AI Engineer
LLMs, embeddings, vector databases, prompt engineering and building production AI applications.
Developer Hub
Step-by-step guides to becoming a frontend, backend, DevOps, AI or cloud engineer, from roadmap.sh.
15 results • Page 1 of 2
LLMs, embeddings, vector databases, prompt engineering and building production AI applications.
Languages, databases, APIs, caching, authentication and everything else backend engineers need.
Step-by-step guide covering HTML/CSS/JavaScript, frameworks, tooling and modern frontend practices.
A guide to designing large-scale distributed systems - load balancing, caching, sharding, consistency and real architectural trade-offs.
“The topic senior engineering interviews actually hinge on - this roadmap is a solid map of the trade-off vocabulary you need before your first whiteboard session.”
A structured path through AWS's core services - compute, storage, networking and IAM.
Networking fundamentals, threat modeling, offensive/defensive security and career specializations.
A path through data pipelines, warehousing, orchestration and the modern data stack, from fundamentals to production systems.
“One of the least-served roles by generic learning content - this roadmap is a rare structured answer to what you actually need beyond SQL for the job.”
A structured path through core CS fundamentals - arrays, trees, graphs, sorting and complexity analysis - for interviews and real engineering judgment.
“Useful well beyond interview prep - the roadmap doubles as a checklist for the CS fundamentals bootcamps and self-taught paths often skip entirely.”
CI/CD, containers, orchestration, infrastructure as code, monitoring and cloud platforms.
A step-by-step guide combining the frontend and backend roadmaps into one path toward full-stack proficiency.
“For the developer who's outgrown thinking in just-frontend or just-backend terms - a genuinely honest sequencing of what to learn next rather than everything at once.”
A dedicated, deep path through Kubernetes - pods, deployments, networking, storage and operating real clusters in production.
“Goes deeper than the general DevOps roadmap's Kubernetes section - the right next step once kubectl-apply-and-hope stops being an acceptable operating strategy.”
A structured path through Python fundamentals, web frameworks, testing and deployment for building real applications.
“Skips the long stretch of Hello World repetition most tutorials get stuck in and gets to frameworks and real deployment fairly quickly.”