MarkiTech - 3 Jobs
Toronto, ON
Job Details:
What you will do:
- Roadmap & standards: Define and socialize DevOps priorities (security, reliability, cost, velocity). Align teams on AWS Well-Architected practices, tagging, guardrails, and repeatable patterns for networking, identity, secrets, and data.
- AI adoption for infra & platform: Drive a pragmatic AI strategy for the team—e.g. standards for AI-assisted IaC and pipeline changes (review gates, testing, drift detection), documentation and runbook quality, incident summarization and triage workflows where appropriate, and guardrails so AI tooling fits regulated or high-stakes environments. Stay current on vendor and open-source options; pilot, measure, and roll out what actually reduces toil.
- Infrastructure as code: Design, review, and implement changes using Terraform and Terragrunt, with clear module boundaries, environment- specific config, and safe promotion across dev → non-prod → production.
- EKS (critical): Build, operate, and own the Kubernetes platform on AWS —cluster lifecycle (creation, upgrades, patching), node groups / capacity, networking (CNI, service mesh or ingress as used), security (RBAC, admission controls, pod security, secrets and IRSA), add-ons, and cost/ reliability tuning. Partner with app teams on standards for workloads, namespaces, and safe rollouts; be the escalation point for cluster-level incidents.
- Broader AWS platform: Operate and improve adjacent services—e.g. RDS/Aurora, DynamoDB, object storage and CDN, KMS, Secrets Manager, SNS (alerting), Lambda, EventBridge, and CI/CD (CodePipeline / CodeBuild, connections to source control)—plus IAM, VPC, and multi-tenant or multi-namespace patterns where applicable.
- Release engineering: Partner with development teams on release processes, deployment strategies, change management, rollbacks, and post-release verification in regulated or high-stakes environments (e.g. healthcare-adjacent workloads).
- Production support: Participate in on-call or escalation rotation as defined by the team; troubleshoot incidents, drive root-cause analysis, and implement preventive fixes (runbooks, dashboards, alarms, automation).
- Observability & operations: Improve monitoring, logging, tracing, and alerting; tune thresholds; reduce noise; document operational procedures.
- Collaboration: Work with security, architecture, and engineering leads to implement least-privilege access, encryption, backup/DR posture, and audit-friendly operations—including how AI-assisted workflows meet security and audit expectations.
- 6+ years in software / systems / DevOps / SRE roles, including 4+ years focused on AWS in production.
- Strong command of infrastructure as code (Terraform) and modular, environment-driven layouts (experience with Terragrunt or similar composition patterns is a plus).
- Deep, mandatory expertise in Amazon EKS: You have prior experience building and owning Kubernetes on AWS—not only deploying applications to a shared cluster. We expect fluency across the stack: cluster design and lifecycle, upgrades and patching, networking (VPC/CNI, DNS, ingress), identity and security (RBAC, IRSA, secrets, guardrails), observability, capacity and performance, and production troubleshooting. Surface-level or “I've used kubectl” experience is not sufficient.
- Solid grasp of CI/CD, artifact promotion, secrets injection, and safe change practices in multi-environment pipelines.
- Experience with production incidents: triage, communication, RCAs, and durable remediation.
- Demonstrated interest or experience in applying AI to DevOps/platform work (e.g. AI-assisted coding and review workflows for IaC, internal tooling, or operational documentation)—with judgment about limits, verification, and risk in production systems.
- Ability to influence without authority: written standards, design reviews, and roadmap proposals that engineering teams actually adopt.
- Excellent communication skills; comfortable working with distributed teams and stakeholders outside pure engineering. Preferred:
- AWS certifications (e.g. Solutions Architect Professional, DevOps Engineer) or equivalent demonstrated depth.
- Kubernetes certifications (e.g. CKA, CKS) or equivalent evidence of advanced Kubernetes/EKS depth.
- Experience with Helm / Helmfile, policy-as-code, or cluster baseline tooling.
- Familiarity with PostgreSQL/RDS, multi-tenant data patterns, or regulated-industry constraints.
- Experience shaping SLOs, error budgets, or platform KPIs.
- Exposure to cost optimization (rightsizing, scheduling non-prod, storage lifecycle) and FinOps collaboration.
- Hands-on experimentation with AI coding assistants, internal LLM or RAG patterns for ops knowledge, or evaluating vendor tools for the platform team.
This is a Hybrid role.