Job Description
Our client, a global leader in claims management and the largest third-party administrator (TPA) in the world, is actively looking for an AI/ML Platform Engineer to join their team! This is a 100% remote opportunity however working hours will be CST.
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***This is a contract-to-hire position with excellent potential for long-term growth!***
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This is a greenfield opportunity to help a $21 billion organization build its enterprise AI platform and leverage Generative AI to improve customer experience and streamline claims and managed care operations. Working under a Principal AI Engineer, you’ll build and deploy production-ready AI agents, workflows, and applications while collaborating directly with end users to solve real business problems.
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Responsibilities
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- Build and maintain the shared platform used to develop, deploy, and operate AI applications.
- Design CI/CD pipelines for AI applications, APIs, containers, models, and agents.
- Establish standardized deployment, environment, configuration, and release-management patterns.
- Implement monitoring, logging, tracing, alerting, and AI observability.
- Build and operate automated AI evaluation and quality-monitoring pipelines.
- Monitor model usage, token consumption, infrastructure cost, latency, and performance.
- Manage container, dependency, infrastructure, and application vulnerability remediation.
- Implement platform security, secrets management, access controls, and operational standards.
- Support production operations and reliability across all AI projects.
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Required Skills & Experience
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- 5+ years of DevOps, Cloud Engineering, Platform Engineering, MLOps, SRE, or related experience.
- Strong hands-on experience with Azure, AWS, or GCP cloud platforms.
- Experience with Docker, Kubernetes or equivalent container orchestration, and cloud-native deployments.
- Strong experience designing and managing CI/CD pipelines and automated release processes.
- Experience with infrastructure-as-code using Terraform, Bicep, CloudFormation, or similar technologies.
- Strong scripting and automation skills using Python, PowerShell, Bash, or equivalent.
- Experience implementing application and infrastructure monitoring, logging, tracing, alerting, and production observability.
- Strong understanding of secrets management, configuration management, identity/access controls, and platform security.
- Experience with vulnerability scanning, container security, dependency management, patching, and remediation processes.
- Understanding of production troubleshooting, incident management, performance optimization, and application reliability.
- Knowledge of MLOps/LLMOps, AI gateways, AI evaluation pipelines, LLM observability, model/prompt versioning, and AI cost management is preferred.
- Experience with Azure DevOps, GitHub Actions, Jenkins, or similar engineering platforms is a plus.
- Ability to build reusable platform capabilities and operational standards supporting multiple AI development teams.
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