AI Infrastructure Engineer (Senior Associate)
New
J
JobgetherAI infrastructure
Based in the United StatesFull-TimeSenior
SalaryEstimated annual base salary ranging from $120,000 to $165,000. Estimated total compensation, including incentive opportunities, ranging from $138,000 to $189,000.
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Job Details
- Experience
- At least 3 years of experience building and operating production cloud infrastructure or platform engineering solutions
- Required Skills
- AWSCI/CDRESTful APIs
Requirements
- Have at least 3 years of experience building and operating production cloud infrastructure or platform engineering solutions.
- Have hands-on exposure to AWS, automation, infrastructure as code, or production operations.
- Have experience defining, provisioning, and managing infrastructure through code and repeatable deployment processes.
- Have practical knowledge of cloud networking, IAM, secrets management, logging, monitoring, deployment automation, and operational support.
- Have software engineering or scripting skills for developing automation, infrastructure tooling, integration components, and operational utilities.
- Demonstrate practical use of AI tools for infrastructure development, code generation, debugging, testing, automation, and technical documentation.
- Be familiar with APIs, event-driven architectures, service integration, and secure deployment patterns.
- Be able to translate established architectural patterns and technical requirements into working systems.
- Understand production reliability, troubleshooting, documentation, and incident handling.
- Be able to work from a location within the United States and travel as needed.
- Preferred: Experience with Amazon Bedrock or other managed AI and model-hosting platforms.
- Preferred: Familiarity with token and cost telemetry, usage attribution, chargeback, showback, or FinOps data pipelines.
- Preferred: Knowledge of containerized or sandboxed execution environments, AI agent tools, MCP, model gateways, API gateways, or secure service-broker architectures.
Responsibilities
- Build, integrate, and operate production infrastructure supporting governed AI usage and approved model-access patterns, including Amazon Bedrock where applicable.
- Develop infrastructure-as-code solutions, deployment automation, reusable platform components, and CI/CD templates.
- Implement telemetry and data pipelines for token consumption, model usage, user and project attribution, quotas, cost tracking, and financial reporting.
- Deploy and maintain approved sandbox environments for coding agents and other tool-using AI agents.
- Build governed mediation and integration patterns for AI applications and agents, including MCP or equivalent approaches.
- Implement logging, monitoring, alerting, audit evidence collection, and operational reporting for AI workloads.
- Create onboarding templates, reference implementations, and reusable infrastructure components for teams adopting approved AI capabilities.
- Use AI tools to accelerate infrastructure coding, automation, debugging, test development, documentation, and runbook creation.
- Develop and maintain technical documentation, operational runbooks, support models, incident escalation procedures, and operational handoffs.
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