Senior AI Infrastructure Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop, integrate, and manage production platform capabilities that facilitate governed AI usage.

• Create and maintain approved model-access frameworks, including Amazon Bedrock wherever applicable.

• Establish infrastructure as code, automate deployments, and create CI/CD templates along with reusable platform components.

• Implement usage telemetry, token reporting, model usage analytics, user and project attribution, quotas, and cost-management data pipelines.

• Deploy and manage sandbox patterns for coding agents and tool-utilizing agents.

• Create governed mediation patterns for AI applications and agents, including MCP or equivalent methodologies.

• Implement logging, monitoring, alerting, audit evidence collection, and operational reporting mechanisms.

• Develop onboarding templates and reusable reference implementations for both internal and client-facing teams.

• Collaborate with the AI Capability Center, reporting to the Chief AI Officer, on infrastructure and platform components.

• Utilize AI tools to enhance infrastructure coding, automation, debugging, test creation, documentation, and runbook development.

• Define and maintain runbooks, support models, incident pathways, and operational transitions.

⛳️ Requirements

• A minimum of 3 years of experience in building and managing production cloud or platform infrastructure.

• Practical experience with AWS, infrastructure as code, automation, or production operations.

• Proficient in infrastructure as code practices.

• Experience in cloud networking, IAM, secrets management, logging, monitoring, deployment automation, and operational support.

• Software engineering or scripting expertise for automation and platform tooling.

• Capability to leverage AI tools for infrastructure automation, code generation, debugging, testing, or documentation purposes.

• Familiarity with APIs, event-driven architectures, service integration, and secure deployment methodologies.

• Ability to navigate ambiguity with guidance from senior engineers and architects, delivering functional systems.

• Preferred: Experience with Amazon Bedrock or alternative managed AI/model platforms.

• Preferred: Experience in token/cost telemetry, usage attribution, chargeback, showback, or FinOps data pipelines.

• Preferred: Experience with durable agent-based AI orchestration platforms.

• Preferred: Experience with containerized or sandboxed execution environments.

• Preferred: Familiarity with agent tools, MCP, model gateways, API gateways, or secure service broker patterns.

• Preferred: Experience supporting regulated, client-confidential, PHI, PII, or sensitive workloads.

• Willingness to travel as required.

🏝️ Benefits

• Annual incentive compensation program.

• Medical coverage.

• Dental coverage.

• Vision coverage.

• Wellness programs.

• Flexible living arrangements across the US.

• Travel as required.