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03 / Services / Cloud / Production

Cloud & DevOps for AISoftware that stays up.

Deploy, scale and secure AI applications, models, agents and data systems with modern cloud and DevOps infrastructure.

Discuss this service All services
Area
Cloud / Production
Stages
6
Related projects
3

01 / The problem

What usuallygets in the way.

Turn prototypes into maintainable applications on AWS, GCP or Azure, with infrastructure as code, CI/CD and observability.
01

The prototype works on one laptop only

02

Deployments are manual and scary

03

No visibility into errors, latency or spend

02 / What I build

Capabilitiesin this service.

01

Containerization & Deployment

Package and deploy AI services using Docker, Kubernetes, Docker Compose, and serverless workflows for more consistent, portable, and production-ready infrastructure.

02

CI/CD for AI Workflows

Set up automated pipelines for deployment, model updates, embedding refreshes, retraining jobs, and environment changes using GitHub Actions and modern DevOps tooling.

03

GPU Inference & Model Hosting

Deploy and optimize GPU-backed inference infrastructure for LLMs, embedding models, speech systems, vision models, and other high-performance AI workloads.

04

Security, Access & Monitoring

Implement authentication, rate limiting, logging, observability, audit trails, alerts, and usage controls to keep AI systems secure, stable, and easier to manage.

05

Vector Store & AI Backend Infrastructure

Deploy and manage vector databases, retrieval systems, API layers, and AI backend services for RAG pipelines, semantic search, knowledge assistants, and intelligent agents.

  • Containerised services and infrastructure as code
  • CI/CD pipelines with tests and preview environments
  • Logging, metrics, alerts and cost guardrails

03 / How it works

From commit to observed production

A typical architecture for this kind of work. Scroll to follow the flow, or hover a stage for detail.

  1. Code

    Reviewed changes with tests alongside.

  2. CI/CD

    Build, test and deploy on every merge.

  3. Containers

    The same image runs locally and in the cloud.

  4. Cloud runtime

    Managed services sized for real load.

  5. Observability

    Logs, traces and alerts on what users feel.

  6. Cost controls

    Budgets and scaling rules to avoid surprises.

04 / In depth

The details.

Cloud & DevOps for AI Services

Deploy, scale, and secure your AI applications, models, agents, and data systems with modern cloud and DevOps infrastructure. I help businesses build production-ready environments for LLMs, APIs, vector databases, model inference, and AI automation workflows.

My Expertise in Cloud & DevOps for AI

I specialize in building custom cloud and DevOps solutions for AI systems across healthcare, legal tech, e-commerce, SaaS, and other data-driven industries. My work combines cloud infrastructure, containerization, CI/CD, model deployment, observability, vector database hosting, and secure API operations to help businesses run AI products reliably at scale.

  • ☁️ Cloud Infrastructure for AI
  • 🐳 Containerization & Deployment
  • ⚙️ CI/CD for AI Workflows
  • 🚀 GPU Inference & Model Hosting
  • 🔐 Security, Access & Monitoring
  • 🧠 Vector Store & AI Backend Infrastructure

Cloud Infrastructure for AI

Build scalable cloud environments on AWS, GCP, Vercel, Supabase, and other platforms to support AI apps, APIs, model serving, storage, and secure backend operations.

My Expertise in Data & AI Industry

From raw data to AI-powered decisions - I help businesses implement end-to-end machine learning workflows, analytics dashboards, and automation pipelines.

Hire Me

Remote Data & AI Solutions

I’m a freelance Data Science and ML Engineer with 7+ years of experience transforming data into actionable insights. I specialize in building intelligent solutions, custom ML models, and scalable pipelines for startups and SMEs worldwide.

  • United States (Remote Projects)
  • Germany (AI Consultancy)
  • EUROPE (Remote Projects)
  • Remote - Available Worldwide

You Can find me here

As an independent Data & AI Engineer, I help companies unlock the full potential of their data. From predictive analytics to workflow automation, I offer strategic and technical support that drives real impact.

Book Free Consultation View Portfolio

05 / Tech stack

Tools I usefor this work.

  • AWS
  • GCP
  • Azure
  • Docker
  • Kubernetes
  • Terraform
  • Next.js
  • FastAPI

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06 / Related work

Proof,not promises.

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Cloud / Production

Need Cloud & DevOps for AI?Let’s scope it together.

Tell me about the goal, the data and the constraints. I’ll reply with questions and a practical first step.

Let’s chat