AI & Analytics Engineer

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Summary
The AI & Analytics Engineer I supports the design, build, and delivery of AI-powered applications, data pipelines, and analytics solutions that drive operational efficiency and decision-making across the organization.

This is a developing-professional role focused on hands-on execution under the guidance of senior engineers, with the goal of expanding the team’s capacity to deliver AI applications and distribute insights at greater velocity.

Description

Core Responsibilities

AI Applications Development

Assist in building and enhancing AI-powered applications and agents that support 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.

Qualifications
Qualifications

Experience

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

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.

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

Compensation:
Role Dependent

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.

EEO Statement
PM Pediatric Care is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status or any other characteristic protected by law.