Remote Agentic and Machine Learning Engineer

Job Description Our client is looking for AI Engineers to build and scale in‑house, production‑grade AI solutions supporting healthcare use cases across Utilization Management, suicide risk assessment, hospital census, compliance, and risk intelligence. The role is intentionally weighted ~70% toward agentic and generative AI solutions (multi‑step, tool‑using agents and RAG systems) and ~30% toward traditional machine learning, used selectively for prediction, forecasting, anomaly detection, and mathematical modeling where LLMs are not appropriate. In this role, you will design and implement complex RAG pipelines and agentic workflows, build backend AI services in Python, and integrate data across Snowflake, Azure, and legacy healthcare systems. You'll focus heavily on data cleansing, reliability, and evaluation, owning solutions end‑to‑end from raw data and retrieval to production deployment We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.

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• LLM / Generative AI
• Prompt engineering, RAG pipelines, LLM-as-judge, hallucination mitigation
• Agentic AI
• Multi-agent orchestration, tool selection, agent validation and testing frameworks
• ML / Anomaly Detection
• Forecasting models, anomaly detection, scoring algorithms
• Experience developing AI Solutions in Snowflake
• CI/CD & DevOps
• GitHub, automated testing, deployment pipelines (dev/test/prod)
• Healthcare Domain Awareness
• HIPAA compliance, PHI handling, clinical data literacy (HL7, fax/document AI)
• Data Engineering
• SQL, data pipelines, integration with BI platforms (Power BI, Salesforce)
• Azure Cloud
• Azure AI Search, Azure Blob Storage, Azure App Service, VNet/security (RBAC) API & Backend
• Python, REST API development, asynchronous processing (event-driven pipelines)