Entry-Level AI Engineer Jobs
Your Path In Starts Here.

The 'experience required' on job postings is often a wishlist, not a hard requirement. Companies hire entry-level candidates who demonstrate capability through other means: strong portfolio projects, open-source contributions, relevant internships, or impressive personal projects. Focus on building 2-3 substantial projects that solve real problems. Document your process, show your thinking, and deploy them publicly. This counts as experience in hiring managers' eyes.

In 2026, entry-level AI roles typically want: 1) Python proficiency with data manipulation (pandas, numpy), 2) Understanding of ML fundamentals (supervised/unsupervised learning, model evaluation), 3) Familiarity with at least one deep learning framework (PyTorch preferred), 4) Basic experience with LLMs and prompt engineering, 5) Git and basic software engineering practices. You don't need to be an expert in everything, but you need enough depth in a few areas to contribute from day one.

Not necessarily. While some companies filter by degree, many startups and forward-thinking companies hire based on demonstrated skills. A strong portfolio, relevant certifications, and practical experience can outweigh formal credentials. That said, a technical background (engineering, physics, math) helps. If you're a career changer from a non-technical field, you'll need to work harder to prove your technical abilities through projects and contributions.

Avoid the typical Titanic or MNIST projects everyone has. Instead, build projects that: 1) Solve a real problem you care about, 2) Use current technologies (LLMs, RAG systems, fine-tuning), 3) Are deployed and usable (not just notebooks), 4) Show end-to-end thinking (problem definition, data, model, deployment). Example: Build a RAG-based assistant for a specific domain, deploy it, and write about what you learned. One great project beats ten tutorials.

Entry-level AI engineer salaries in 2026 typically range from $90K-$140K depending on location, company size, and your specific skills. Major tech hubs (SF, NYC, Seattle) pay at the higher end but have higher costs of living. Remote roles often pay 10-20% less but offer flexibility. Startups might offer lower base salary but include equity. Your negotiating power increases significantly with a strong portfolio and competing offers.

Self-study works, but it's slow and you don't know what you don't know. Coaching provides: 1) A personalized roadmap based on your current skills and target roles, 2) Accountability to actually complete projects instead of endless tutorial loops, 3) Insider knowledge on what hiring managers look for, 4) Resume and portfolio review from someone who's hired AI engineers, 5) Mock interviews and feedback. Most candidates who work with me land roles 2-3 months faster than they would alone.

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.

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.

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.

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.

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.

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.