AI Infrastructure Engineer; Senior Associate

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for an AI Infrastructure Engineer (Senior Associate) based in the United States.

The AI Infrastructure Engineer will build and operate secure, scalable infrastructure that enables the reliable and responsible use of artificial intelligence across the organization. This role focuses on cloud and platform engineering, translating approved architectures into production-ready solutions that support AI models, intelligent agents, and enterprise integrations. Working closely with senior architects and cross-functional technology teams, you will develop automation, infrastructure-as-code solutions, deployment pipelines, and governance capabilities.

You will also help establish monitoring, usage tracking, cost management, and operational controls to ensure AI workloads remain secure, observable, and efficient. The position combines hands‑on engineering with emerging AI technologies in a collaborative, fast‑evolving environment. This is an excellent opportunity for an infrastructure professional who enjoys practical problem‑solving and wants to contribute to the foundations of enterprise AI adoption.

• AI Infrastructure Development:
  Build, integrate, and operate production infrastructure supporting governed AI usage, working with approved architectures and model‑access patterns, including Amazon Bedrock where applicable.
• Infrastructure as Code and Automation:
  Develop infrastructure-as-code solutions, deployment automation, reusable platform components, and continuous integration and delivery (CI/CD) templates to improve consistency, reliability, and scalability.
• AI Usage Monitoring and Cost Management:
  Implement telemetry and data pipelines for token consumption, model usage, user and project attribution, quotas, cost tracking, and financial reporting to support transparency and effective resource management.
• Agent Execution Environments:
  Deploy and maintain approved sandbox environments for coding agents and other tool‑using AI agents, ensuring secure execution and appropriate operational controls.
• Secure Service Integration:
  Build governed mediation and integration patterns for AI applications and agents, including Model Context Protocol (MCP) or equivalent approaches, following established architectural and security requirements.
• Observability and Operational Readiness:
  Implement logging, monitoring, alerting, audit evidence collection, and operational reporting for onboarded AI workloads. Help ensure systems are supportable, traceable, and aligned with enterprise requirements.
• Reusable Platform Solutions:
  Create onboarding templates, reference implementations, and reusable infrastructure components that enable teams across AI delivery, enterprise IT, analytics, engineering, consulting, and internal operations to adopt approved AI capabilities efficiently.
• Cross‑Functional
  
  Collaboration:
  
  Partner with AI platform leadership and multidisciplinary teams to deliver the infrastructure and platform components that support internal business solutions and client‑facing initiatives.
• AI‑Assisted Engineering:
  Use AI tools to accelerate infrastructure coding, automation, debugging, test development, documentation, and runbook creation while maintaining appropriate quality and security standards.
• Documentation and Support:
  Develop and maintain technical documentation, operational runbooks, support models, incident escalation procedures, and operational handoffs to ensure reliable ongoing service delivery.

• Professional
  
  Experience:
  
  At least 3 years of experience building and operating production cloud infrastructure or platform engineering solutions, with hands‑on…