> Markdown version of [/jobs/ext/1626312-senior-devops-infrastructure-ai-llm-systems-engineer-hybrid-yuma-ai](https://www.wearedevelopers.com/jobs/ext/1626312-senior-devops-infrastructure-ai-llm-systems-engineer-hybrid-yuma-ai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior DevOps / Infrastructure & AI LLM Systems Engineer (Hybrid) Yuma AI - **Company:** Raw Talent - **Location:** Barcelona, Spain (Remote available) - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Amazon Web Services, Application Performance Management, Systems Engineering, Microsoft Azure, Software as a Service, Cloud Computing, DevOps, Github, Identity and Access Management, Python (Programming Language), PostgreSQL, Performance Tuning, Redis, Ruby, Systems Architecture, Data Logging, Google Cloud, Large Language Models, Backend, Kubernetes, Docker - **Published:** July 18, 2026 - **Apply:** https://es.trabajo.org/oferta-2258-4c9e94e4df1abaf80b0ef2434bfdeafe ## About the Role Systems: - High-scale PostgreSQL (large DB, indexes, performance tuning). - Redis and Sidekiq pipelines, queue scaling, job parallelization. - API performance and throughput. - AI / LLM Systems: - Manage and optimize LLM deployments across cloud providers. - Improve latency, reliability, and cost through routing and system architecture. - Help build and maintain eval pipelines and A/B tests. - Contribute directly at the app level (prompts, agents, routing). - Support or prototype self-hosted model experiments (optional but valuable). The Ideal You: - 8+ years of experience in DevOps / infrastructure roles, ideally in fast-paced SaaS or startup environments. - Scaled production systems before and knows how systems behave under real load. - Comfortable deep in Kubernetes or writing Ruby/Python for quick scripts, tools or LLM eval. - Enjoys working on AI systems and has hands-on experience with LLM-powered applications. - Toolkit includes: Kubernetes, Docker; AWS, Azure, GCP ## Description Senior DevOps / Infrastructure & AI LLM Systems Engineer (Hybrid) Yuma AI (YC W23) - Join as our first dedicated DevOps/Infrastructure Engineer. This foundational role gives you full ownership of cloud infrastructure, deployments, reliability, and scaling. Over the past two years, we built a large amount of core tech, and the surface ahead is even larger as we scale usage, models, and automation. You will keep our platform fast, reliable, and ahead of the curve. What You Will Own: - Infrastructure & Platform: - All cloud infrastructure across AWS, GCP, and Azure. - Kubernetes cluster management, scaling, upgrades, and security. - CI/CD pipelines (GitHub Actions) and deployment systems. - Observability, monitoring, logging, alerting, and reliability practices. - Incident response, on-call rotation, and uptime improvements. - Cost optimization and infra-level performance tuning. - Security best practices, IAM, secrets, policies, and overall infra hygiene. - Backend & Data ## Related Videos - [Coffee with Developers: David Heinemeier Hansson](https://www.wearedevelopers.com/videos/875-coffee-with-developers-david-heinemeier-hansson) - [Reducing LLM Calls with Vector Search Patterns - Raphael De Lio (Redis)](https://www.wearedevelopers.com/videos/1714-reducing-llm-calls-with-vector-search-patterns-raphael-de-lio-redis) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Coroutine explained yet again 60 years later](https://www.wearedevelopers.com/videos/690-coroutine-explained-yet-again-60-years-later) - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) ## Related Articles - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs)