We are looking for an AI Engineer to join our Information Technology team. The ideal candidate will be a practitioner-level specialist with deep expertise in AI, machine learning, and data engineering. This role will focus on designing, developing, and deploying AI-powered data and intelligence solutions supporting our care insights platform. You will transform clinical, operational, medication, and incident data into timely, actionable intelligence that improves care delivery and supports better clinical decision-making.

Key Responsibilities

Design, develop, and maintain AI capabilities supporting our insights platform, synthesizing complex care and operational data into actionable insights for behavioral pattern analysis, client risk identification, medication adherence monitoring, and early-warning indicators. Develop predictive models and early-warning capabilities using historical and current organizational data, identifying signals associated with changes in client risk, behavioral patterns, incidents, medication adherence, and care delivery; evaluate model performance (sensitivity, specificity, false-positive rates) and incorporate user feedback to improve insight quality. Build secure LLM solutions for clinical and enterprise information, including Retrieval-Augmented Generation (RAG) using governed organizational data, prompt management, and evaluation frameworks; assess LLM outputs for accuracy, relevance, hallucination, and clinical usability. Develop reusable AI services and APIs supporting dashboards and applications; partner with analytics teams to integrate AI-generated insights with enterprise BI tools; optimize the timeliness and usability of insights for clinical and operational teams. Deploy AI and machine-learning services using scalable cloud-native architectures; establish model evaluation, monitoring, and drift detection; monitor production systems for accuracy, performance, latency, reliability, and cost. Ensure compliance with HIPAA, state regulatory requirements, and organizational security policies; implement responsible AI practices including bias detection, explainability, traceability, and human oversight; design human-in-the-loop processes so clinical judgment remains central to high-impact decisions.

Requirements

Education: Bachelor's degree in Computer Science, Engineering, Data Science, or related field Experience: 5+ years in AI engineering, machine learning, data engineering, software engineering, or related fields Skills: Hands-on experience with LLM APIs and orchestration frameworks; prompt engineering and RAG architectures; strong proficiency in Python and modern AI/data frameworks; experience building predictive models, ML pipelines, or advanced analytics solutions; APIs and microservice development; cloud-native services (Docker, CI/CD) Technical Stack: Experience with Microsoft Azure, Microsoft Fabric, Azure Data Lake, or comparable cloud/data platforms; understanding of Medallion data architecture and enterprise data governance Other: Structured and unstructured dataset experience; data quality and security understanding; ability to communicate technical AI concepts to non-technical and clinical audiences

Preferred Qualifications

Healthcare, behavioral health, clinical analytics, or regulated-industry experience Reinforcement learning, feedback-based optimization, or adaptive AI systems exposure Experience working with electronic health records (EHR) or clinical data systems Background in care delivery, clinical operations, or behavioral health domain

Benefits

Competitive Salary: Market-competitive based on experience and qualifications Health and Wellness: Comprehensive health insurance, wellness programs, and mental health support Work-Life Balance: Generous PTO, remote work flexibility, and flexible hours Professional Development: Training programs, conference opportunities, and continuous learning support Mission-Driven Work: Opportunity to directly impact care delivery and patient outcomes in behavioral health