SuperPlane
AI

Applied AI Engineer

SuperPlane · ES

Actively hiring Posted 5 months ago

Role overview

  • Design and implement AI-powered features end to end, including prompts, agents, tools, retrieval, evaluation, and feedback loops.
  • Build agent systems that interact safely with infrastructure, codebases, and deployment pipelines.
  • Integrate LLMs deeply into product workflows as core platform primitives.
  • Own quality across correctness, reliability, latency, and cost of AI systems in production.
  • Collaborate closely with Product, Frontend, and Backend engineers to ship cohesive user-facing features.
  • Establish best practices for prompt design, evaluation, observability, and iteration.

Basic qualifications

  • You shipped production systems where LLMs, tool calling, or RAG workflows were part of the core functionality.
  • You’ve built and owned highly reliable backend systems with strong engineering judgment and technical depth. You are willing to master Go and Typescript.
  • You’ve developed systematic LLM evaluation pipelines using observability tools (LangSmith/Braintrust) to track performance and regressions.
  • You worked closely with product and frontend partners to deliver user-facing features.
  • You communicate clearly in writing and in technical discussions.
  • Work on an open source platform shaping the future of DevOps worldwide.
  • Build AI systems that operate real infrastructure, not toy demos.
  • Competitive compensation & meaningful equity in a high-growth startup.
  • Fully remote and flexible environment that lets you focus and create.

About the company

SuperPlane is an AI-native DevOps control plane. Our mission is to build the platform teams use to ship and manage software in the AI era.

Agents are helping us write an order of magnitude more code, while systems have become too complex for human-driven ops alone. We're rethinking DevOps from first principles for the AI era: a single control layer where engineers and agents safely collaborate.

We move fast. We aim high. If that sounds like the kind of problem you want to work on, we’d love to talk.

Tags & focus areas

Used for matching and alerts on DevFound
Remote Ai Ai Engineer Generative Ai
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.