Mosai

Support Engineer

• Deliver an excellent, efficient, and quality support response to every client, every time
• Identify, investigate, and research user questions and challenges
• May refer to technical team members for follow-up
• Maintain an awareness of all product knowledge information and how to use internal resources
• Train users of the software and work as a team where needed to resolve an issue
• Troubleshoot client issues, including collecting details as necessary
• Escalation of issues to Team Leads and/or Engineering as necessary to resolve client issues
• Maintain a superior level of service while interpreting and validating technical issues
• Follow up and make scheduled call backs to clients where necessary
• Interact with clients to provide and process information in response to inquiries, concerns, and requests about products and services

Client Support Analyst

Full-stack Engineer

• Provide innovative and scalable solutions
• Complete all phases of software development life cycle
• Work closely with product team for user experience
• Own features/projects from design to deployment
• Contribute to system architecture and technical design discussions
• Troubleshoot and resolve complex technical issues
• Support compliance with healthcare data privacy standards
• Offer technical guidance and mentorship to junior engineers

Senior Software Engineer

Machine Learning Engineer

• Design, build, and maintain scalable data pipelines supporting model training, inference, batch processing, and real-time analytics workflows.
• Monitor production ML pipelines to identify anomalies, performance degradations, or failures related to data quality, logic defects, or infrastructure issues.
• Execute rapid troubleshooting and root-cause analysis followed by timely remediation, validation, and full regression testing prior to redeployment.
• Collaborate with Data Science, Engineering, and Product teams to operationalize machine learning models—including LLM-based and MCP-orchestrated systems—ensuring seamless integration into production environments.
• Develop CI/CD workflows, model deployment strategies, and automated testing frameworks to support reliable, repeatable releases.
• Implement and maintain observability tooling (logging, monitoring, alerting) to ensure high availability and traceability of ML systems.
• Manage and optimize cloud infrastructure across Azure and AWS for compute, storage, orchestration, and security needs.
• Create and maintain documentation, runbooks, and best practices for model operations and system maintenance.
• Perform all other job-related duties as assigned.

Machine Learning Operations Engineer

• Provide innovative and scalable solutions that better enable our clients to focus on patient care.
• Ability to complete all phases of software development life cycle including R&D, scoping, design, development, testing and support.
• Work closely with members of the product team to achieve the best user experience while writing high quality, scalable code.
• Own features/projects beginning to end from mockups and design to review and deployment.
• All other duties related to this position.