LLMops Engineer

📋 Description

• Build and maintain operational tooling for LLM-powered systems, including prompt/pipeline
• Implement monitoring and observability for production LLM systems — tracking latency, token usage
• Design and run automated evaluation suites to catch regressions, hallucinations, and quality
• Manage RAG pipelines and vector store infrastructure, keeping retrieval sources fresh, accurate
• Implement safety and compliance guardrails — content filtering, PII redaction, and access controls
• Own cost governance for LLM usage: caching strategies, model routing, and usage reporting to keep

🎯 Requirements

• 4+ years of experience in a software engineering role, with a solid background in Backend
• Hands-on experience operating or supporting LLM-powered systems in production (via APIs, RAG
• Proficiency in a backend language such as Python, Java, TypeScript or Go, and familiarity with
• Experience implementing APIs, working with SQL and NoSQL databases, and writing automated tests
• Working knowledge of at least one cloud platform (AWS, GCP, or Azure), across both managed and
• Familiarity with infrastructure-as-code (e.g., Terraform) and CI/CD tooling (e.g., GitHub Actions

🎁 Benefits

• Work at the operational core of Coursera's AI transformation — solving problems that keep real
• Build hands-on expertise in one of the fastest-growing and most in-demand engineering disciplines
• Join a supportive, innovative team with a strong culture of continuous learning and improvement
• Be part of a mission-driven company transforming global access to education and upskilling in the