Lead AI Software Engineer

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

📋 Description

• Taking ownership of product-level AI solution design and implementation in partnership with the AI Architect.

• Constructing RAG pipelines utilizing EHR data, claims, and clinical text through embeddings and vector search.

• Creating, fine-tuning, and assessing LLMs and traditional ML models with effective guardrails.

• Setting up and managing MLOps infrastructure, which includes experiment tracking, CI/CD, and drift monitoring.

• Overseeing the reliability, security, and cost aspects of your product’s AI services, covering SLOs and incident response.

• Ensuring the integration of HIPAA compliance and responsible AI practices throughout development and operations.

• Reviewing code and experiments with a focus on reproducibility while mentoring engineers and data scientists within the team.

• Contributing reusable AI components to the shared platform and utilizing GitHub and Microsoft Copilot to enhance team productivity.

⛳️ Requirements

• A Bachelor’s degree in Computer Science, Information Technology, Health Informatics, or a related discipline.

• Over 10 years of software engineering experience, including a minimum of 5 years delivering AI/ML solutions in production settings.

• At least 2 years of experience leading AI/ML projects or teams.

• Experience in the healthcare domain, particularly in clinical or revenue cycle management environments.

• Practical experience with OpenAI or Anthropic models, encompassing prompt engineering, function calling, and evaluation.

• Proficiency in Python and familiarity with the ML ecosystem — including PyTorch or TensorFlow, Hugging Face, LLM orchestration frameworks, and vector databases.

• Hands-on experience with the Azure AI platform, specifically AI Foundry, Azure OpenAI, and Azure ML.

• Skilled in SQL Server and T-SQL using SSMS, along with experience integrating AI services into .NET/C# applications.

• MLOps experience with MLflow or similar tools, Docker, Kubernetes, CI/CD for ML, and monitoring for drift and bias.

• A solid understanding of HIPAA, PHI/PII management and de-identification, and Responsible AI practices.

• Proficiency with Visual Studio and a working knowledge of Microsoft Copilot and GitHub Copilot.

• Excellent communication, analytical, and documentation skills, thriving in a collaborative team environment.

• A curious intellect that constantly seeks the best, most efficient, and cost-effective growth strategies.

• An outcome-focused, results-driven mindset that views challenges as opportunities and approaches work with optimism.

🏝️ Benefits

• A comprehensive suite of benefits.