Senior AI Engineer

About Simplify Healthcare:

Simplify Healthcare is a leading healthcare IT company, founded in 2008, dedicated to empowering health insurance providers through cloud-based, automation-driven solutions. Our latest venture — an agentic AI platform — leverages cutting-edge language models and retrieval-augmented generation (RAG) to revolutionize payer operations.

What You'll Do:

As a Sr. Software Engineer- AI & ML, you'll be at the core of designing and building our agentic AI and conversational intelligence platform that supports use cases such as claims automation, provider queries, and policy insights.

You'll work with advanced tools and frameworks to architect intelligent agents and RAG pipelines that deliver real-time, context-aware responses.

Responsibilities:

• Design and build LLM-based RAG pipelines with vector databases (e.g. Azure Cognitive /AI Search).
• Develop conversational AI agents using LangChain, Python, and agentic frameworks.
• Fine-tune or prompt-tune LLMs (Azure OpenAI) for domain-specific use cases in healthcare insurance.
• Integrate structured/unstructured data sources (MongoDB, MSSQL, etc.) for context injection into AI pipelines.
• Create scalable APIs (FastAPI) to serve AI models and handle requests in real-time production environments.
• Collaborate with product and data teams to design data pipelines, evaluate model performance, and enhance UX.
• Optimize memory, context handling, and multi-agent collaboration to ensure reliable, explainable outputs.
• Contribute to experiment tracking, A/B testing, and prompt engineering tools for faster iteration cycles.

Tech Stack:

• Languages & Frameworks: Python, FastAPI,
• AI Tooling: LangChain, Azure OpenAI, Vector Embeddings
• Vector DBs: Azure AI Search, Graph Database
• Databases: MongoDB, MSSQL
• Infra/DevOps: Azure, Docker, Azure DevOps Pipelines
• Other: Git, Postman, Application Insights

Requirements:

• 5 years of hands-on experience in AI/ML or NLP engineering, ideally in enterprise or healthcare contexts.
• Experience building RAG systems, vector search, or LLM-based applications in production.
• Proficiency in Python and building APIs with FastAPI or Flask.
• Experience with MongoDB, document-based query optimization, and working with semi-structured data.
• Understanding of prompt engineering, memory management, and multi-agent orchestration.
• Experience working with Azure or cloud-hosted AI models is a plus.
• Strong collaboration skills with product and backend teams.

Nice to Have:

• Exposure to agentic AI architecture (multi-agent coordination, goal decomposition).
• Experience integrating structured data (claims, benefits, policies) into AI workflows.
• Knowledge of healthcare payer operations, HIPAA, or compliance requirements.