Principal AI/ML Platform Engineer (US)

United StatesRemoteFull-Timelead

Data ScienceOtherDevOps & InfrastructurePlatform EngineerMl Platform EngineerAi Platform EngineerInfrastructure & Cloud

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Quick Summary

Overview

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.

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.

Technical Tools

kubernetesci-cd

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 AI/ML 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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