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Engineering Lead

Genius
Department:React Lead
Type:REMOTE
Region:EU
Location:Spain
Experience:Mid-Senior level
Salary:$5,000 - $7,000
Skills:
PYTHONNODEREACTNEXT.JSAPISPIPELINESORCHESTRATIONSTORAGELLM-INTEGRATED WORKFLOWSSYSTEM ARCHITECTUREAI CAPABILITIESOPEN-SOURCE TOOLSCLOUD INFRAAWSGCPCI/CD PIPELINESCONTAINERSDEPLOYMENT
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Job Description

Posted on: May 24, 2025

Engineering Lead (AI-Powered Digital Products)

We're looking for an Engineering Lead who builds systems with clarity, speed, and leverage. This role is central to how we operate. You'll lead through architecture, code, and clean abstractions — not people management. You'll work directly with product, design, and generalists to create the internal infrastructure that allows our small team to operate at 5-10x capacity.

We're not shipping AI features to check a box. We're building AI-native workflows — tools that shift how people think, work, and ship. Every system you help build will start with internal use. Once it consistently improves human output, we'll commercialize it.

This role requires a builder who thinks long-term but ships in short loops. Someone who sees product quality and infrastructure quality as two sides of the same problem.

Salary: Highly competitive package aligned with your experience level, technical capability, and local market rates + an incentive program that we include high-performing hires in. ($5,000 - $7,000)

Location: Remote

Schedule: Fully remote position with flexible working hours defined as: minimum hours per week that can be worked flexibly throughout the day, depending on product lifecycle needs and priorities.

RequirementsWhat you'll do

  • Build backend systems and infrastructure from scratch — APIs, pipelines, orchestration, storage
  • Own full-stack workflows: light front-end (React, Next.js) to backend (Python, Node, etc.) to deployment
  • Design and evaluate LLM-integrated workflows that assist or automate high-value tasks
  • Define system architecture and technical direction with an eye toward composability and maintainability
  • Collaborate across product and design to scope, build, and iterate quickly, internal-first, userfacing second
  • Evaluate and integrate emerging AI capabilities (retrieval, agents, reasoning frameworks, etc.)
  • Identify, adapt, and integrate open-source tools and frameworks where useful —always optimizing for speed, clarity, and leverage
  • Debug, refactor, and improve systems as they grow — no handoffs, no silos

What you bring

  • Strong experience building and scaling backend systems in production (Python, Node, Go, or similar)
  • Familiarity with LLMs, prompt engineering, or workflow-based AI integrations
  • Experience in building and iterating on algorithms and their use with AI workflows
  • Comfort working across the stack — you don't need to love front-end, but you're not blocked by it
  • Ability to work autonomously and make smart decisions with imperfect information
  • Fluency with cloud infra (AWS, GCP, etc.), CI/CD pipelines, containers, and deployment
  • Systems thinking: you design for long-term simplicity, not short-term hacks
  • Clear communication — concise, honest, direct

Nice to have (but not required)

  • Experience with agentic systems, vector databases, AI memory implementations or task routing logic
  • Background in developer tools, internal platforms, or automation infrastructure
  • Comfort working in early-stage, zero-to-one product environments

Benefits

Why this contribution matters

Every product we build is powered by the systems you help create. If our infrastructure is tight, modular, and expressive — we move faster, ship better, and think more clearly as a team.

This isn't a layer-above-the-team engineering role. This is the team. If you're looking for depth over headcount, clarity over consensus, and the chance to shape how AI systems get built from the inside out — we'd love to talk.

Originally posted on LinkedIn

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