Case Status®

Full-stack Engineer

• Implement innovative features using Python (Flask, Sqlalchemy, Redis, Celery) on the backend
• Build frontend components using Next.js/React/TypeScript and maintain existing Ember.js frontend
• Write reusable and testable code
• Develop and launch impactful product features
• Ensure the stability and performance of applications
• Actively participate in bi-weekly agile sprints and maintain adequate story points
• Contribute positively to team culture; report to Engineering Team Lead

Full Stack Engineer

QA Engineer

• Report to the Director of Product as part of Product & Engineering
• Develop and execute comprehensive test plans for CaseStatus web app, Android app, and iOS app using Ghost Inspector for regression and feature testing
• Streamline and optimize existing and new test scenarios to maximize efficiency and accuracy
• Enhance automated web application tests and expand knowledge of HTML and CSS
• Explore and apply visual testing, functional testing, load testing, and unit testing techniques
• Conduct thorough User Acceptance Testing (UAT) on new features, enhancements, and bug fixes using engineering Jira boards
• Document all testing steps and findings with clarity and precision
• Log defects, conduct regression testing to validate bug fixes, and ensure issues are resolved effectively
• Isolate and document reproduction steps for bugs reported by customers and internal team members
• Triage newly submitted bugs and low-level enhancements from the Development Request Board in Jira and handle urgent tickets
• Work closely with developers and the QA team to ensure high-quality, bug-free updates and proactively communicate potential release issues
• Utilize tools such as Sentry, Chrome Developer Tools, Log Rocket, and Postman to track and resolve bugs
• Assist with creating and maintaining detailed documentation for new features in Confluence as needed
• As a remote employee, may be required to work from the Charleston, SC office once per quarter and attend company offsite events in January and July

Quality Assurance Specialist

Machine Learning Engineer

• Translate product problems into ML approaches, baseline against simple methods, and define success metrics and evaluation protocols.
• Build and maintain training datasets.
• Iterate on models, then graduate them from notebooks to production-quality services with proper testing, logging, and observability.
• Design, deploy, and maintain inference services and batch jobs. Handle scale, latency, and cost with appropriate architectures, queues, and caching.
• Monitor for data drift, model degradation, and operational issues. Set up dashboards and alerts, run A/B or offline evaluations.
• Work across the stack as needed: schema design, APIs, CI/CD, containerization, and infrastructure-as-code in cloud environments.
• Contribute to agentic AI development: implement orchestration layers where AI agents can plan, act, and use tools, and integrate these agents with Case Status’ platform using MCP.
• Document decisions and results, and communicate trade-offs to technical and non-technical stakeholders.