Lead AI Software Engineer – US Remote

Goldstone Partners, Inc.•Oak Brook, IL

6h•$170,000 - $185,000•Remote

About The Position

As the newest member of our AI Engineering team, you'll own the design and delivery of AI/ML solutions that drive measurable clinical and business outcomes across our SmartCare platform. With 10+ years in software engineering and at least 5 years delivering AI/ML solutions in production environments, you bring both architectural thinking and hands-on execution from data pipelines and LLM fine-tuning to MLOps and production deployment. You have demonstrated healthcare domain experience, a deep command of Azure AI services, and the ability to build responsibly in a HIPAA-regulated environment. If you're passionate about applying AI to behavioral health and want to make a measurable impact, let's talk!

Requirements

Bachelor’s degree in Computer Science, Information Technology, Health Informatics, or a related field
10+ years of software engineering experience with at least 5 years delivering AI/ML solutions in production environments
2+ years leading AI/ML initiatives or teams
Healthcare domain experience in a clinical or revenue cycle management setting
Hands-on experience with OpenAI or Anthropic models, including prompt engineering, function calling, and evaluation
Strong Python and ML ecosystem fluency — PyTorch or TensorFlow, Hugging Face, LLM orchestration frameworks, and vector databases
Hands-on Azure AI platform experience, including AI Foundry, Azure OpenAI, and Azure ML
Proficiency in SQL Server and T-SQL using SSMS, and experience integrating AI services into .NET/C# applications
MLOps experience with MLflow or equivalent, Docker, Kubernetes, CI/CD for ML, and monitoring for drift and bias
Solid understanding of HIPAA, PHI/PII handling and de-identification, and Responsible AI practices
Proficiency with Visual Studio and working familiarity with Microsoft Copilot and GitHub Copilot
Refined communication, analytical and documentation skills – you thrive in a team-oriented environment
Intellectual curiosity - a mind that’s always thinking about the best, most efficient, and cost-effective way to grow
Outcome-focused, results-oriented mindset — you see challenges as opportunities and approach work with optimism

Responsibilities

Owning product-level AI solution design and delivery in collaboration with the AI Architect
Building RAG pipelines using EHR data, claims, and clinical text using embeddings and vector search
Developing, fine-tuning, and evaluating LLMs and classical ML models with robust guardrails
Establishing and operating MLOps infrastructure, including experiment tracking, CI/CD, and drift monitoring
Managing reliability, security, and cost for your product’s AI services, including SLOs and incident response
Ensuring HIPAA compliance and responsible AI practices are embedded across development and operations
Reviewing code and experiments with an emphasis on reproducibility - mentoring engineers and data scientists on the team
Contributing reusable AI components back to the shared platform and leveraging GitHub and Microsoft Copilot to improve team productivity