Technical Task: Setup CI/CD Pipeline with AI-Automation & Security Layer
Goal: Expand the infrastructure for the project (Python/FastAPI + JS) and automate the code review process using LLM (AI agents) with a focus on security and Multi-tenancy.
1. Stage: Infrastructure Setup (The Core)
• Version Control: Set up a private repository on GitHub. Configure branch protection rules so that code does not enter main without review.
• Environment Management: Move all sensitive data (API keys, DB credentials, Proxy settings) to GitHub Secrets and .env files. Zero hardcoded secrets policy.
• Documentation Hub: Deploy Notion (or Linear) as the central task manager and knowledge base.
2. Stage: AI-Pipeline Automation (The Synergy)
It is necessary to implement an automatic chain (via GitHub Actions):
1. Trigger: The developer creates a Pull Request or makes a push.
2. Action: The system extracts the code differentiation (diff) and sends it via API to LLM (Claude 3.5 Opus / GPT-4o).
3. AI Analysis (Security & Architecture):
• Audit for leakage of server IP/domains in frontend code.
• Check the logic of header masking (Fingerprinting spoofing).
• Control the presence of tenant_id in all new DB models and Redis queries.
4. Reporting: The result of the review is automatically published in Notion and as a comment to the Pull Request in GitHub.
3. Stage: Security & Risk Management
• Least Privilege Access: Configure access so that the AI operator does not have access to "live" user databases.
• Isolation: Set up Staging (test) and Production servers. Automatic deployment to Production is only possible after an APPROVED status from the AI agent and manual approval from the owner.
• Audit Log: All actions with code and access to servers must be logged.
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1 day334 USD
1 day334 USD
✋ Hello! We are the IT company dZENcode.
We are implementing a CI/CD pipeline on GitHub Actions with LLM code review (GPT-4o/Claude), secure secret management, multi-tenancy checks, reports in Notion, staging/production isolation, and audit logging, relying on the team's experience, best practices, and our own developments.
Has a GitHub organization and a private project repository already been created?
Which LLM provider will we choose for the API — OpenAI or Anthropic?
You can find detailed information about our services and rates on our website:
Freelancehunt.
Take a look – we will discuss the work details further, write when you are ready.
…
The final cost is determined only after clarifying the scope and requirements.
___________________
Best regards,
Manager of dZENcode
Our strengths:
💎 10+ years providing IT services: Outsourcing, Outstaffing
🔥 90+ in-house specialists
🚀 Projects "from scratch" and for support
⚙️ SLA and post-production support
✅ Contract with the company, guaranteed results!
🔥 250+ public reviews since 2015.
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7 days446 USD
7123 53 0 7 days446 USD
Hello! I am very interested in your project for setting up a CI/CD pipeline with AI automation. My 5 years of experience in development with Python (FastAPI) and JavaScript, as well as a deep understanding of architecture and infrastructure solutions, are perfectly suited for deploying your system. I am ready to efficiently set up the necessary infrastructure, integrate LLM automation for code review, and ensure a high level of security and support for multi-tenancy. I am confident that I can build a reliable and efficient pipeline that fully meets your requirements.
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14 days334 USD
4028 11 0 2 14 days334 USD
Hello!
I am ready to implement an AI code review process (LLM agents) with a focus on security and multi-tenancy according to your requirements.
I have practical experience with:
Python / FastAPI / Django
GitHub Actions / CI/CD / Docker
working with secrets, .env, staging/prod isolation
automating checks, API integrations, logging
building controlled pipelines with secure access
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24 days446 USD
417 2 0 24 days446 USD
Good day!
I have experience in building infrastructure and automation. I can implement the described pipeline.
**What I have already done:**
- **GitHub, branch protection** — working with private repos, branch protection
- **Secrets, .env** — zero hardcoded: API keys, DB credentials in environment variables
- **Docker, VPS, nginx** — production environment, SSL, reverse proxy
- **Staging / Production** — separate environments (dev/stage/prod) in projects
… - **CI/CD, deploy scripts** — automation of deployment, health checks
- **Python, FastAPI** — backend, API integrations
- **Runbooks, documentation** — operational instructions, audit trail
**Regarding AI-Pipeline:**
- GitHub Actions — setting up workflow for PR/push
- LLM API (Claude/GPT) — integration via API, diff analysis
- Prompts for security: leakage of IP/domains, tenant_id, fingerprinting
- Publishing results in Notion and as a comment to PR — via API
**Timeline:** 2–3 weeks.
I am ready to discuss the details — which LLM (Claude/GPT), Notion or Linear, whether there is already a repo. I look forward to your response.
Sergiy
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