Knowledge of LLM evaluation frameworks.
• Experience leading technical projects and mentoring engineers.
• Contributions to open-source AI projects or published research are a plus.