Try for free
Event PAST

AI Engineering: Skill Stack, Agents, LLMOps, and How to Ship AI Products

26 January Online

Join this event

🎟️ Register / View Event Details

About this event

​Shipping real AI products is now one of the most in-demand engineering skills, but most teams still get stuck turning prototypes into something that actually works.

​In this podcast, AI engineer and bestselling author Paul Iusztin breaks down the full AI engineering skill stack:

  • ​The principles behind production-grade systems
  • ​How to build reliable agentic workflows
  • ​The LLMOps practices that keep models stable
  • ​The patterns he’s learned from shipping more than 20 AI applications

​We’ll also go beyond the code. Paul will share how he structures his work, teaching, writing, and professional growth, and how he uses AI tools to stay focused, productive, and consistent.

​Join us live if you want a straightforward look at the technical and personal side of modern AI engineering.
​
​About the Speaker:
​Paul Iusztin is an AI engineer committed to helping developers create fully functional, production-grade AI products. He is the author of the bestselling "LLM Engineer’s Handbook," leads the Agentic AI Engineering course, and is a founding AI engineer at a startup based in San Francisco. He also Decoding AI Magazine, where he assists engineers in moving beyond the proof-of-concept stage to build more effective AI systems.

​With over ten years of experience, Paul teaches comprehensive AI engineering, covering everything from data gathering to deployment, monitoring, and evaluation. He emphasizes robust software practices, infrastructure, and principles that are reliable in a world increasingly influenced by AI coding tools.

Join our Slack: https://datatalks.club/slack.html

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity

We respect your inbox. Unsubscribe at any time.

© 2026 DevFound.ai. All rights reserved.

Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.

Still have questions?

Contact Support