Career routes
Pick the AI role you're aiming for. Each route takes the lessons that matter for that job, in order, with a portfolio project to build as you go. Pass every lesson check and the route exam to earn a KatalockAi career route certificate.
Customer AI Deployment
Forward-Deployed AI Engineer · Field AI Engineer · AI Solutions Engineer
Discover a customer workflow, reduce its riskiest assumptions, and carry a useful AI system through measurement and rollout.
Developer Experience and Education
AI Developer Relations Engineer · AI Developer Advocate · Developer Experience Engineer
Build credible integrations, examples, and reusable agent packages, then turn developer friction into clearer tools and teaching.
AI Data Systems
AI Data Engineer · Machine Learning Data Engineer · Retrieval Engineer
Build reliable data, feature, embedding, retrieval, evaluation, and observability pipelines for AI systems.
Agent Systems Engineering
Agent Systems Engineer · Agentic AI Engineer · AI Agent Engineer
Engineer tool-using agent loops with explicit context, memory, orchestration, safety, evaluation, and production control.
LLM Product Engineering
Applied AI Engineer · LLM Engineer · AI Product Engineer
Turn language-model capability into evaluated, safe, cost-aware product behavior that can survive production traffic.
AI Evaluation and Reliability
AI Evaluation Engineer · AI Reliability Engineer · Machine Learning Site Reliability Engineer
Measure model and agent behavior, expose failure modes, instrument the runtime, and build release and incident controls around evidence.
Skill paths
Shorter paths through one skill, 5 to 17 lessons each. Pass every lesson check on a path, then a 10-question path quiz, and you earn a skill path certificate: a smaller milestone on the way to the big ones.
- Software Engineering FundamentalsBuild the repository, debugging, testing, interface, security, release, and operational foundations AI systems depend on.
- Building and Deploying AI ApplicationsBuild an AI feature from prompt and structured output through retrieval, evaluation, production serving, observability, and release.
- Agent-Assisted EngineeringFrame, plan, execute, delegate, verify, review, and improve coding-agent work inside real repositories.
- Product Judgment and DeliveryTurn evidence into outcomes, assumptions, testable slices, executable specifications, measurement plans, and owned feedback loops.
- Model Context Protocol (MCP)Build, secure, verify, and operate stateless MCP systems from JSON-RPC envelopes through conformance release gates.
- Agent Skills EngineeringBuild, route, secure, evaluate, package, and verify Agent Skills in real hosts.
Routes are built from current AI job descriptions. A certificate shows you completed the route's lessons and passed its exam; it doesn't guarantee a role or replace real production experience.