AI & Analytics Engineer (Software Engineer – Full stack)

Core Responsibilities

AI Applications Development

• Assist in 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

• Assist with 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 and maintain semantic models, datasets, and dashboards (Power BI and related tools)

• Apply standardized business metrics and KPI definitions across reports

• Optimize queries and data structures for performance and usability

• Implement and maintain row-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

Engineering Standards & 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 technical proficiency over the first 12–18 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.

• 2–4 years of experience in data analytics, BI development, data engineering, or software development

• Hands-on experience building custom software products, including writing code and delivering end-to-end solutions aligned to business requirements.

• Proven ability to conduct testing, troubleshoot and debug issues, and ensure high-quality, reliable application performance across environments.

• Hands-on experience building dashboards, reports, or data pipelines in a professional setting

• Hands-on experience building and shipping user-facing applications end-to-end, including both frontend (web or mobile UI) and backend (services, APIs, data access) components
• Demonstrated proficiency with a modern frontend framework (React, Vue, Angular, or similar)
• Demonstrated proficiency with a backend framework (FastAPI, Django, Express, ASP.NET Core, Spring Boot, or similar)
• Active GitHub profile or equivalent code portfolio with reviewable code samples (required at application)
• Exposure to AI, machine learning, or workflow automation projects (academic or professional) preferred

Technical & Functional Expertise

• Demonstrated proficiency in modern software engineering tools (IDES), practices; including Agile development, CI/CD workflows, automated testing, and code review standards.
• Daily experience with Git and GitHub (or comparable), including branching, pull requests, and code review workflows
• Working proficiency with SQL and relational data modeling
• Experience with Power BI (or comparable BI platform) including DAX and semantic models
• Familiarity with ETL/ELT concepts and at least one data integration tool
• Exposure to cloud platforms (Azure preferred) and AI/ML services a plus
• Comfort working with both structured and unstructured data

Competencies

• Strong analytical and problem-solving skills with attention to detail
• Willingness to learn from senior engineers and apply feedback quickly
• Effective written and verbal communication with technical and non-technical partners
• Ability to manage multiple concurrent tasks and meet committed delivery dates

• Healthcare or pediatrics domain interest is a plus