Location
Remote, United States
Workplace
Remote
Category
IT
IT Category
DevOps / SRE
Language
English
Posted
May 25, 2026
Last verified
June 10, 2026
JobGrid context
Role summary by JobGrid
Principal GenAI Platform Engineer (US) at pointclickcare: Remote, United States; IT; DevOps / SRE. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.
- Location and workplace: Remote, United States
- Role classification: IT, DevOps / SRE
- Source freshness: checked by JobGrid on 2026-06-10.
- Application path: candidates continue to the employer application page with non-personal referral tags.
The Team
This team will serve as the product owner for GenAI capabilities within PointClickCare, working closely with other engineering teams across the organization to identify, build and support generative AI solutions. This centralized team with deep specialization, closely integrated with key horizontal partners to ensure delivery of safe, scalable and high-impact AI Products
Job summary
The Principal GenAI Platform Engineer will focus on building the infrastructure that connects AI systems with existing products and will enable seamless delivery of AI-generated insights into agent workflows.
Key responsibilities.
- Design, build, and maintain the core infrastructure layer supporting GenAI products, including model gateways, prompt/versioning stores, vector databases, and LLM evaluation tools.
- Implement secure access controls and authentication mechanisms integrated by default into the AI platform components.
- Develop and manage observability, monitoring, and logging solutions for GenAI workloads and infrastructure.
- Collaborate closely with product and engineering teams to integrate GenAI infrastructure with agent frameworks, and downstream applications.
- Optimize infrastructure for scalability, high availability, cost efficiency for production workloads.
Qualifications & Skills
- Extensive experience building and maintain AI platform infrastructure, Kubernetes, and container security.
- Demonstrated expertise in observability, and monitoring frameworks, with a focus on real-time performance (i.e: experience with OpenTelemetry, MLFlow).
- Experience with AI infrastructure components such as vector databases, prompt/versioning stores, and AI IDEs.
Preferred experience
- Familiarity with vLLM, SGLang or similar framework to host LLM inference workloads.
- Experience with CI/CD pipelines and automation for AI model deployment and platform operations
- Strong knowledge of authentication and authorization frameworks integrated into AI platforms.
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