DevOps Architect

Responsibilities:

Design scalable, secure, and cost-efficient AWS architectures for greenfield builds and migrations, and defend those designs to technical and non-technical stakeholders.
Lead systems design decisions covering high availability, disaster recovery, multi-account strategy, network topology, and performance at scale.
Build and maintain Infrastructure as Code (Terraform, AWS CDK, or CloudFormation) and set standards for its use across teams.
Architect and improve CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline).
Write production-grade automation and tooling in Python and Bash, and contribute to Java/Node.js services where needed.
Use AI coding and assistant tools (Claude, ChatGPT, Codex, Copilot, etc.) to speed up IaC, scripting, documentation, and troubleshooting, and critically review AI-generated output for security, correctness, and cost implications.
Lead client-facing workshops, architecture reviews, and technical discussions. Translate business requirements into technical solutions, and explain trade-offs clearly.
Implement observability (CloudWatch, Datadog, or similar) and drive incident response and post-mortem practices.
Embed security and compliance into infrastructure (IAM least privilege, encryption, guardrails, SOC 2 / ISO / PCI as applicable).
Mentor engineers and raise the technical bar of the team.

Requirements:

8+ years in DevOps, SRE, or cloud infrastructure roles, including 2+ years in an architect or technical lead capacity.
AWS (Proficient): Deep, hands-on expertise across core domains: VPC networking, IAM and Organizations, EC2/ECS/Lambda, RDS/DynamoDB/S3, CloudWatch, and cost optimization. You’ve designed production environments, not just deployed into them.
Systems Design (Proficient): Proven record of designing distributed systems for scale, resilience, and fault tolerance. You can whiteboard an architecture and explain every trade-off.
Scripting & Programming (Intermediate–Advanced): Strong in Python and Bash for automation; working proficiency in Java or Node.js.
AI Tooling (Intermediate–Advanced): Regular, practical use of AI assistants and coding agents in your engineering workflow. You know where they speed things up, where they fail, and how to verify their output.
Client Communication (Proficient): Experience leading client or stakeholder engagements, presenting architectures to leadership, managing expectations, and pushing back when a request is technically unsound.
Hands-on experience with Infrastructure as Code and containers/Kubernetes.

Nice to Have:

AWS Certified Solutions Architect – Professional or DevOps Engineer – Professional
Kubernetes certifications (CKA/CKAD)
Consulting or professional services background
Experience building AI/LLM capabilities into internal tooling or pipelines
Multi-cloud exposure (Azure/GCP)