Generative AI Engineer Jobs
The Hottest Role in Tech.
Generative AI is reshaping every industry. Companies are desperately hiring
engineers who can build with LLMs, diffusion models, and foundation models.
AI Native Engineer Community Access
Breaking Into GenAI Is Harder Than It Looks.
The field evolves weekly. Skills from 6 months ago are already outdated.
Everyone calls themselves an 'AI engineer' now. Standing out is nearly impossible.
Job postings mix research roles with engineering roles. Hard to know what you're applying for.
Get Hired as a Generative AI Engineer.
The AI Career Accelerator
Generative AI engineer jobs require a specific skill stack: LLM architecture knowledge, fine-tuning expertise, prompt engineering, and deployment experience. Here's how to build that profile and land the role.
Master the GenAI Stack
LLMs, embeddings, RAG, fine-tuning
Build Production Projects
Ship real GenAI applications
Position & Apply
Target the right companies and roles
Meet Your Mentor
When I started in tech, I was based in the Netherlands with no connections and only thousands of video game hours under my belt. Not exactly the ideal starting point.
My first tech job was software tester. One of the most junior roles you can start with. I was just happy someone took a chance on me.
I kept learning. Kept pivoting. But what actually accelerated my career wasn't more certifications or more code. It was learning to solve problems that matter and proving beyond a doubt that what I built solved real problems. That's the skill that stays future-proof, even with AI.
I've since worked remotely for international software companies throughout my career. Proof that the high-paid remote path is possible for anyone with the right skills and motivation. In the end, I went from a $500/month internship to 6 figures as a Senior AI Engineer at GitHub.
Now I teach over 22,000 engineers on YouTube. Becoming an AI-Native Engineer is a system I lived through and offer to you today.
Real Results
Vittor
AI Engineer
Landed his first AI Engineering role in 3 months
"The coaching played a huge part in my success. I focused on AI fundamentals, the certification path, and soft skills like professional writing. Having access to expert guidance gave me confidence during interviews and helped me feel I was on the right path.
I built my own platform (simple but functional) and deployed it on AWS. I used it in my portfolio and showcased it during interviews. The way complex topics were explained, especially the restaurant analogy for AI systems, really stuck with me. Focusing on doing the basics well was absolutely essential."
What You Will Get
Personalized Roadmap & Career Strategy
A custom plan tailored to your background, goals, and timeline. No generic advice.
Weekly 1:1 Coaching Calls
Direct access to Zen for guidance, project feedback, and answers to your questions.
Portfolio-Ready AI Projects
Build production-grade AI applications to showcase to employers. Work that gets you hired.
Interview Prep & Mock Interviews
Practice technical and behavioral interviews. Learn what hiring managers look for.
Resume & LinkedIn Optimization
Transform your online presence to attract recruiters. Stand out from other applicants.
Community Career Support
Join the AI Native Engineer community. Not seeing results yet? You stay and keep going. We're with you through the ups and downs.
GenAI Hiring Is Peaking Now
Every month you delay can cost you thousands in lost earning potential. While you're watching tutorials, others are landing $120K+ AI Engineering roles.
I can only work with a limited number of 1:1 clients at a time to ensure you get the personalized attention you deserve.
Frequently Asked Questions
What's the difference between a Generative AI Engineer and ML Engineer?
ML Engineers build predictive models (classification, regression, forecasting). Generative AI Engineers build systems that create new content: text, images, code, audio. The tech stack differs significantly. GenAI roles focus on LLMs (GPT, Claude, Llama), diffusion models (Stable Diffusion, DALL-E), fine-tuning techniques (LoRA, PEFT), RLHF, and prompt engineering. Traditional ML roles focus on scikit-learn, XGBoost, feature engineering, and MLOps. Many companies now split these into separate teams.
What skills do I need for generative AI engineer jobs?
Core skills for 2026: 1) LLM fundamentals - transformer architecture, attention mechanisms, tokenization, 2) Fine-tuning - LoRA, QLoRA, PEFT, instruction tuning, 3) RAG systems - vector databases, embeddings, retrieval strategies, 4) Prompt engineering - few-shot learning, chain-of-thought, function calling, 5) RLHF/DPO - preference optimization, reward modeling, 6) Deployment - serving LLMs at scale, latency optimization, cost management. Python is essential. PyTorch preferred over TensorFlow for GenAI work.
What's the salary range for generative AI engineers?
Generative AI engineer salaries in 2026: Entry-level (0-2 years): $120K-$160K. Mid-level (2-5 years): $160K-$220K. Senior (5+ years): $220K-$350K. Staff/Principal: $300K-$500K+. Top-tier companies (OpenAI, Anthropic, Google DeepMind, Meta FAIR) pay significantly above market. Equity can double total compensation at startups. Remote roles typically pay 10-20% less than Bay Area rates. Specialized skills like RLHF or multimodal models command premium salaries.
Which companies hire generative AI engineers?
Top employers for GenAI roles in 2026: Foundation model companies - OpenAI, Anthropic, Google DeepMind, Meta AI, Mistral, Cohere. Enterprise AI - Microsoft, Amazon (AWS Bedrock), Salesforce, Adobe, Notion. AI-native startups - Runway, Character.ai, Jasper, Copy.ai, Midjourney. Traditional tech with GenAI teams - Netflix, Spotify, Uber, Airbnb, Stripe. Every Fortune 500 company is now building GenAI teams. The best opportunities often come from Series A-C startups building GenAI products.
Do I need a PhD for generative AI engineer jobs?
No. Most generative AI engineer roles are engineering positions, not research roles. You need to understand how to use and deploy models, not invent new architectures. What matters: proven ability to build GenAI applications, understanding of the tech stack, and production deployment experience. A strong portfolio beats a PhD for engineering roles. Research Scientist roles at labs like Anthropic or DeepMind do prefer PhDs, but Applied AI Engineer and GenAI Engineer positions hire based on demonstrated skills.
What portfolio projects should I build for GenAI jobs?
Projects that get you hired: 1) RAG application - Build a chatbot that answers questions from your own documents. Shows embedding, retrieval, and LLM integration skills. 2) Fine-tuned model - Take a base model and fine-tune it for a specific task. Document the process. 3) AI agent - Build an agent that can use tools, plan, and execute multi-step tasks. 4) Multimodal application - Combine text and image generation. 5) Production deployment - Show you can deploy and scale GenAI apps. Open-source contributions to LangChain, LlamaIndex, or Hugging Face also stand out.
Do I need prior AI experience?
Not necessarily. While some programming experience is helpful, many of my clients have successfully transitioned from web development, data science, or other technical backgrounds. We'll assess your current skills during our strategy call and create a personalized plan that meets you where you are.
How much time do I need to commit?
Most clients invest 10-15 hours per week, but this can be flexible based on your schedule. We'll have weekly 1:1 calls plus time for you to work on projects and learning. The key is consistency. Regular, focused effort beats occasional marathons.
What if I don't land interviews in 90 days?
You become a member of the AI Native Engineer community, and you stay and keep going. Career transitions take different amounts of time for everyone, and I'm not going to abandon you if things take longer. You get ongoing support through good times and bad.
How is this different from online courses?
Online courses give you content. 1:1 coaching gives you a personalized roadmap, direct feedback on your work, career strategy, interview prep, and accountability. You get answers to your specific questions and guidance tailored to your unique situation instead of generic advice meant for everyone.
What's the investment for 1:1 coaching?
Investment details are discussed during the 30-minute strategy call, where we'll assess your goals and create a custom plan. The program is designed to pay for itself quickly through your increased salary. Most AI engineers see a 20-50% pay increase.
Can I do this while working full-time?
Absolutely. Most of my clients work full-time and make steady progress. We'll schedule calls at times that work for you and create a realistic plan that fits your schedule. Consistency matters more than intensity.
Ready to Land Your AI Role?
Stop watching others succeed. Start building your AI career today.
30-minute strategy call • Limited spots available