Medical Review Institute of America

Develop and maintain full-stack web applications using modern technologies and AI-assisted tools in a regulated healthcare environment. | Requires 2+ years web development experience with JavaScript, Python, NodeJS, React, cloud deployment, and familiarity with AI-assisted coding tools. | Who We Are - Motivated by Purpose. Powered by Clinical Expertise. Founded in 1983, we’re a clinically driven, tech-enabled utilization management company offering expert clinical reviews, regulatory guidance, and actionable insights to healthcare organizations. Excellence starts with our people. We Offer • A competitive compensation package • Benefits include healthcare, vision, and dental insurance • A generous 401(k) match • Paid vacation, PTO, and holidays • Growth and training opportunities • An award-winning remote work environment Position Summary: Staff-level software engineer responsible for designing, developing, and maintaining modern web applications using full-stack technologies. This role leverages AI-assisted development tools (e.g., Claude Code, Gitlab Duo) alongside traditional engineering practices to deliver high-quality, secure, and scalable software solutions in a regulated healthcare environment. Roles • Develop, maintain, and deploy full-stack web applications • Build user interfaces using React and modern frontend technologies • Develop backend services using NodeJS and Python (APIs, microservices) • Support application hosting, server management, and deployment pipelines • Utilize AI-assisted coding tools to enhance development efficiency and quality Major Responsibilities or Assigned Duties: • Design, implement, test, document, and maintain software applications aligned with coding standards and industry best practices • Develop scalable APIs and backend services using NodeJS and Python • Build responsive, accessible UI components using React • Collaborate with stakeholders to define system scope, requirements, and design solutions • Document, investigate, prioritize, and resolve software defects • Monitor, analyze, and enhance application performance and reliability • Contribute to CI/CD pipelines, automated testing, and DevOps practices • Research and recommend improvements to tools, frameworks, and development processes • Ensure adherence to security, privacy (PHI/HIPAA), and compliance standards • Complete other duties as assigned AI-Assisted Development & Coding Tools Usage • Actively use AI-powered coding assistants (e.g., Claude Code, Gitlab Duo, etc.) throughout the development lifecycle Apply AI tools to • Generate and refactor code • Accelerate debugging and root cause analysis • Create unit tests and documentation • Assist in architectural and design decisions • Improve development speed while maintaining accuracy, maintainability, and security Engineering Expectations • Treat AI-generated content as advisory, not authoritative • Perform thorough validation, testing, and code review of all AI-assisted output • Ensure generated code meets: Coding standards, Secure coding practices, Performance and scalability requirements • Demonstrate ability to refine prompts and evaluate outputs critically Secure & Compliant AI Usage • Do not input sensitive data into AI tools, including: Protected Health Information (PHI), Personally Identifiable Information (PII). & Proprietary or confidential logic • Use only organization-approved AI tools and environments • Comply with all data security, privacy, and regulatory policies Governance & Audit Readiness • Maintain traceability of AI-assisted contributions where required: Clear commit messages, Documentation of AI-assisted design or code decisions • Be prepared to demonstrate: Human validation of outputs, and Compliance with security and development standards • Support organizational standards for responsible AI usage Continuous Improvement • Identify opportunities to improve delivery through AI-assisted workflows • Share best practices, prompt designs, and learnings across the team • Contribute to development of AI usage guidelines and reusable accelerators Risk Awareness • Identify and mitigate risks from AI-generated output, including: Incorrect or incomplete logic, Security vulnerabilities, and Licensing or compliance concerns • Escalate concerns related to AI that may impact security, compliance, or reliability Requirements: Hard Skills • 2+ years of web development experience • Proficiency in JavaScript • Proficiency in Python • Proficiency in NodeJS • Familiarity with modern web architecture • Familiarity with API development • Experience deploying solutions on cloud platform • Experience with React (Advantage) • Experience with AI-assisted coding tool (Advantage) • Experience with Claude (Advantage) • Experience deploying solutions on cloud platforms • Familiarity with containerization and orchestration • Proficiency in Windows C++ • Experience with FastAPI or Django (Advantage) Education • Bachelor’s degree in Computer Science, Engineering, or Information Technology, or an equivalent combination of education and relevant experience. • : Work Environment: Ability to sit at a desk, utilize a computer, telephone, and other basic office equipment is required. This role is designed to be a remote position (work-from-home). Diversity Statement: Diversity creates a healthier atmosphere: All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status, sexual orientation, gender identity or expression, marital status, genetic information, or any other characteristic protected by law. Drug-Free Workplace: This company is a drug-free workplace. All candidates are required to pass a Background Screen before beginning employment. All newly hired employees will take a Drug Screen, as well as agreeing to all necessary Compliance Regulations on their first day of employment. Employees are required to adhere to all applicable HIPAA regulations and company policies and procedures regarding the confidentiality, privacy, and security of sensitive health information. California Consumer Privacy Act (CCPA) Information (California Residents Only): • Sensitive Personal Info: MRIoA may collect sensitive personal info such as real name, nickname or alias, postal address, telephone number, email address, Social Security number, signature, online identifier, Internet Protocol address, driver’s license number, or state identification card number, and passport number. • Data Access and Correction: Applicants can access their data and request corrections. For questions and/or requests to edit, delete, or correct data, please email the Medical Review Institute at HR@mrioa.com.

Design, develop, and operationalize machine learning models to improve healthcare utilization management products, collaborating cross-functionally to integrate ML into scalable software solutions. | 3+ years applied ML experience, 1+ year ML product integration, strong Python and ML libraries knowledge, healthcare data experience, and a Master’s or PhD in Computer Science or related field. | MRIoA is seeking an experienced and pragmatic AI/ML Scientist to drive the design and productization of machine learning solutions tailored to healthcare utilization management. This role is focused on translating proven ML research and existing algorithms into practical, scalable tools that improve operational efficiency, automate decisions, and enhance the internal and external customer experience. Working at the intersection of data science, healthcare operations, and product development, the ideal candidate excels at adapting state-of-the-art models to solve targeted, high-impact business problems. Major Responsibilities or Assigned Duties: Applied ML & Product Integration • Translate business and clinical requirements into machine learning use cases focused on automation, decision support, and risk prediction in the utilization management domain. • Adapt and optimize existing machine learning techniques—including classification, NLP, and time series modeling—to address specific operational workflows and data structures. • Collaborate with developers to rapidly prototype and iterate on ML models with a focus on productionreadiness, scalability, and integration into customer-facing products. • Contribute to the design of intelligent services (e.g., automated prior authorization, clinical rule learning, denial prediction) that directly impact product capabilities. Data & Model Engineering • Collaborate with data engineers to acquire, preprocess, and structure healthcare data from diverse sources (claims, EHR, clinical notes). • Perform data wrangling and feature engineering to enable robust modeling pipelines. • Evaluate and tune model performance using business-relevant metrics (e.g., precision, recall, F1, ROI), ensuring alignment with product goals and customer needs. Cross-functional Product Development • Partner closely with product managers, designers, and software engineers to embed ML capabilities into digital products and decision support tools. • Develop documentation, model APIs, and integration specifications to support seamless model deployment in production systems. • Provide insights and recommendations to support product roadmap decisions and feature prioritization. Operationalization & Lifecycle Management • Ensure ML solutions are reliable, maintainable, and explainable, supporting long-term operation in healthcare environments. • Implement monitoring and retraining strategies to maintain performance and adapt to data drift. • Align development with healthcare compliance requirements (HIPAA, HITRUST, SOC 2) and promote ethical use of AI. Continuous Improvement & Innovation • Stay up to date with emerging research in ML and health AI, identifying opportunities to apply new techniques pragmatically. • Conduct competitive analysis of commercial and open-source AI/ML tools, identifying components to reuse or adapt. • Contribute to internal knowledge sharing, helping build a culture of applied innovation and product-driven development. Work Environment: Ability to sit at a desk, utilize a computer, telephone, and other basic office equipment is required. This role is designed to be a remote position (work-from-home). Diversity creates a healthier atmosphere: All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status, sexual orientation, gender identity or expression, marital status, genetic information, or any other characteristic protected by law. This company is a drug-free workplace. All candidates are required to pass a Background Screen before beginning employment. All newly hired employees will take a Drug Screen, as well as agreeing to all necessary Compliance Regulations on their first day of employment. Employees are required to adhere to all applicable HIPAA regulations and company policies and procedures regarding the confidentiality, privacy, and security of sensitive health information. California Consumer Privacy Act (CCPA) Information (California Residents Only): • Sensitive Personal Info: MRIoA may collect sensitive personal info such as real name, nickname or alias, postal address, telephone number, email address, Social Security number, signature, online identifier, Internet Protocol address, driver’s license number, or state identification card number, and passport number. • Data Access and Correction: Applicants can access their data and request corrections. For questions and/or requests to edit, delete, or correct data, please email the Medical Review Institute at HR@mrioa.com. Requirements: Skills and Experience: • At least 3 years of experience in applied Machine Learning (ML) or data science. • 1 year of experience integrating ML into software products. • Experience working with real-world healthcare data, claims, Electronic Health Record (EHR), and clinical text. • Experience applying ML to structured and unstructured data, particularly in classification, NLP, or time series forecasting. Hard Skills • Strong Python programming skills. • Knowledge of ML libraries, scikit-learn, TensorFlow, PyTorch, Hugging Face, or XGBoost. • Knowledge of model evaluation, validation, and operational considerations (e.g., scalability, explainability, monitoring). Education • Master’s degree in Computer Science, or a related field. • PhD in Computer Science, or a related field. Preferred Qualifications • Experience with MLOps tools and practices (e.g., MLflow, SageMaker, Airflow, Docker). • Familiarity with clinical coding systems (ICD, CPT, SNOMED) and interoperability standards (FHIR, HL7). • Background in building AI features in healthcare SaaS or digital health products. • Awareness of AI regulatory and ethical guidelines in healthcare (e.g., model interpretability requirements).