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Cogniify
India · remote · Salary not listed
At Cognify Analytics, we’re driven by a single belief: that data and AI should be accessible and transformative for every organization. Founded by a team of ex-Google and Meta technologists, we specialize in delivering cutting-edge analytics and cloud solutions to companies around the globe. Whether it’s deploying machine learning models, optimizing cloud infrastructure, or guiding enterprise migrations—our mission is to turn complex data challenges into real-world impact.
We’re seeking a Mid-Level Cloud/DevOps Engineer to independently design, build, and operate cloud infrastructure and DevOps workflows on AWS and Azure. In this role, you will own key infrastructure components end to end, drive CI/CD maturity, manage containerized and serverless workloads, and collaborate with development and data teams to ensure reliable, secure, and cost-optimized cloud operations. You will also support cloud migrations, build automation frameworks, and integrate AI-powered tools into operational workflows.
Design, provision, and manage production cloud infrastructure on AWS and Azure using Terraform, CloudFormation, CDK, Bicep, or Pulumi.
Build and maintain robust CI/CD pipelines for application and infrastructure deployments using GitHub Actions, GitLab CI, Jenkins, AWS CodePipeline, or Azure DevOps.
Deploy and manage containerized workloads on Amazon ECS, EKS, or Azure Kubernetes Service (AKS), including service mesh and auto-scaling configurations.
Implement serverless architectures using AWS Lambda, Step Functions, API Gateway, EventBridge, Azure Functions, and Logic Apps.
Support and execute cloud migration projects, ensuring scalability, security, and minimal downtime during transitions.
Develop and maintain Django-based and Python back-end applications integrated with cloud-native services such as RDS, DynamoDB, ElastiCache, S3, and SQS.
Implement infrastructure monitoring, alerting, and observability using CloudWatch, Azure Monitor, Prometheus, Grafana, Datadog, or OpenTelemetry.
Automate operational workflows using Python, Bash, Go, or PowerShell and build self-healing infrastructure patterns.
Enforce security best practices including IAM, VPC design, WAF, secrets management (Secrets Manager, Vault), encryption, and compliance controls.
Optimize cloud costs through reserved instances, savings plans, right-sizing, and FinOps practices.
Apply on source siteListed via Himalayas
Collaborate with development, data engineering, and ML teams to support application deployments, data pipelines, and AI/ML workloads.
Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
3–5 years of professional experience in cloud engineering, DevOps, or site reliability engineering with production responsibility.
Strong hands-on experience with AWS services (EC2, S3, RDS, Lambda, VPC, ECS/EKS, CloudFormation, IAM) and/or Azure services (VMs, AKS, App Service, Functions, ARM/Bicep).
Proficiency with infrastructure-as-code tools: Terraform (strongly preferred), CloudFormation, CDK, or Pulumi.
Experience building and managing CI/CD pipelines with GitHub Actions, GitLab CI, Jenkins, or cloud-native pipeline services.
Working knowledge of Docker, Kubernetes, and container orchestration in production environments.
Strong scripting skills in Python, Bash, or Go for automation and tooling.
Solid understanding of networking (VPC, subnets, load balancers, DNS, CDN), security (IAM, RBAC, encryption), and compliance in cloud environments.
Experience with monitoring and observability tools: CloudWatch, Prometheus, Grafana, Datadog, or equivalent.
Familiarity with Agile methodologies and collaborative development workflows.
AWS Solutions Architect Associate/Professional, AWS DevOps Engineer Professional, or AZ-104/AZ-400 certification.
Experience with Django or FastAPI application deployment on cloud infrastructure.
Familiarity with GitOps practices and tools (ArgoCD, Flux).
Experience with database management on cloud platforms: RDS, Aurora, DynamoDB, Azure SQL, Cosmos DB.
Exposure to AI/ML infrastructure: SageMaker, Azure ML, Bedrock, GPU instance management, or model serving pipelines.
Experience with event-driven architectures using Kafka, SQS/SNS, EventBridge, or Kinesis.
Knowledge of FinOps principles and cloud cost optimization strategies.
Join a team of industry veterans from Google, Meta, and top-tier tech companies.
Work on impactful, high-scale projects with leading global clients.
Enjoy a flexible, remote-first culture focused on innovation and excellence.
Competitive salary, equity options, and continuous learning opportunities.
Shape the future of cloud and AI infrastructure at a rapidly growing company.
Life & accidental insurance for additional protection.
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other protected characteristic.
Originally posted on Himalayas