Freelancers using Helm
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Alexis Nieves
Denver, USA
Senior DevOps/SRE | AWS, Kubernetes & Terraform Expert
New to Contra
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Senior DevOps/SRE | AWS, Kubernetes & Terraform Expert
0
Architected and implemented a production-grade, fully automated DevOps platform on AWS, covering the entire software delivery lifecycle from code commit to live deployment. The platform integrates eight tightly coupled layers: a developer workflow built on Git, Docker Compose, and pull requests; a GitHub Actions CI/CD pipeline with dedicated workflows for continuous integration, deployment, Terraform provisioning, security scanning, and semantic releases; and a multi-tool security gate enforcing SAST, SCA, IaC scanning, container analysis, OWASP ZAP, and CodeQL checks before any artifact progresses. Infrastructure is provisioned as code using Terraform, deploying a multi-AZ VPC, an EKS cluster, ECR repositories, RDS MySQL, an ALB with WAF, and IAM OIDC integration on AWS. Applications are packaged with Helm Umbrella Charts and deployed to Kubernetes with Horizontal Pod Autoscaling (2–8 replicas) and RBAC-enforced NetworkPolicies. GitOps state management is handled by ArgoCD, providing continuous reconciliation, drift detection, auto-sync, and self-healing across all application sets. Observability is delivered through a dual-stack setup: a metrics pipeline (Prometheus → Grafana → Alertmanager → Slack) and a log aggregation pipeline (Filebeat → Logstash → Elasticsearch → Kibana). Releases are fully automated using Semantic Release with Conventional Commits, producing versioned GitHub Releases and Docker image tags without manual intervention.
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30
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Comparing AWS ECS and AWS EKS for Container Orchestration
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1
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Implementing Additional Checks for AWS Security
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Designed and developed a Command Line Interface (CLI) security tool that leverages the Google Gemini API (gemini-2.5-flash) to perform advanced, AI-driven vulnerability analysis on Python codebases. This tool acts as an automated security engineer, scanning source code to detect critical flaws before they reach production. The scanner parses Python files and evaluates them against a detailed security prompt to identify vulnerabilities such as SQL injection, hardcoded secrets (API keys and database passwords), weak cryptography (e.g., MD5 hashing), insecure deserialization, and improper input validation. It outputs a structured, color-coded terminal report assigning severity ratings (🔴 High, 🟠 Medium, 🟢 Low) to each finding. For every detected issue, the tool provides the vulnerability type, the exact line number, a concise explanation of the risk and potential impact, and actionable remediation advice with secure code fixes. The architecture is built on a lightweight Python foundation using a virtual environment for dependency isolation. It utilizes the google-generativeai SDK for model interaction and python-dotenv for secure environment variable management, ensuring API keys are never hardcoded. This project demonstrates the ability to integrate cutting-edge Large Language Models (LLMs) into traditional DevSecOps workflows, providing enterprise-grade security scanning capabilities directly within the developer's terminal.
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30
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Chidozie Uzoegwu
Newcastle upon Tyne, UK
Data/ML Engineer | AWS & Terraform | LLM/RAG & MLOps
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Data/ML Engineer | AWS & Terraform | LLM/RAG & MLOps
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PostgreSQL Deployment on AWS EKS for NHS
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15
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Cardiovascular Studies RAG System Development
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5
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Full-Stack To-Do App Development with React and AWS Amplify
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11
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React Setup in Vite with HMR
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5
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Tatiana Denel
Ramat Gan, Israel
DevOps, GCP, AWC, PCC, Docker, K8s, Terraform, CI/CDPipeline
8
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DevOps, GCP, AWC, PCC, Docker, K8s, Terraform, CI/CDPipeline
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High-Security DevOps Pipeline for a Financial Platform
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13
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Scalable Cloud Migration for a FinTech Platform
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11
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Multi-Region Disaster Recovery & High Availability Setup
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14
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Yasser Boukhers
Paris, France
CI/CD Specialist | Kubernetes, Docker & Jenkins Guru
$1k+
Earned
1x
Hired
2
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CI/CD Specialist | Kubernetes, Docker & Jenkins Guru
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High Availability Jenkins CloudBees Deployment Automation
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19
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Scalable Kubernetes Infra with Automated Canary Deployment
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17
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Infrastructure Automation with Advanced Ansible Techniques
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18
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Stanislav Stankov
Sofia, Bulgaria
Principal Product Manager
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Principal Product Manager
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SaaS Shipment Tracking System
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4
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AOL Communities PoC
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5
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PLG Data Driven Growth for B2B SaaS
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2
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Joshua Rotimi
Atlanta, USA
AI Output Evaluator & LLM Quality Specialists
New to Contra
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AI Output Evaluator & LLM Quality Specialists
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A sample LLM evaluation report analyzing AI responses for accuracy, reasoning quality, hallucinations, and failure patterns. Demonstrates structured testing and quality assessment workflows.
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Evaluated 60 multi-turn conversations from a retail support AI to track context retention, persona consistency, and task completion across longer exchanges. Found that context drops clustered around the third and fourth turn, pointing to a memory window limitation rather than random failures, and flagged each instance with the exact turn where context broke down.
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Ran 48 adversarial prompts against a production LLM to surface jailbreak vulnerabilities, role override attempts, and context manipulation before a public launch. Found 11 vulnerabilities including 3 critical, documented every failure with reproducible prompts, and delivered a prioritised risk report with fixes.
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Built a custom evaluation rubric for scoring AI customer support outputs across five weighted dimensions: factual accuracy, reasoning validity, instruction adherence, adversarial robustness, and format compliance. Each dimension includes plain-language scoring criteria so any team member can apply it consistently, no AI background required.
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20
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Gabe G
São Paulo, Brazil
DevOps engineer fixing CI/CD and cloud failures
New to Contra
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DevOps engineer fixing CI/CD and cloud failures
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Docker & Kubernetes Issues
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25
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AWS Deployment Fix
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24
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Terraform Debug
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28
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CI/CD Pipeline Failure Root Cause & Fix
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52
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Warintorn Tang
Bangkok, Thailand
Visualizing Complex IT & Database Solutions
New to Contra
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Visualizing Complex IT & Database Solutions
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Kong Hybrid Proof of Concept and Architecture Assessment : Supported a Kong Hybrid proof of concept covering control plane and data plane design, traffic flow, configuration flow, and target environment considerations for broader platform adoption.
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Technical Documentation and Migration Support : Prepared technical documentation, migration checklists, handover materials, and implementation summaries for infrastructure and database-related projects.
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AWS Aurora to Azure MySQL Migration : Participated in cross-cloud migration activities from AWS Aurora to Azure MySQL, including compatibility review, migration considerations, and target environment assessment.
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AWS EC2 to Azure VM MSSQL Migration : Supported cross-cloud migration activities for Microsoft SQL Server workloads from AWS EC2 to Azure VM. Reviewed workload compatibility, target architecture, and migration considerations for the target platform.
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46
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