Senior Cloud / DevOps Engineer - USA

Cogniify•Scottsdale, AZ

110d•$115,000 - $130,000•Remote

About The Position

We’re looking for an experienced Senior Cloud Engineer who thrives in high-scale environments and enjoys working directly with clients to understand their needs. In this role, you’ll lead cloud infrastructure design and migration efforts, primarily on AWS, while building scalable Django-based applications. You’ll also engage closely with stakeholders to gather requirements and drive technical strategy from ideation to deployment. As a senior member of the team, you will act as a technical advisor to both internal teams and external stakeholders, champion engineering best practices, and ensure our cloud solutions are secure, cost-efficient, and production-ready.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
5+ years of experience in cloud engineering with a strong focus on AWS services (EC2, S3, RDS, Lambda, ECS, EKS, VPC, IAM, CloudFormation, Step Functions).
Proficiency in building and maintaining Django applications at scale, integrated with cloud-native services.
Hands-on experience with infrastructure automation tools like Terraform, Ansible, or AWS CloudFormation/CDK.
Proven ability to lead large-scale application or data migrations to the cloud.
Strong understanding of networking, security, and DevOps practices in cloud environments.
Experience interfacing with clients or business stakeholders for requirements gathering and technical discussions.
Deep knowledge of container orchestration (Docker, ECS, EKS, AKS), serverless architectures, and event-driven design patterns.
Experience designing highly available, fault-tolerant, and disaster-recoverable architectures.
Proven ability to mentor engineers, lead design reviews, and influence infrastructure direction.
Strong understanding of cloud security: IAM, WAF, GuardDuty, Security Hub, encryption, and compliance frameworks (SOC2, ISO 27001).

Nice To Haves

AWS Solutions Architect Professional, AWS DevOps Engineer Professional, or Azure Solutions Architect Expert certification.
Experience with multi-cloud or hybrid-cloud architectures spanning AWS and Azure.
Familiarity with platform engineering and internal developer platform concepts (Backstage, Port, Humanitec).
Experience with AI/ML infrastructure: SageMaker, Bedrock, Azure OpenAI, GPU cluster management, model serving (Triton, BentoML).
Experience with GitOps workflows (ArgoCD, Flux), progressive delivery (Argo Rollouts, Flagger), and canary deployments.
Knowledge of data engineering infrastructure: Airflow, dbt, Kafka, Kinesis, Snowflake, or Redshift on cloud platforms.
Experience with FinOps at scale: cost allocation, showback/chargeback models, and cloud financial governance.
Familiarity with chaos engineering practices (AWS Fault Injection Simulator, LitmusChaos, Gremlin).

Responsibilities

Architect and implement cloud infrastructure solutions on AWS for web applications and data platforms.
Lead end-to-end cloud migration projects, ensuring scalability, security, and minimal downtime.
Develop and maintain Django-based back-end systems integrated with cloud-native services.
Collaborate with clients to gather technical requirements and translate them into actionable engineering plans.
Implement CI/CD pipelines and infrastructure-as-code using tools like Terraform or CloudFormation.
Optimize cloud cost and performance through monitoring, automation, and continuous improvement.
Ensure high availability, security compliance, and disaster recovery readiness.
Act as a technical advisor to both internal teams and external stakeholders.
Design multi-account AWS architectures using AWS Organizations, Control Tower, and Service Control Policies for enterprise-grade governance.
Architect and manage Kubernetes clusters (EKS/AKS) with service mesh (Istio, Linkerd), auto-scaling, and multi-environment promotion strategies.
Lead infrastructure observability strategy using OpenTelemetry, Prometheus, Grafana, Datadog, or CloudWatch with custom dashboards and SLO-based alerting.
Design and implement platform engineering solutions including internal developer platforms, golden paths, and self-service infrastructure tooling.
Support deployment of AI/ML workloads on cloud infrastructure including SageMaker, Bedrock, Azure OpenAI, GPU instances, and model serving architectures.
Mentor junior and mid-level engineers, conduct architecture reviews, and drive knowledge sharing across the team.