Core Responsibilities
AI Applications Development
- Assistin building and enhancing AI-powered applications and agents that support business workflows
- Build user-facing interfaces using a modern frontend framework (React, Vue, Angular, or similar) that surface AI capabilities to clinical and operational users
- Develop backend services and REST or GraphQL APIs (Python, Node.js, .NET, or similar) that integrate AI capabilities into business workflows
- Develop components of AI solutions that automate routine tasks and surface insights
- Gather requirements from stakeholders with guidance from senior team members
- Iterate on AI applications based on user feedback and testing results
- Provide ongoing Level 3 support for software products
AI Integration & Delivery
- Support integration of AI applications with enterprise systems (e.g., EMR, HRIS, data platforms) under senior direction
- Assistwith deployment, testing, and monitoring of AI solutions in lower and production environments
- Translate documented business requirements into functional workflows
- Follow established standards for reliability, security, and code quality
Data Engineering & Pipeline Development
- Build and maintain ETL/ELT pipelines that feed analytics and AI use cases
- Ingest and transform data from multiple source systems into centralized platforms
- Validate accuracy, completeness, and structure of pipeline outputs
Analytics & Data Modeling
- Develop andmaintainsemantic models, datasets, and dashboards (Power BI and related tools)
- Apply standardized business metrics and KPI definitions across reports
- Optimizequeries and data structures for performance and usability
- Implement andmaintainrow-level security and access controls on reports
Cross-Functional Collaboration
- Partner with IT, clinical informatics, operations, and business stakeholders to understand reporting and AI needs
- Communicate progress, blockers, and trade-offs clearly to both technical and non-technical audiences
- Escalate architectural or scope questions to senior engineers
EngineeringStandards & Quality
- Follow team practices for source control, code review, documentation, and testing
- Monitor AI outputs and data pipelines for accuracy and reliability
- Support compliance with data security, privacy, and governance standards (HIPAA-aware)
Continuous Learning & Improvement
- Build technical depth in AI/ML tooling, cloud services, and modern data platforms
- Contribute small improvements to existing AI tools, dashboards, and pipelines
- Stay current with emerging AI and analytics technologies relevant to healthcare operations
Scope & Impact
- Contributes directly to AI application and analytics delivery used across business operations
- Expands team throughput on AI applications, dashboards, and insight distribution
- Operates under the technical direction of the AI & Analytics Engineer II and Senior Director of AI, Data, & Enterprise Applications
Success Metrics
- Volume and quality of analytics and AI deliverables completed
- Reliability and performance of owned pipelines and reports
- Reduction in backlog for analytics and AI requests
- Growth in technicalproficiencyover the first 12 6 months
- Stakeholder satisfaction with delivered solutions
Target Compensation: 125k - 135k
The salary/rate range listed here has been provided to comply with local regulations and represents a potential base salary/rate for this role. Please note that actual salaries/rates may vary within this range above or below, depending on experience and location. We look at compensation for each individual and based on experience and qualifications.