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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead AI Software Engineer - US Remote - **Company:** Goldstone Partners, Inc. - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $170,000.0 - $185,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Microsoft Azure, Health Informatics, C Sharp (Programming Language), Continuous Integration, Github, Python (Programming Language), Machine Learning, Microsoft Visual Studio, Tensorflow, Azure Machine Learning, Search Technologies, Software Deployment, Software Engineering, Systems Integration, Transact-SQL, Microsoft Power Automate, GitHub Copilot, Pytorch, Large Language Models, Prompt Engineering, AI Platforms, Kubernetes, Information Technology, HuggingFace, Machine Learning Operations, SQL Server Management Studio (SSMS), Data Pipelines, Docker - **Published:** June 20, 2026 - **Apply:** https://arc.dev/remote-jobs/j/goldstone-partners-llc-lead-ai-software-engineer-us-remote-oyay6th9v8 ## About the Role 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! Applicants must be currently authorized to work in the United States on a full-time basis without current or future visa sponsorship. You Value: Communication, Integrity, Curiosity, * 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, Anything is possible. You have a "can do" attitude and your glass is always half full. ## Description * 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 ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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