Event PAST

MLOps London Signal Night: Agents in Production

21 May Online

About this event

You do not need to be deep in MLOps to attend.

If you are a founder building with AI, a recruiter trying to understand what good AI engineering talent looks like, a fractional CTO/advisor, or a newer builder wondering what happens after a demo works, this event is about the real-world jump from prototype to something people can rely on.

MLOps London is moving into its next chapter.

The group has a strong history of practical talks and production-focused conversations. This first event under the new cadence is deliberately simple: a signal night for introductions, production-AI pain points, hiring/fractional CTO needs, and topics people want the community to cover next.

The theme for the next few months is production AI:

  • agent systems after the demo
  • observability and evaluation
  • deployment and rollback
  • governance and ownership
  • what teams are learning the hard way

No slides. No formal talks. No vendor pitches.

The lightweight format:

  • builders mark what they know: agents, evals, observability, infra, deployment, governance, cost, rollback
  • founders/recruiters mark what they need: fractional CTO input, hiring signal, architecture review, speaker/topic suggestions
  • everyone leaves with a Production AI Bench Card: one useful intro target, one topic/failure mode for the June talk night, and one clear ask or offer

Ram will give a short welcome around 7pm and outline the plan for the June talk night: "AI Agents in Production: What Actually Breaks After the Demo."

Come if you build, deploy, evaluate, operate, hire for, advise on, or lead production AI systems.

Free to attend. Please RSVP with enough detail for us to understand who is in the room.

You should leave with a clearer sense of what breaks first when AI meets real users, what skills matter, what questions founders and recruiters should ask, and who in the room can help.

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.