DevOps Engineer with AI

• Ability to work 2:00 p.m. - 10:00 p.m . (CEST)
• At least 5 years of experience in a DevOps role, with a strong focus on infrastructure and reliability engineering
• Previous experience in working on AI/ML projects - MUST❗️
• Proven experience in building and maintaining production-ready agentic systems (including agent loop architecture, tool/function calling integrations, state management, and custom evaluation harnesses)
• Strong hands-on experience writing clean, scalable Python code
• Knowledge of relational databases (e.g., PostgreSQL), vector databases, and columnar databases
• Practice with AWS, K8s and Terraform

Nice to have:

• BS/MS in Computer Science, Mathematics, Statistics, or a related quantitative field
• Knowledge of Golang

You will be cooperating with a leading provider of AI evaluation and optimization solutions, trusted by multinational companies to optimize AI agents and detect performance issues in large language models.
Currently, we are developing advanced reinforcement learning (RL) environments and scalable evaluation systems that guide and shape the behavior of cutting-edge AI models. The company’s mission is to enable safe, verifiable, and aligned AGI through rigorous, real-world agent evaluation.

Due to the client’s time zone, we would appreciate a candidate who can work until 10:00 p.m.

Join us and make a real impact!

If you’re ready to broaden your horizons and work with an innovative company at the forefront of AI, we’d love to hear from you. You’ll help build the environments that shape how future AI systems are trained, evaluated, and aligned - and collaborate with world-class engineers and researchers on one of the most important technical challenges of our time.

,[Build and maintain production agentic systems, including agent loop architecture, tool/function calling integrations, state management, and custom evaluation harnesses, Produce high-quality, reproducible, production-level code that integrates cleanly into our client’s systems, Develop infrastructure for task generation, synthetic data generation, verifiable reward design and tool simulations, Creating and maintaining CI/CD processes and automating deployments, Drive Infrastructure as Code practices using Terraform, Work with customers on environment integrations, stepping in hands-on to unblock the team as needed] Requirements: Python, FastAPI, AI, AWS, Kubernetes Additionally: Sport subscription, Private healthcare, Flat structure, Small teams, International projects.