Original listing text, shown exactly as published by the company.
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
