DevOps Architect (AWS)

Location: Remote in Toronto/North America

Company

hirify.global provides an agentic AI platform for enterprise customer experience, enabling global brands to automate customer journeys with scalable AI agents.

What you will do

• Design, build, and own scalable, secure, highly available, and cost-efficient AWS architectures for greenfield environments and migrations.
• Lead systems design across disaster recovery, multi-account strategy, networking, performance, resilience, and fault tolerance.
• Build Infrastructure as Code and establish standards using Terraform, AWS CDK, or CloudFormation.
• Architect and improve CI/CD pipelines, production automation, observability, incident response, and post-mortem practices.
• Embed security and compliance through least-privilege IAM, encryption, guardrails, and applicable SOC 2, ISO, or PCI controls.
• Lead client workshops and architecture reviews, explain trade-offs to technical and executive stakeholders, and mentor engineers.

Requirements

• 8+ years in DevOps, SRE, or cloud infrastructure roles, including 2+ years in an architect or technical lead capacity.
• Deep, hands-on AWS expertise across VPC networking, IAM and Organizations, EC2, ECS, Lambda, RDS, DynamoDB, S3, CloudWatch, and cost optimization; production environment design experience is required.
• Proven experience designing distributed systems for scale, resilience, and fault tolerance, with the ability to explain architectural trade-offs.
• Strong Python and Bash skills for automation, plus working proficiency in Java or Node.js.
• Regular practical use of AI assistants and coding agents, with the ability to verify their security, correctness, and cost implications.
• Experience leading client or stakeholder engagements, presenting architectures to leadership, managing expectations, and challenging technically unsound requests.
• Hands-on experience with Infrastructure as Code and containers/Kubernetes.

Nice to have

• AWS Certified Solutions Architect – Professional or DevOps Engineer – Professional certification.
• Kubernetes certification such as CKA or CKAD.
• Consulting or professional services background.
• Experience building AI/LLM capabilities into internal tooling or pipelines.
• Multi-cloud experience with Azure or GCP.

Culture & Benefits

• Full-time remote work in Toronto/North America.
• Opportunity to work on an agentic AI platform used by large global brands.
• Equal opportunity employment commitment and evaluation without regard to protected characteristics.