Yuma AI - Senior DevOps / Infrastructure & AI LLM Systems Engineer (Hybrid)
Requirements
• fast-paced SaaS or startup environments. • You’re equally comfortable deep in Kubernetes or writing Ruby/Python for a quick script, tool or LLM eval. You care about reliability, speed and pragmatism. You enjoy working on AI systems and have hands-on experience with LLM-powered applications. • comfortable deep in Kubernetes or writing Ruby/Python • Your toolkit includes: • Kubernetes, Docker • AWS, Azure, GCP (strong in at least 2) • GitHub Actions CI/CD • LLM APIs (OpenAI, Azure, Anthropic; self-hosted a plus) • Terraform or similar IaC • Strong coding ability to contribute across the stack • The Alternative You : • If you're earlier in your career but have strong infrastructure experience and clear upside, and you can reasonably grow into the full scope within 2 to 3 years, feel free to reach out. Raw talent is welcome, but depth of experience scaling systems is a big plus here. • Why Yuma ? • Why Yuma ? • High impact with ownership from day one : join a small, international engineering team where every feature you ship and every solution you design is directly visible in production. • High impact with ownership from day one • Competitive compensation based on experience and stock options
Responsibilities
• 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 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 : • You have 8+ years of experience in DevOps / infrastructure roles, ideally in fast-paced SaaS or startup environments. You’ve scaled production systems before and know how systems behave under real load. • You’re equally comfortable deep in Kubernetes or writing Ruby/Python for a quick script, tool or LLM eval. You care about reliability, speed and pragmatism. You enjoy working on AI systems and have hands-on experience with LLM-powered applications. • Your toolkit includes: • Kubernetes, Docker • AWS, Azure, GCP (strong in at least 2) • GitHub Actions CI/CD • LLM APIs (OpenAI, Azure, Anthropic; self-hosted a plus) • Terraform or similar IaC • Strong coding ability to contribute across the stack • The Alternative You : • If you're earlier in your career but have strong infrastructure experience and clear upside, and you can reasonably grow into the full scope within 2 to 3 years, feel free to reach out. Raw talent is welcome, but depth of experience scaling systems is a big plus here. • High impact with ownership from day one : join a small, international engineering team where every feature you ship and every solution you design is directly visible in production. • Competitive compensation based on experience and stock options • Fast growth = fast learning curve : in this hybrid engineering role, you’ll quickly gain exposure to AI, product iteration, customer workflows, and cross-functional problem-solving • Work closely with founders and product/engineering leadership : your ideas and your ownership will directly influence the roadmap. • A culture of ownership, transparency, and continuous improvement : we move fast, iterate constantly, and empower people to grow • Flexibility : fully remote in Europe with preference for Barcelona office (Boston office is also an option) • Please, if you are considering applying, first read our culture page: https://www.notion.so/yuma-ai/Yuma-s-Culture-5b0e15f1334242ce8a62daab9f2038a1?pvs=4
Benefits
• stock options • Fast growth = fast learning curve : in this hybrid engineering role, you’ll quickly gain exposure to AI, product iteration, customer workflows, and cross-functional problem-solving • Fast growth = fast learning curve : • Work closely with founders and product/engineering leadership : your ideas and your ownership will directly influence the roadmap. • Work closely with founders and product/engineering leadership • A culture of ownership, transparency, and continuous improvement : we move fast, iterate constantly, and empower people to grow • ownership, transparency, and continuous improvement • Flexibility : fully remote in Europe with preference for Barcelona office (Boston office is also an option) • Flexibility • OUR CULTURE • OUR CULTURE • Please, if you are considering applying, first read our culture page: https://www.notion.so/yuma-ai/Yuma-s-Culture-5b0e15f1334242ce8a62daab9f2038a1?pvs=4
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