Muhammad Huzaifa S.

𝗦𝗲𝗻𝗶𝗼𝗿 𝗔𝗪𝗦 & 𝗚𝗖𝗣 𝗗𝗲𝘃𝗢𝗽𝘀 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 | 𝗧𝗲𝗿𝗿𝗮𝗳𝗼𝗿𝗺 | 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 | 𝗖𝗜/𝗖𝗗 | 𝗔𝗜/𝗟𝗟𝗠𝗢𝗽𝘀 I stand behind my work with a 100% satisfaction guarantee. If I do not meet the agreed expectations, I will refund my fee for the work completed. Build faster, scale confidently, and reduce cloud costs with secure AWS and Google Cloud infrastructure built for production and AI workloads. With 8+ years of hands-on experience in DevOps, cloud architecture, Kubernetes, Infrastructure as Code, security, observability, and AI infrastructure, I help startups, SaaS companies, and enterprise teams build reliable, scalable, and cost-efficient platforms. 𝗛𝗼𝘄 𝗜 𝗖𝗮𝗻 𝗛𝗲𝗹𝗽 • AWS and Google Cloud architecture • Terraform and Infrastructure as Code • Kubernetes, Amazon EKS, GKE, ECS, Fargate, and Cloud Run • Docker containerization and cloud migrations • CI/CD with GitHub Actions, GitLab CI, Jenkins, CodePipeline, and Cloud Build • AI/ML infrastructure, LLMOps, model deployment, and AI observability • Cloud security, IAM, networking, secrets, and compliance • Monitoring, logging, alerting, and incident response • AWS, GCP, Kubernetes, and AI cost optimization • Backup, high availability, and disaster recovery • SOC 2, CIS Benchmark, and NIST-aligned controls 𝗔𝗪𝗦 & 𝗚𝗖𝗣 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲 AWS: EC2, S3, RDS, Aurora, VPC, Lambda, API Gateway, CloudFront, Route 53, IAM, EKS, ECS, Fargate, DynamoDB, CloudWatch, CloudTrail, GuardDuty, Inspector, WAF, KMS, Secrets Manager, AWS Backup, Organizations, and Control Tower. GCP: Compute Engine, GKE, Cloud Run, Cloud Functions, Cloud SQL, Cloud Storage, VPC, Load Balancing, Cloud DNS, IAM, Secret Manager, Artifact Registry, Cloud Build, Cloud Deploy, Cloud Monitoring, Cloud Logging, Pub/Sub, BigQuery, and Cloud Armor. I design multi-account and multi-project environments, private networks, highly available architectures, container platforms, serverless systems, automated deployments, and production monitoring. 𝗔𝗜, 𝗠𝗟𝗢𝗽𝘀 & 𝗟𝗟𝗠𝗢𝗽𝘀 I help teams deploy and operate AI applications securely and reliably across AWS and GCP, including: • LLM and AI application infrastructure • Model and API deployment • GPU-enabled and containerized AI workloads • Vector databases and retrieval pipelines • Token usage, latency, performance, and cost monitoring • Identity, secrets, and network security for AI services • Model routing and Dev, Staging, and Production segregation • CI/CD and observability for AI services My focus is practical AI operations: reliable deployments, controlled access, measurable usage, strong monitoring, and predictable costs. 𝗧𝗲𝗿𝗿𝗮𝗳𝗼𝗿𝗺, 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 & 𝗖𝗜/𝗖𝗗 I create reusable, version-controlled infrastructure using Terraform, CloudFormation, Ansible, AWS CDK, AWS CLI, gcloud CLI, Python, and Boto3. I can develop Terraform modules, review existing code, fix state issues, configure remote backends, and establish controlled workflows for Development, Staging, and Production. I deploy workloads on EKS, GKE, ECS, Fargate, and Cloud Run using Docker, Kubernetes, Helm, Karpenter, autoscaling, ingress controllers, load balancers, and secure secrets management. My CI/CD pipelines include automated testing, security scanning, container builds, Terraform plans, approval gates, deployments, rollback procedures, and notifications. 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆, 𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆 & 𝗖𝗼𝘀𝘁 I implement least-privilege IAM, secure networking, encryption, secrets management, vulnerability scanning, audit logging, WAF controls, private connectivity, and compliance evidence collection. I work with CloudWatch, Cloud Monitoring, Prometheus, Grafana, ELK, OpenSearch, Fluent Bit, Sentry, and distributed tracing. I optimize compute, Kubernetes resources, databases, storage, networking, logging, idle services, autoscaling, Savings Plans, Reserved Instances, Spot workloads, and committed-use discounts. 𝗦𝗲𝗹𝗲𝗰𝘁𝗲𝗱 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 • Built highly available Kubernetes platforms with automated deployments and monitoring. • Migrated applications and workloads to AWS and GCP. • Developed Terraform infrastructure for multi-environment deployments. • Implemented centralized logging, alerting, and security monitoring. • Designed backup, failover, and disaster recovery solutions. • Reduced cloud and AI costs through right-sizing, autoscaling, and architecture improvements. 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 AWS Certified Solutions Architect – Professional AWS Certified DevOps Engineer – Professional AWS Certified Developer – Associate Certified Kubernetes Administrator (CKA) Microsoft Specialist – Implementing Microsoft Azure Infrastructure Solutions Send me an invitation with your AWS, GCP, Kubernetes, DevOps, or AI infrastructure challenge. I will review your requirements and recommend the most practical next steps.