DevOps Architect

Accountabilities: Design scalable, secure, and cost-efficient AWS architectures for new environments and cloud migrations, presenting and justifying architectural decisions to technical and non-technical stakeholders. Lead systems architecture decisions involving high availability, disaster recovery, multi-account strategies, network topology, performance, and resilience. Build, maintain, and establish standards for Infrastructure as Code (IaC) using Terraform, AWS CDK, or CloudFormation. Design, optimize, and maintain CI/CD pipelines using tools such as GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline. Develop production-grade automation scripts and engineering tools using Python and Bash, contributing to Java or Node.js services when required. Integrate AI coding assistants and tools, such as Claude, ChatGPT, Codex, and Copilot, into engineering workflows to accelerate infrastructure development, scripting, documentation, and troubleshooting. Critically evaluate AI-generated outputs to ensure security, technical correctness, reliability, and cost efficiency. Lead client-facing workshops, architecture reviews, and technical discussions, translating business requirements into practical solutions and clearly explaining technical trade-offs. Implement observability solutions using CloudWatch, Datadog, or similar platforms, while strengthening incident response and post-mortem practices. Embed security and compliance into infrastructure through least-privilege IAM policies, encryption, security guardrails, and relevant standards such as SOC 2, ISO, and PCI. Mentor engineers, share architectural expertise, and establish high technical standards across the team. Requirements: 8+ years of experience in DevOps, Site Reliability Engineering (SRE), or cloud infrastructure roles, including at least 2 years in an architecture or technical leadership position. AWS expertise: Deep, hands-on knowledge of core AWS services and domains, including VPC networking, IAM and Organizations, EC2, ECS, Lambda, RDS, DynamoDB, S3, CloudWatch, and cloud cost optimization. Proven experience designing and building production-grade cloud environments, rather than simply deploying applications into existing infrastructure. Systems design: Strong experience designing distributed systems for scalability, resilience, and fault tolerance, with the ability to explain architectural decisions and trade-offs. Scripting and programming: Strong Python and Bash skills for automation, alongside working proficiency in Java or Node.js. AI tooling: Practical, regular use of AI assistants and coding agents in engineering workflows, with the ability to assess their limitations and validate generated outputs. Client communication: Experience leading client or stakeholder engagements, presenting architectures to senior leadership, managing expectations, and challenging technically unsound requirements when necessary. Hands-on experience with Infrastructure as Code and container technologies, including Kubernetes. Strong technical leadership, problem-solving, communication, and mentoring skills. Nice to have: AWS Certified Solutions Architect – Professional or AWS Certified DevOps Engineer – Professional. Nice to have: Kubernetes certifications such as CKA or CKAD. Nice to have: Background in consulting or professional services. Nice to have: Experience integrating AI or large language model (LLM) capabilities into internal tools or engineering pipelines. Nice to have: Exposure to multi-cloud environments, particularly Azure or Google Cloud Platform (GCP). Benefits: Full-time employment. Fully remote work arrangement. Opportunity to work on enterprise-scale cloud infrastructure and advanced AI-enabled engineering workflows. Inclusive workplace committed to equal employment opportunities and diversity.