Job Description The BlueCat Horizon team is responsible for powering all BlueCat SaaS products. Our mission is to deliver BlueCat products on a reliable, fast, globally distributed, and cost-effective enterprise-grade cloud infrastructure. Central to this mission is our AI first strategy, as we fully embrace a product model where AI is integral to everything we create. The AI Infrastructure Engineer role is a high-impact, implementation-focused position centered on building a production-grade agentic platform for Horizon. You will be lead coder for our autonomous agent runtime, leveraging Amazon Bedrock AgentCore as the core framework and Kubernetes (EKS) as the orchestration engine. Key Responsibilities You will bridge the gap between "experimental agents" and "production systems." Your mission is to build the secure, scalable, and stateful infrastructure that allows agents to reason, access enterprise tools, and persist memory. You will spend the majority of your time writing Go for systems-level Kubernetes extensions and Python for the agentic framework logic. You will be working closely with the Architecture Team, driving architectural decisions to implementation and operation, interact with the product management team to understand the use-cases, requirements and develop and present technical solutions. Your work will directly impact the scalability, performance, and reliability of the BlueCat Horizon Platform, ensuring that it meets the demanding needs of the versatile AI Agentic Workloads. Responsibilities/Duties Runtime Implementation: Deploy and optimize the AgentCore Runtime on Amazon EKS,



ensuring agents have a secure, high-performance setting for long-running tasks. Secure Gateway Logic: Build the AgentCore Gateway using Go to mediate between autonomous agents and internal microservices, enforcing zero-trust security. State & Memory Management: Architect persistent state layers, ensuring agents maintain context across sessions or specialized vector stores. Platform Integration: Engineer the "connective tissue" between AgentCore and the Horizon Kubernetes platform, ensuring agents have native access to cluster resources and internal services. Standardized Tooling: Leverage the Model Context Protocol (MCP) to integrate diverse data sources and internal tools into the agent ecosystem. Secure Gateways: Build the "connective tissue" in Go or Python that allows agents to securely interact with enterprise APIs via the AgentCore Gateway. Evaluation: Design and implement automated evaluation frameworks to verify that Horizon agents are performing tasks accurately, safely, and within BlueCat's operational guardrails. Observability: Build the infrastructure to capture agent execution traces and user feedback, feeding it back into the evaluation pipeline to continuously improve agent reliability. Horizon-Specific Tooling: Build secure, high-performance interfaces in Go and Python that allow agents to interact with Horizon APIs, telemetry data, and configuration engines. IaC Mastery: Lead the implementation of Terraform or AWS CDK modules to deploy the full AgentCore stack (Identity, Memory, and Gateway) in a repeatable, multi-

📌 Ai Infrastructure Engineer (Toronto)
🏢 BlueCat
📍 Toronto