TRIMEDX is a company dedicated to serving clients and communities with care and performance. The Staff Development Operations Engineer role focuses on creating and delivering DevOps and MLOps solutions that support enterprise applications and AI/ML workloads, while leading platform-based initiatives and ensuring reliable delivery environments.
Responsibilities:
- Designs, develops, tests, and implements DevOps and MLOps solutions supporting CI/CD pipelines, infrastructure automation, and AI/ML lifecycle management
- Leads platform and foundational initiatives spanning multiple applications and environments
- Defines and applies standards, patterns, and best practices to ensure stability, scalability, and security
- Identifies and resolves complex system and performance issues impacting delivery and operations
- Serve as a leader within the DevOps team, providing guidance on design decisions and implementation approaches
- Leads architecture and design discussions, communicating solutions clearly to peers and partners
- Contributes to the definition of future-state platform capabilities and shared technical roadmaps
- Mentors and supports less-experienced engineers through knowledge sharing and technical guidance
- Provides support for complex production issues and escalations within area of expertise
- Supports release activities and ensures operational readiness for new and existing platforms
- Develops and executes validation and testing strategies for platform changes
- Balancing operational support with delivery of new capabilities across multiple concurrent initiatives
- Collaborates with engineering, data science, infrastructure, and security teams to deliver integrated solutions
- Participates in and contributes to design reviews, planning sessions, and cross-functional meetings
- Communicates technical concepts effectively to technical and non-technical stakeholders
- Documents design, standards, and decisions in a clear and consistent manner
- All other duties as assigned
Requirements:
- At least 5+ years of experience in DevOps, platform engineering, or related discipline is required
- Experience supporting AI/ML workloads in production environments (MLOps)
- Strong experience with CI/CD, cloud platforms, infrastructure-as-code, and automation
- Ability to manage multiple priorities and initiatives in a fast-paced environment
- Strong written and verbal communication skills
- Bachelor's degree in Computer Science, Engineering, or a related field is required, or equivalent experience