Choose Your Role

Select your engineering career path and follow a structured, expert-curated roadmap that links directly to real course modules — no guesswork required.

20 Career Paths

Every path is built from existing SKILLY course modules — click any role to see its full learning roadmap.

⚙️

DevOps Engineer

Build CI/CD pipelines, automate infrastructure, containerize workloads, and monitor production systems.

10 Steps Beginner → Advanced
🔷

Azure DevOps Engineer

Specialize in Azure-native pipelines, AKS deployments, Bicep IaC, and enterprise delivery workflows.

10 Steps Intermediate
🛠️

Site Reliability Engineer

Own system reliability through SLOs, error budgets, observability stacks, and incident response engineering.

10 Steps Advanced
☁️

Cloud Engineer

Design and manage cloud infrastructure across Azure, AWS, and GCP with Terraform automation.

10 Steps Beginner → Intermediate
🏛️

Cloud Architect

Design enterprise-scale multi-cloud architectures, governance frameworks, and reliability strategies.

10 Steps Advanced
🏗️

Platform Engineer

Build internal developer platforms enabling teams to self-serve infrastructure, pipelines, and observability.

10 Steps Advanced
🛡️

DevSecOps Engineer

Embed security into every delivery stage — from code scanning and SAST to pipeline security gates.

10 Steps Intermediate → Advanced
🤖

Automation Engineer

Build, maintain, and optimize automated workflows using Python, PowerShell, and AI-assisted tooling.

10 Steps Intermediate
🚀

Build & Release Engineer

Own the build, packaging, versioning, and release process across multi-environment delivery pipelines.

10 Steps Intermediate
🧪

Test Automation Engineer

Design automated testing strategies across unit, integration, security, and regression layers.

10 Steps Intermediate
🤝

Support Engineer

Diagnose and resolve production issues across cloud, containers, and observability platforms.

10 Steps Beginner → Intermediate
📊

Data Engineer

Build AI-ready data pipelines on Azure with MLOps, OpenAI integration, and cloud infrastructure.

10 Steps Intermediate → Advanced
🧠

AI Engineer

Build production AI applications with Azure AI services, Azure OpenAI, containers, deployment pipelines, and observability.

10 Steps Intermediate → Advanced
⚙️

MLOps Engineer

Operationalize ML systems with reproducible environments, model deployment pipelines, governance, and production monitoring.

10 Steps Advanced
📡

AIOps Engineer

Apply machine learning and LLM workflows to observability, anomaly detection, alert intelligence, and incident response.

10 Steps Advanced
🤖

AI Automation Engineer

Design workflows that combine scripting, pipelines, AI services, and LLMs to automate operational and developer tasks.

10 Steps Intermediate → Advanced
🖥️

IIS Administrator

Configure, secure, monitor, and troubleshoot IIS on Windows Server — from application pool management and SSL binding to PowerShell automation and production incident diagnosis.

10 Steps Beginner → Intermediate
🤝

Application Support Engineer

Diagnose and resolve application-layer failures across cloud, containers, and observability platforms. The technical bridge between user-reported problems and engineering teams.

10 Steps Beginner → Intermediate

Windows & Linux Administrator

Own the OS layer across both platforms — provisioning, securing, monitoring, and maintaining servers in hybrid environments where Windows and Linux workloads run side by side.

10 Steps Beginner → Intermediate
💻

.NET Backend Engineer

Build, ship, and secure .NET applications on Azure with containers, CI/CD, and code quality gates.

10 Steps Intermediate