Lead AI Software Engineer

About Streamline Healthcare Solutions

Streamline Healthcare Solutions is a high‑growth technology company building web‑based software for healthcare organizations, delivering solutions that improve behavioral health and quality of life. Established in 2003, we have partnered with premier behavioral health providers and focus on innovative, HIPAA‑compliant technology.

Senior‑level engineer responsible for designing and implementing AI/ML solutions for the healthcare industry, including LLM‑powered applications, retrieval‑augmented generation (RAG), and predictive models. The role is Azure‑first and requires hands‑on experience with OpenAI or Anthropic models, Microsoft Copilot, Git Hub Copilot, SQL Server (SSMS), and Visual Studio. A commitment to HIPAA compliance, Responsible AI, and measurable clinical and business outcomes is essential.

This remote position is based in the United States and offers a salary range of $150,000 - $200,000, DOE. Employment visa sponsorship is not available.

• Co‑design AI solutions with the AI Architect and own product‑level solutioning and delivery within enterprise AI architecture, standards, and governance.
• Lead end‑to‑end implementation for the product squad: RAG over EHR/claims/clinical text using embeddings and vector search.
• Develop and train/fine‑tune models (LLMs and classical ML), create evaluation frameworks, and establish guardrails for hallucination reduction, safety, and PII/PHI handling.
• Deploy production services with containerization/orchestration, optimizing GPU‑aware inference where applicable.
• Establish and operate MLOps: experiment tracking, model registry, CI/CD for ML, canary/A/B testing, monitoring for latency, accuracy, drift, bias, and cost.
• Own reliability, security, and cost for AI services: define SLOs, participate in on‑call/incident response, manage token/GPU budgets, and optimize prompts, embeddings, caching, and indexing.
• Build and maintain data pipelines (e.g., Spark/Databricks) and ensure robust SQL Server performance and data quality; collaborate with DBAs and data engineers.
• Ensure HIPAA compliance and Responsible AI practices across development and operations; partner with security and compliance to meet policy requirements.
• Collaborate with product management, domain experts, and compliance to translate requirements into safe, reliable, high‑impact AI services.
• Conduct reviews emphasizing code quality, experiment rigor, reproducibility, and evaluation discipline; mentor engineers and data scientists.
• Participate in architecture reviews; propose improvements and contribute reusable components (RAG templates, evaluation harnesses) to the shared AI platform.
• Leverage Microsoft Copilot and Git Hub Copilot to improve developer productivity, quality, and documentation, aligning with governance.

• Bachelor’s degree in Computer Science, Information Technology, Health Informatics, or a related field.
• 10+ years in software engineering; 5+ years building and shipping ML/AI solutions; 2+ years leading AI/ML initiatives or teams.
• Azure AI Foundry (Azure AI Studio) knowledge and familiarity with Azure AI resources and deployment patterns.
• Proficiency with SQL Server Management Studio (SSMS) for SQL development, performance tuning, and troubleshooting; strong T‑SQL fundamentals.
• Experience integrating AI services into .NET/C# applications or services.
• Hands‑on experience using OpenAI or Anthropic models (GPT‑4.x/4o, Claude 3.x), including prompt engineering, function/tool calling, and evaluation.
• Experience with Microsoft Copilot and Git Hub Copilot in professional workflows.
• Strong Python and ML ecosystem skills:
  PyTorch/Tensor Flow, transformers/Hugging Face, embeddings, LLM orchestration (e.g., Lang Chain or Llama Index), and vector databases (FAISS, Azure AI Search, Pinecone).
• MLOps expertise: MLflow/WandB, Docker, Kubernetes, CI/CD for ML, model registries, monitoring, A/B testing, and rollback strategies.
• Cloud AI on Azure:
  Azure OpenAI, Azure AI Search, Azure ML, Azure Key Vault, with understanding of IAM, secrets, and encryption.
• Demonstrated security, privacy, and compliance competence: HIPAA,…