Why Software Engineers Should Move Into AI Engineering

Bashiri Smith · Facebook reel · 2026-09-17 · 0:49 · 2,132 views · Open on Facebook

Topics: Resume, Job Search & Interviews, Start Here: Roadmaps & Strategy, Industry Trends & Job Market · Level: beginner

Summary

The creator argues that AI engineering is a natural next career step for software engineers. Most AI engineering work means turning existing models into useful products, not research, so you don't need a PhD or strong math. Your current skills with APIs, databases, debugging and deployment carry over. To get there, learn model integration, RAG, tool use, evaluation, and how to handle failures, cost and latency in production. The video ends by asking viewers to comment "UPGRADE" to get the creator's roadmap and a link to the creator's community.

Key points

• The creator says AI engineering is ranked #1 on LinkedIn's Jobs on the Rise list and calls it the fastest-growing career in tech.
• Most AI engineering work means taking existing models and turning them into useful products or features. You don't need a PhD or a love of math.
• Retrieval-augmented generation (RAG) is the most-requested skill and appears in more than 40% of AI engineering job descriptions (creator's claim).
• The creator says AI engineers earn about 20% more on average than regular software engineers.
• These software skills carry over: APIs, databases, debugging and deployment.
• Skills to learn: connecting models to your app, RAG over your own data, giving AI tools so it can take actions, evaluating whether the system actually works, and handling failures, cost and latency in production.
• How to learn: pick one real problem, build a solution, test it, deploy it, and be able to explain your decisions.

Resources mentioned

• The Complete AI Engineer Roadmap for 2026 (Exact Courses + Step-by-Step) · video · youtube.com · free
  Bashiri Smith's free YouTube training on upgrading your skills and becoming competitive for AI engineering roles, with specific courses listed step by step.
  Also in: SWE-to-AI Engineer Plan for 2027: LLMs, RAG, Agents, Evals, Job Search (Bashiri Smith on Facebook · notes), Pointer to Bashiri Smith's Complete AI Engineer Roadmap for 2026 (Bashiri Smith on Facebook · notes), Step-by-Step Roadmap to a $200K+ AI Engineering Role (Bashiri Smith on Facebook · notes), Software Engineer to AI Engineer Before 2027: A 5-Step Career Plan (Bashiri Smith on Facebook · notes) and 19 more
• BASWE.Ai Engineer (Skool community) · community · skool.com · paid
  The creator's paid community and program, with an AI learning roadmap (including the full ops and evaluation track), daily calls with engineers and recruiters, resume and portfolio help, and a job-search pipeline.
  Also in: Basic RAG Pipeline in 60 Seconds: From Documents to Grounded Answers (Bashiri Smith on Facebook · notes), Pointer to Bashiri Smith's Complete AI Engineer Roadmap for 2026 (Bashiri Smith on Facebook · notes), Step-by-Step Roadmap to a $200K+ AI Engineering Role (Bashiri Smith on Facebook · notes), How to Evaluate a RAG Pipeline: Retrieval vs. Generation (Interview Answer) (Bashiri Smith on Facebook · notes) and 76 more
• LinkedIn Jobs on the Rise · article · linkedin.com · free
  LinkedIn's ranking of the fastest-growing jobs in the US, which put AI engineer at #1 for 2026.
  Also in: AI Engineer Salaries at OpenAI & Anthropic and the Skills They Want (Bashiri Smith on Facebook · notes)

Try this

• Choose one real problem and build an AI-powered solution for it.
• Test the solution, deploy it, and be ready to explain your design decisions.
• Learn to connect models to an application, build RAG over your own data, add tool use, set up evaluations, and handle failures, cost and latency.
• Comment "UPGRADE" on the post to get the creator's roadmap and community link.
• Pick one real problem and build, test and deploy an AI solution for it, such as a RAG app that answers questions using your own data.