Sr Platform Engineer (remote)

Platform Engineer

At Spacelabs Healthcare, you make a difference.

Every member of our worldwide team plays an integral role in improving treatment and helping providers deliver exceptional care to their patients. From newborns to centenarians, more than 60 million people benefit each year from the advancements we make in patient monitoring and management, care coordination, and clinical decision support.

Driven by the belief that anyone who seeks care could be a member of our own family, our team is dedicated to solving the greatest challenges the healthcare system currently faces, including the need to enhance the patient experience, improve population health, reduce costs, support care team well-being and advance health equity. As part of our mission, we take pride in creating services and technologies that are personalized and tailored to support the needs of healthcare providers anywhere in the world.

Because while we may not be at a patient’s bedside, their health is still in our hands.

Under minimal supervision, the Platform Engineer works with the Spacelabs Cloud Services division. The work requires collaboration with software developers, system operators, quality assurance, and support staff in identifying production issues, deploying product updates, and implementing real-time fixes to customer issues. The Sr Platform Engineer will partner with clinical experts and Software Engineers to design and operationalize AI-driven capabilities, leveraging LLMs and cloud-based machine learning services to enhance telemetry monitoring and other critical systems. The Sr Platform Engineer is expected to be able to resolve approximately 90% of inbound technical inquiries without escalation to a Level 4 Engineer. Must participate in an on-call rotation as scheduled and must perform after-hours support. Compliance with all company policies, procedures, and guidelines is essential at all times.

Responsibilities

• Work with AWS Bedrock to integrate, deploy, and operationalize LLM-based services such as Claude and other foundation models.
• Ensure AI systems comply with regulatory, privacy, and security requirements within healthcare and telemetry monitoring environments.
• Build, optimize, and maintain machine learning inference pipelines using Amazon SageMaker and other AWS AI services.
• Implement monitoring, logging, and cost-optimization strategies for AI workloads running on SageMaker, Bedrock, and containerized environments.
• Develop automation around model versioning, model deployment, dataset management, and CI/CD for ML workflows.
• Troubleshoot performance issues in LLM endpoints, SageMaker endpoints, embedding generation, and vector retrieval services.
• Effectively manage and assign projects as necessary while lending continuous support to the team with a good amount of availability.
• Responds timely and effectively to all system alerts and outages.
• Continuously evaluate existing systems with industry standards and make recommendations for improvement.
• Work closely with subject matter experts to interpret requirements and translate them into software solutions.
• Work closely with global tech support in the identification and resolution of production issues.
• Participate in technical meetings with the client's technical specialists.
• Assist Technical agencies with troubleshooting any performance issues (either database or with the application/API’s) or system failure.
• Researches and resolves cases in the production support queue.
• Provide visibility into business and systems performance metrics, in support of capacity planning and business reports.
• Analyze information to determine, recommend, and plan the installation of a new system or modification of an existing system.
• Coordinates the definition of processes and standards related to production functions.
• Coordinates the research and troubleshooting of production issues.
• Coordinates in the planning and execution of strategic architecture changes.
• Stays current on and evaluates the potential use of new technologies in production.
• Upholds Spacelabs values of Customer Obsession, Ownership Mindset, and Superior Results.
• Uphold the company’s core values of Integrity, Innovation, Accountability, and Teamwork.
• Demonstrates behavior consistent with the Company’s Code of Ethics and Conduct.
• It is the responsibility of every Spacelabs Healthcare employee to report to their manager or a member of senior management any quality problems or defects for corrective action to be implemented and to avoid recurrence of the problem.
• Duties may be modified or assigned at any time to meet the needs of the business.

Qualifications

• Bachelor’s degree in Computer Science or equivalent experience; additional combination of relevant experience and education may substitute.
• 8+ years’ relevant DevOps / SRE experience required.
• Familiarity with Software management, development, and build frameworks, including Jenkins, Maven, Git/SVN, GitHub, and common IDEs.
• FDA-regulated industry and medical device experience preferred.
• Has worked in an Agile Development environment using tools like JIRA, Confluence, and has been a member of Scrum teams.
• Experience integrating AI/ML systems into production SaaS or healthcare platforms, preferred.
• Understanding of AI model lifecycle management, security considerations, and healthcare compliance constraints.
• Ability to create CI/CD pipelines for machine learning workflows and automate AI service deployment. Experience in the deployment of complex high-availability applications.
• Strong experience with Linux-based infrastructures, Linux/Unix administration, and AWS.
• Able to work, influence, and lead in a highly cross-functional team environment.
• Excellent communication and negotiation skills, for both internal and external audiences, at all levels.
• Takes a logical, analytical approach to problem solving and pays close attention to detail.
• Self-motivated and results-oriented.
• Demonstrates strong focus on quality delivery and delighting customers; holds self to high standards of delivery.
• Strong team player; able to work effectively within a team and more broadly with people from a variety of backgrounds and areas across the organization.
• Ability to work in various time zones.