SkillHack › Career guides

50 AI careers, each with a free roadmap

“AI” is not one job. Every path below has an authored roadmap: phases of topics, a study note and real reading on each, and graded practice questions that unlock as you pass the topic before. Pick the one closest to the job you already do.

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Every path

Agent Engineer

Multi-agent architectures, orchestration, tool design, and agent reliability. Build agent systems that plan, act, and recover on their own.

5 phases · 103 practice questions

AI Alignment Researcher

Training methods, oversight, and alignment evaluations. Make advanced AI pursue the goals we intend.

5 phases · 105 practice questions

AI Automation Engineer

Agents, tool integration, and workflow orchestration. Turn multi-step business processes into automated flows.

5 phases · 18 practice questions

AI Data Engineer

Ingestion pipelines, embeddings, vector stores, and data quality for training and retrieval. Feed AI systems clean, fresh, well-shaped data.

5 phases · 92 practice questions

AI Developer Advocate

Docs, sample apps, talks, and community feedback loops. Help developers build with AI and carry their voice back to the product.

5 phases · 17 practice questions

AI Engineer

Prompt and context design, tools, retrieval, orchestration, evaluation, and structured output. Build reliable agent apps end to end.

5 phases · 60 practice questions

AI Evals Engineer

Benchmark design, LLM-as-judge, regression suites, and quality metrics. Measure what models actually do before and after every change.

5 phases · 77 practice questions

AI for Science Engineer

Modeling in biology, chemistry, physics, and materials, plus research tooling. Apply AI to scientific discovery.

5 phases · 15 practice questions

AI Governance Analyst

Regulatory compliance, model cards, risk frameworks, and audit trails. Keep AI systems accountable and inside the rules.

5 phases · 80 practice questions

AI Infrastructure Engineer

Data pipelines, infrastructure, deployment, observability, and cost control. Keep data, infra, and models reliable and cost-aware.

5 phases · 87 practice questions

AI Integration Engineer

APIs, enterprise systems, legacy migration, and AI-feature rollout. Wire AI capabilities into the software businesses already run.

5 phases · 82 practice questions

AI Platform Engineer

Internal SDKs, model gateways, routing, and guardrail infrastructure. Build the platform every team ships AI on.

5 phases · 17 practice questions

AI Policy Analyst

Regulation, standards, risk, and societal impact. Translate AI policy into what teams must actually build.

5 phases · 17 practice questions

AI Product Manager

Product scoping, model capability awareness, eval-driven decisions, and AI UX trade-offs. Decide what to build and prove it works.

5 phases · 81 practice questions

AI Program Manager

Scoping, sequencing, risk, and cross-team coordination. Drive AI initiatives from research to launch.

5 phases · 19 practice questions

AI Quality Engineer

Behavioral test suites, regression and red-team checks, and release gates. Test AI products that never give the same answer twice.

5 phases · 15 practice questions

AI Red Team Specialist

Jailbreaks, adversarial testing, misuse probing, and vulnerability reporting. Attack AI systems before real adversaries do.

5 phases · 77 practice questions

AI Reliability Engineer

Uptime, fallbacks, guardrails, and incident response for AI in production. Keep AI features fast, safe, and available.

5 phases · 81 practice questions

AI Research Engineer

Training runs, fine-tuning, experiment infrastructure, and paper-to-production. Turn research ideas into working, measured models.

5 phases · 76 practice questions

AI Research Scientist

Novel architectures, training methods, scaling laws, and publication. Push the frontier of what models can do.

5 phases · 75 practice questions

AI Safety Engineer

Risk analysis, red teaming, privacy, policy, evaluation design, and monitoring. Probe, evaluate, and govern AI systems.

5 phases · 93 practice questions

AI Security Engineer

Prompt injection defense, model supply chain, data leakage, and access control. Secure AI systems end to end.

5 phases · 74 practice questions

AI Solutions Architect

System design, model selection, build-vs-buy, and scaling and cost. Architect enterprise AI solutions that hold up in production.

5 phases · 79 practice questions

AI Strategist

Opportunity sizing, build-vs-buy, and adoption strategy. Decide where AI creates real business value.

5 phases · 16 practice questions

AI Systems Engineer

GPUs, distributed training, kernels, and memory and throughput optimization. Make large models train and serve fast.

5 phases · 77 practice questions

AI UX Designer

Human-AI interaction patterns, trust, uncertainty, and feedback loops. Design interfaces where people and models work well together.

5 phases · 78 practice questions

Analytics Engineer

Data modeling, transformation pipelines, metrics, and data quality. Turn raw data into trusted datasets teams can build on.

5 phases · 15 practice questions

Applied Scientist

Model adaptation, evaluation, and prototyping against real product problems. Take research from paper to production.

5 phases · 75 practice questions

Computer Vision Engineer

Image and video models, VLMs, detection, and visual inspection. Ship systems that see and understand the world.

5 phases · 75 practice questions

Context Engineer

Context windows, memory systems, retrieval strategy, and token budgeting. Get the right information in front of the model every time.

5 phases · 81 practice questions

Conversational AI Designer

Dialog flows, persona design, voice and chat UX, and escalation paths. Craft conversations people actually want to have.

5 phases · 77 practice questions

Data Scientist

Experiment design, statistics, causal inference, and modeling. Turn data into decisions and explain why.

5 phases · 17 practice questions

Edge AI Engineer

On-device models, quantization for mobile and embedded, and offline inference. Run AI where the cloud can't reach.

5 phases · 49 practice questions

Forward-Deployed Engineer

Workflow discovery, ambiguous requirements, agent-solution scoping, and deployment planning. Turn vague customer asks into scoped, shippable agent solutions.

5 phases · 91 practice questions

Generative Media Engineer

Image, video, audio, and 3D generation - pipelines, controllability, and creative tooling. Build the systems behind generative media.

5 phases · 15 practice questions

Inference Optimization Engineer

Quantization, distillation, serving performance, and latency and cost control. Make models fast and affordable at scale.

5 phases · 77 practice questions

Interpretability Researcher

Features, circuits, probing, and mechanistic analysis. Explain what is actually happening inside a model.

5 phases · 75 practice questions

Knowledge Engineer (RAG)

Knowledge bases, embeddings, vector search, and graph RAG. Ground model answers in the right source of truth.

5 phases · 17 practice questions

LLMOps Engineer

Prompt and version management, evaluation gates, and cost and latency monitoring. Keep LLM applications reliable through every model and prompt change.

5 phases · 17 practice questions

ML Engineer

Model selection, training and evaluation, experimentation, and statistical reasoning about the models you ship.

5 phases · 27 practice questions

MLOps Engineer

Model CI/CD, registries, monitoring, and drift detection. Keep the path from training to production repeatable and observed.

5 phases · 17 practice questions

Multimodal AI Engineer

Text, image, audio, and video together - fusion, cross-modal retrieval, and multimodal integration. Build AI that sees, hears, and reads at once.

5 phases · 75 practice questions

NLP Engineer

Text pipelines, classification, extraction, and multilingual systems. Build the language layer of AI products.

5 phases · 17 practice questions

Post-Training Engineer

Fine-tuning, RLHF, alignment tuning, and model specialization. Shape base models into products with the behavior you need.

5 phases · 75 practice questions

Prompt Engineer

Prompt design, context engineering, and eval-driven iteration. Get reliable, repeatable behavior out of frontier models.

5 phases · 15 practice questions

Recommender Systems Engineer

Candidate generation, ranking models, embeddings, and feedback loops. Personalize what every user sees at scale.

5 phases · 16 practice questions

Robotics / Embodied AI Engineer

Perception, control, simulation, and vision-language-action models. Put AI to work in the physical world.

5 phases · 16 practice questions

Search & Ranking Engineer

Classic information retrieval, neural retrieval, and LLM re-ranking. Return the right result first, at scale.

5 phases · 17 practice questions

Synthetic Data Engineer

Data generation, augmentation, and privacy-preserving datasets. Manufacture the data real-world collection can't provide.

5 phases · 16 practice questions

Voice AI Engineer

Speech recognition, text-to-speech, voice agents, and real-time audio. Build AI you can talk to.

5 phases · 15 practice questions

Start the AI path for free

The full study notes, the reading, and the practice questions behind every topic above are in the app. Answer one tonight and you have started.

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