AI Infrastructure Engineer

BlueCat; Toronto; On-site; CAD 160,000 - 180,000; Full time

Benefits offered by this job

Professional Development Budget

Dedicated Wellness Days

Lifestyle Spending Account

Employee Recognition Program

Job summary

BlueCat is seeking an AI Infrastructure Engineer responsible for building a production-grade platform for the BlueCat Horizon team. The role involves deploying and optimizing agentic infrastructure using technologies like Golang, AWS AgentCore, and Kubernetes.

Candidates are expected to have a Bachelor's degree in computer science or related fields and at least 10 years of software engineering experience. A competitive salary range of 160,000 - 180,000 CAD per year along with various benefits is offered.

Qualifications

• 10+ years of experience in software engineering with 5+ years in cloud distributed systems.
• Hands-on experience with AWS AgentCore or similar agentic AI platforms.
• 2+ years of hands-on proficiency in Kubernetes.

Responsibilities

• Deploy and optimize the AgentCore Runtime on Amazon EKS.
• Architect persistent state layers to ensure agent context maintenance.
• Build infrastructure for capturing agent execution traces.

Skills

Golang

Asynchronous Python

Kubernetes

AWS AgentCore

API Development

Education

Bachelor's degree in computer science or Engineering

Master's degree

Tools

Terraform

GitLab CI/CD

Job description

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 environment 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-account fashion.
• Provide the infrastructure support for Retrieval-Augmented Generation (RAG) systems, ensuring low-latency access to vector databases.
• Knowledge Graph Support: Support the integration of Knowledge Graphs into the agent reasoning loop to provide structured enterprise context.

Qualifications

• Bachelor’s degree in computer science, Engineering, or a related field; Master’s degree preferred.
• 10+ years' experience in software engineering with around 5+ years commercial experience in cloud distributed systems and high scale designs with Golang and async Python.
• Hands‑on experience with AWS AgentCore (or similar Agentic AI platforms), Agent SDK (Strand, OpenAI, LangChain), protocols (MCP, A2A).
• Agentic Expertise: Proven ability to move agents beyond "chat" into autonomous "action" loops (MCP, A2A, RAG, KnowledgeBase).
• Must have 2+ years hands‑on proficiency in Kubernetes, Kubernetes operators and containers.
• Experience with Helm charts, API gateways, ingress/egress gateways.
• You are passionate about building great REST APIs (and helping others do the same).
• Passion for engineering rigor and operational excellence (design principles and patterns, unit testing, best practices for security and privacy, CI/CD etc).
• Experience with CI/CD tools (GitLab) & automation.
• Strong experience with code tools like Terraform.
• Excellent written and verbal/presentation communication skills.
• Ability to work well with a distributed team.

This position offers a salary range of 160,000 - 180,000 CAD per year plus participation in a discretionary bonus plan. Final compensation will be based on skills, experience, and qualifications.

The role is for an existing vacancy.

Benefits

• Professional Development Budget.
• Dedicated Wellness Days and Wellness Week.
• Lifestyle Spending Account.
• Employee Recognition Program.