Platform Engineer: Scalable, Reusable AI Tooling

Genesis AI; Paris; On-site; EUR 90,000 - 130,000; Full time

Job summary

Genesis AI is seeking an experienced software engineer to design, build, and maintain foundational frameworks and tools that empower expert teams to rapidly experiment and deliver production-ready AI systems.

You will collaborate across teams to validate use cases, craft modular, reusable components, and drive high-quality code through reviews, documentation, and training, with a focus on scalable internal tooling for AI research.

Qualifications

• Excellent software engineering skills in Python, Go, or Rust.
• Experience designing, building, and maintaining modular and reusable systems.
• Experience collaborating with engineers and researchers across fields, understanding complex requirements, and providing clear and simple solutions.
• Ability to implement large-impact changes across the organization with minimal disruption.
• Experience building internal tooling to accelerate AI research workflows (debugging, evaluation, experiment tracking and versioning, CI automation, etc.).

Responsibilities

• Design, build, and maintain foundational frameworks and tools to empower expert teams to experiment fast and turn ideas into full-fledged and production-ready systems.
• Collaborate with expert teams to validate uses cases and build robust solutions, bringing cross-team perspective and aiming for modular and reusable components.
• Identify and mitigate high-level code design flaws and development workflow inefficiencies that cause friction, hinder productivity, and create silos across the organization.
• Advocate for good practices and maintain high code quality through code reviews, documentation, and training.

Skills

Python

Go

Rust

Modular system design

Cross-disciplinary collaboration

Impactful change implementation

Internal tooling for AI research

Job description

Genesis AI is seeking an experienced software engineer to design, build, and maintain foundational frameworks and tools that empower expert teams to rapidly experiment and deliver production-ready AI systems.

You will collaborate across teams to validate use cases, craft modular, reusable components, and drive high-quality code through reviews, documentation, and training, with a focus on scalable internal tooling for AI research.