Full Stack AI Engineer

This is a fully remote position, open to applicants in Argentina.

📋 Description

• Create AI applications tailored for healthcare workflows.

• Design and implement RAG pipelines, encompassing document ingestion, chunking, embeddings, vector storage, and retrieval quality assessment.

• Integrate APIs from LLM providers such as Azure AI Foundry, Amazon Bedrock, and OpenAI, ensuring a balance of quality, cost, and latency.

• Develop agentic workflows utilizing LangChain and LangGraph, which include tool invocation, multi-step orchestration, and maintaining persistent conversation states.

• Create real-time voice agents using WebSockets, streaming speech-to-text and text-to-speech pipelines, as well as platforms like Retell.

• Develop application features and backend services utilizing Python 3.12+ and JavaScript/Node.js.

• Design REST APIs and asynchronous processing workflows leveraging BullMQ, RabbitMQ, or Amazon SQS.

• Implement structured outputs, validation, retries, and fallback mechanisms to ensure reliable AI functionalities.

• Establish tracing, evaluation, and monitoring processes to assess model performance, diagnose issues, and enhance efficiency.

• Containerize services using Docker and Docker Compose; contribute to AWS deployments and CI/CD processes.

• Collaborate on sprint planning, code reviews, and technical decision-making while adhering to healthcare privacy and security protocols.

• Deliver dependable AI features with quantifiable retrieval quality, responsive voice interactions, and transparent system visibility.

• Balance model quality, cost, latency, and context limits while ensuring the software is secure, comprehensible, and production-ready.

⛳️ Requirements

• Solid hands-on experience in building RAG systems, focusing on vector search, embeddings, chunking strategies, and retrieval trade-offs.

• Practical experience in integrating LLM provider APIs and deploying AI features in a production environment.

• Proficient in Python and JavaScript/Node.js, particularly in API development and service integrations.

• Familiarity with LangChain and LangGraph for orchestrating stateful LLM workflows.

• Experience in developing real-time voice applications, including streaming, turn-taking, interruption management, and latency optimization.

• Knowledge of message queues and reliable background processing.

• Working experience with Docker, Docker Compose, Git, and GitHub.

• Familiarity with CI/CD tools like AWS CodePipeline or similar.

• Experience in an iterative development setting, utilizing Jira and sprint planning.

• Understanding of HIPAA regulations and the responsibilities associated with managing protected health information (PHI).

• Excellent communication skills, sound technical judgment, and the ability to translate loosely defined requirements into maintainable software.

• Additional valued experience with Parse and MongoDB.

• Additional valued experience with AWS services including ECS, Lambda, and Application Load Balancer.

• Additional valued experience in healthcare software or applications dealing with sensitive data.

• Additional valued experience in multi-agent coordination and long-running workflows involving checkpointing, memory, and persistence.

• Additional valued experience in prompt engineering, schema-constrained generation, and function/tool definitions.

• Additional valued experience in LLM evaluation, observability, and testing of non-deterministic systems.

• Additional valued experience in mitigating hallucinations, prompt injections, and unsafe tool usage through validation and guardrail design.

🏝️ Benefits

• Competitive salary and benefits package.

• Opportunities for professional development and ongoing training.

• Collaborative and innovative work environment.

• Flexible work arrangements and a focus on work-life balance.