Agent & DevOps Platform Engineer

Epsilon Solutions Canada — Canada · Posted ~3 hours ago

Senior Full-time Onsite

Skills

CI/CD Cloud engineering Platform engineering Python AWS AWS IAM Docker Kubernetes AI/LLM tools AI agents LLMOps Infrastructure automation API integration Amazon ECS Amazon EKS Java .NET Groovy Node.js LLM

🔓 Log in to save this job, tailor your resume & track your apply process — 7 days free, no card needed.

Log in to add to target list

Summary ✨ AI‑Generated

An onsite platform engineering opportunity for an experienced engineer combining DevOps, cloud infrastructure, and production AI agents. You will automate enterprise infrastructure, build CI/CD systems, operate containerized workloads, manage cloud identity and access, and develop or integrate LLM-powered tools using modern agent and LLMOps practices.

Highlights

Build enterprise-grade platform infrastructure and AI agent capabilities in a hands-on engineering role. The position combines cloud, automation, containers, security, CI/CD, and production AI/LLM systems, with substantial ownership of platform tooling and operational solutions.

Description

Agent & DevOps Platform Engineer Full Time Toronto, ON (Onsite) Required Skillsets: • 5+ years of hands-on CI/CD, cloud, and platform engineering experience in enterprise environments • Strong proficiency in Python for automation, API integrations, infrastructure tooling, agent services, and production scripting • Working experience with at least one additional language or ecosystem such as Java, .NET, Groovy, or Node.js • Hands-on AWS experience designing or operating production workloads • Practical knowledge of AWS IAM, including roles, policies, trust relationships, cross-account access, least privilege, and service-to-service authentication • Production experience building and deploying containers with Docker and a container platform such as Kubernetes, Amazon ECS, or Amazon EKS • Experience building or integrating AI/LLM-based tools or agents in production or near-production environments • Strong understanding of LLMOps concepts: prompt management, tool use, agent architectures, evaluation, observability, and reliability • Experience with Git-based workflows, build automation, and release pipelines at scale • Hands-on experience with Infrastructure as Code, configuration management, and cloud-native deployments • DevSecOps mindset — security is a design constraint, not a checklist item Good to have skills • Experience with AWS services such as EKS, ECS, ECR, Lambda, Bedrock, CloudWatch, S3, Secrets Manager, Systems Manager, and VPC • Experience with Terraform, CloudFormation, or AWS CDK • Experience designing multi-account AWS environments and implementing enterprise identity and access patterns • Familiarity with Kubernetes operations, Helm, service accounts, ingress, networking, and workload security • Experience integrating AI into developer platforms or enterprise tooling, rather than only building standalone applications • Prior work on agentic orchestration frameworks such as LangChain, LlamaIndex, or custom toolchains • Experience enabling DevOps practices across multiple teams or business units • Agile delivery experience using Scrum, Kanban, or SAFe Roles and Responsibilities • You build things and share them — your coaching is your working code, your pipelines, your agents, and your reusable platform patterns • You think in systems: you understand the downstream effects of cloud, identity, container, and automation decisions • You're comfortable in ambiguity and can define the right problem before solving the wrong one • You have strong opinions on automation, reliability, security, IAM, and operational simplicity — and can defend them with evidence • You learn fast, experiment deliberately, and know when to stop experimenting and ship • You understand that secure defaults, clear ownership, and good developer experience are essential to platform adoption