Description

Beyond technical skills, we’re looking for someone who brings:

Ownership: You close the loop. You don’t just provision infrastructure, you monitor it, cost-optimize it, and improve it without being asked.

Comfort with Ambiguity: AI infrastructure is still being invented. You are energized by ambiguity and comfortable writing the runbook that didn’t exist before you joined.

Communication: Able to explain an IAM boundary decision or a rate-limiting architecture to an AI engineer or a business stakeholder equally well.

Security and Governance Mindset: You think about what happens when things fail, when costs spike, when an agent calls an endpoint it shouldn’t. You build guardrails proactively.

Requirements

As an AI Systems Engineer, you will own the infrastructure, deployment, and reliability of production-grade agentic AI systems that power the next

generation of intelligent automation at project. Reporting to the General Head of AI Strategy, Policy, and Governance, you will operate at the intersection of cloud infrastructure engineering and AI systems,



provisioning, securing, and scaling the AWS environments that make our AI pipelines run reliably and cost-efficiently.

What makes this role interesting?

Frontier Stack: Work directly with AWS Bedrock AgentCore, a capability that most cloud engineers are only beginning to encounter. You’ll be among the first teams operationalizing it in production.

High Impact: Small team, direct line to executive leadership, real decisions.

Here’s how you’ll be making an impact:

IaC and Cloud Provisioning: Design and maintain infrastructure-as-code (Terraform) for all AI workloads: Bedrock agents, AgentCore runtimes, Lambda functions, API Gateway endpoints, and supporting data services.

AWS Bedrock AgentCore: Own deployment, configuration, and scaling of AWS Bedrock AgentCore environments, including model invocation routing, session management, and memory backends.

Security and IAM: Architect secure, least-pri

📌 Senior AI Engineer0 (Lima)
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📍 Lima