Senior Devops Engineer-AWS & AI tool

Architecture & Builder Mode

·AWS solution architecture. Translate workloads and non-functional requirements into AWS architectures covering accounts, networking, compute, storage, data services, identity, security, observability, resilience, and cost. Maintain clear conceptual, logical, and physical deployment designs.

·Infrastructure as code. Design and implement reusable, version-controlled infrastructure using Terraform, AWS CDK, CloudFormation, or approved equivalents. Establish environment consistency, state management, code review, policy checks, and controlled promotion.

·Cloud-native platforms. Lead deployment of containerized and serverless workloads using services such as ECS, EKS, EC2, Lambda, API Gateway, and appropriate managed services. Select technologies based on workload needs, operational complexity, and cost.

··CI/CD and release engineering. Build secure, repeatable pipelines for application and infrastructure delivery. Own build, test, artifact, scanning, deployment, approval, rollback, and release automation patterns across environments.

··AI-DLC enablement. Use Claude Code, Codex, or comparable tools to accelerate IaC, pipeline development, scripting, documentation, and troubleshooting. Define safe agent permissions, review gates, and policies for AI-generated infrastructure changes.

·End-to-end platform delivery. Own platform workstreams from discovery and design through provisioning, integration, testing, production rollout, and operational handover. Coordinate with application, architecture, security, networking, QA, and customer teams.

Firefighter Mode

·A deployment fails before a customer milestone. You trace the pipeline, artifact, configuration, and infrastructure dependencies, restore a safe deployment path, and communicate the recovery plan.

·An application is unreachable or unstable in AWS. You investigate DNS, routing, security groups, IAM, load balancing, compute, and service telemetry to identify the cause and coordinate a verified fix.

·A production environment shows rising latency, error rates, or infrastructure cost. You use operational evidence to isolate the issue, implement appropriate scaling or optimization, and measure the result.

··An AI-generated Terraform or pipeline change introduces security or deployment risk. You block unsafe promotion, review the proposed changes, remediate the issue, and improve the automated guardrails.

Systems Thinker Mode

·Secure cloud foundations. Establish account and environment isolation, VPC/network design, least-privilege IAM, encryption, secrets management, logging, and approved connectivity. Partner with security and governance teams on policies and risk remediation.

·Reliability and operations. Design for availability, fault isolation, scaling, backup, recovery, and disaster recovery requirements. Establish SLOs where appropriate, monitoring, ing, runbooks, incident response, and tested recovery procedures.

·Platform standardization. Create reusable IaC modules, pipeline templates, container standards, environment baselines, and self-service patterns that reduce manual effort while preserving governance and traceability.

·Team enablement. Mentor DevOps and application engineers, review infrastructure designs and code, define ownership and operating procedures, and help teams adopt cloud and AI-DLC practices safely and independently.

·Delivery and cost accountability. Own technical dependencies, capacity, release readiness, and platform risks. Track deployment frequency, failure/recovery trends, infrastructure drift, service reliability, and cost; make optimization decisions using measurable evidence.

Minimum Qualifications

··Experience. Typically 7+ years in software engineering, cloud infrastructure, DevOps, or platform engineering, including at least 2 years leading technical delivery or cloud/platform architecture. Equivalent demonstrated experience will be considered.

··Education. Bachelor's degree in Computer Science, Software Engineering, Engineering, or a related field, or equivalent practical experience. A Master's degree is an advantage.

·AWS and DevOps expertise. Strong hands-on experience designing and operating production AWS environments, infrastructure as code, CI/CD, Linux, networking, security, containers, scripting, and operational troubleshooting.

·Leadership and delivery. Proven ability to guide engineers, own infrastructure and deployment decisions, coordinate with application and security teams, and deliver production platforms with clear operational accountability.

Technical Toolkit

We value demonstrated technical depth and the ability to learn adjacent technologies—not superficial familiarity with every tool listed below.

·AWS architecture and networking. AWS Organizations/Control Tower familiarity, IAM, VPC, subnets, routing, security groups, VPC endpoints, Transit Gateway or VPN/Direct Connect where applicable, Route 53, load balancers, and AWS networking/security fundamentals.

·Compute, containers and serverless. EC2, ECS/Fargate, EKS/Kubernetes, ECR, Lambda, API Gateway, autoscaling, and appropriate managed storage/data services such as S3, RDS, or DynamoDB. Strong Docker and container troubleshooting experience.

·Infrastructure and automation. Terraform, AWS CDK, CloudFormation, or comparable IaC; Bash and Python scripting; Git, reusable modules, environment/state management, infrastructure testing, and drift detection.

··CI/CD and DevSecOps. GitHub Actions, GitLab CI, Jenkins, AWS CodePipeline/CodeBuild, or comparable platforms; artifact management, automated testing, security scanning, policy-as-code, secrets handling, approvals, and deployment strategies.

··Security and operations. IAM least privilege, KMS, Secrets Manager, CloudTrail, CloudWatch, AWS Config, GuardDuty, Security Hub, or approved equivalents; observability, ing, incident response, backup/recovery, and cost optimization.

·Cloud-native architecture. High availability, disaster recovery, infrastructure resilience, service networking, event-driven integration, deployment patterns, and AWS Well-Architected principles. Familiarity with Bedrock, SageMaker, or AI workload infrastructure is an advantage.

· AI-first engineering. Claude Code, OpenAI Codex, GitHub Copilot, Cursor, or comparable tools; specification-driven infrastructure development, agent instructions/skills, approved tool access, context engineering, and human-verified automation.