AI Platform Engineer

Cinteot seeks an AI Platform Engineer to build, harden and help operate a shared enterprise GenAI and agentic platform. The role focuses on platform foundations rather than individual AI use cases, enabling development teams to deploy agents at scale under consistent governance and controls. The position is listed as full-time and remote, with Newark, New Jersey, United States as its location.

Responsibilities

• Engineer and maintain the LLM gateway, model routing, shared compute and infrastructure, and platform governance controls. Onboard supported models and agent tools, and provision resources such as Amazon Bedrock Knowledge Bases and vector-backed retrieval components where applicable.
• Build Terraform or equivalent infrastructure-as-code automation and dashboards. Operate infrastructure and backend/frontend deployment pipelines, troubleshoot failures, and improve repeatability and reliability across environments.
• Support agent teams with platform-related deployment, agent creation, result-quality and conversation-memory issues. Monitor performance, quality and agent behavior through benchmarks and evaluation monitoring, including Bedrock Eval where applicable.
• Track platform budgets, usage and costs; provide reporting and optimization recommendations. Work with security, architecture and governance partners on enterprise-aligned controls, including access to agent creation capabilities.

Requirements

• A bachelor’s degree in computer science, engineering, information systems or a related technical discipline, or equivalent experience; experience designing and operating shared enterprise application or platform services.
• Experience with CI/CD, automation and infrastructure provisioning; knowledge of modern AI/ML or GenAI platforms and cloud services; and understanding of reliability, monitoring and support practices.
• Experience supporting AI, ML or GenAI platforms in regulated industries such as healthcare, insurance or financial services; familiarity with agent architectures and LLM integration; experience with cloud cost management, usage monitoring or FinOps; and professional cloud or AI-related certifications, such as AWS or Azure.

Benefits listed include flexible remote work, medical, dental, vision and life insurance, a 401(k) company contribution, paid time off and holidays, birthday PTO, and tuition reimbursement.