Full Stack AI Engineer

• Build AI applications for healthcare workflows
• Design and build RAG pipelines, including document ingestion, chunking, embeddings, vector storage, and retrieval quality testing
• Integrate LLM provider APIs including Azure AI Foundry, Amazon Bedrock, and OpenAI, balancing quality, cost, and latency
• Develop agentic workflows using LangChain and LangGraph, including tool calling, multi-step orchestration, and persistent conversation state
• Build real-time voice agents using WebSockets, streaming speech-to-text and text-to-speech pipelines, and platforms such as Retell
• Develop application features and backend services using Python 3.12+ and JavaScript/Node.js
• Design REST APIs and asynchronous processing workflows using BullMQ, RabbitMQ, or Amazon SQS
• Implement structured outputs, validation, retries, and fallback behavior for dependable AI features
• Establish tracing, evaluation, and monitoring to assess model behavior, diagnose failures, and improve performance
• Containerize services with Docker and Docker Compose; contribute to AWS deployments and CI/CD pipelines
• Collaborate on sprint planning, code reviews, and technical decisions while applying healthcare privacy and security practices
• Deliver reliable AI features with measurable retrieval quality, responsive voice interactions, and clear system visibility
• Balance model quality, cost, latency, and context limits while maintaining secure, understandable, production-ready software

• Strong practical experience building RAG systems, including vector search, embeddings, chunking strategies, and retrieval tradeoffs
• Hands-on experience integrating LLM provider APIs and shipping AI features into production
• Proficiency in Python and JavaScript/Node.js, including API development and service integrations
• Experience with LangChain and LangGraph for orchestrating stateful LLM workflows
• Experience building real-time voice applications, including streaming, turn-taking, interruption handling, and latency optimization
• Familiarity with message queues and reliable background processing
• Working knowledge of Docker, Docker Compose, Git, and GitHub
• Familiarity with CI/CD tools such as AWS CodePipeline or equivalent
• Experience working in an iterative development environment using Jira and sprint planning
• Awareness of HIPAA and responsibilities involved in handling protected health information (PHI)
• Clear communication, sound technical judgment, and ability to turn loosely defined requirements into maintainable software
• Additional valued experience with Parse and MongoDB
• Additional valued experience with AWS services such as ECS, Lambda, and Application Load Balancer
• Additional valued experience with healthcare software or applications involving sensitive data
• Additional valued experience with multi-agent coordination and long-running workflows with checkpointing, memory, and persistence
• Additional valued experience with prompt engineering, schema-constrained generation, and function/tool definitions
• Additional valued experience with LLM evaluation, observability, and testing of non-deterministic systems
• Additional valued experience mitigating hallucinations, prompt injection, and unsafe tool use through validation and guardrail design