The Command Line Assistant (CLA) team (powered by RHEL Lightspeed) is hiring a Software Engineer to build AI-powered RHEL experiences—shipping production software while engineering the quality, reliability, and evaluation signals that make AI verifiable and production-ready for real-world system administration. The RHEL command line assistant provides an optional AI enabled assistant which is available from the RHEL command line. It uses a natural language interface to answer RHEL-related questions, help with troubleshooting, and can be used as a learning aid.
What You’ll DoBuild and maintain production-grade software (tools, services, libraries, CLIs) that improves CLA behavior and operational reliability.
Implement automation and evaluation systems: test frameworks, harnesses, data generators, and CI quality gates that scale with the product.
Define and run validation across unit, integration, system, performance, and other non-functional checks.
Triage and debug failures across product code, test code, CI pipelines, environments, and integrations; drive root-cause fixes and targeted improvements.
Improve testability and observability by adding diagnostics, structured logs, metrics, and troubleshooting hooks in the codebase.
Own CI/CD validation workflows (e.g., tmt/fmf, Testing Farm) and improve signal quality (flake reduction, regression prevention).
Participate in open source development: upstream work, reviews, proposals, and contributions where appropriate.
Engage with Fedora and community workflows (as relevant) to validate early changes and strengthen upstream/downstream feedback loops.
Document results and present findings to stakeholders.
3+ years of software engineering experience with strong emphasis on automation, debugging, and maintainable systems.
2–3 years strong experience with Python (pytest preferred) and writing testable, well-structured code.
Experience in Linux/RHEL environments and system-level troubleshooting (logs, processes, basic networking).
Practical experience with CI/CD pipelines, code review, and version control (Git).
Experience with AI/ML technologies such as foundational frameworks, large language models (LLMs), Retrieval Augmented Generation (RAG) paradigms, embedding models, vector databases, CLI assistants.
Clear written and verbal communication; effective in distributed work across time zones.
The following are considered a plus:
Exposure to AI/ML evaluation concepts, or interest in applying QE methods to AI-enabled systems.
Experience designing LLM evaluations for production.
Knowledge of RHEL release workflows and enterprise testing cycles. Experience with RPM-based distributions and packaging basics.
Familiarity with LLM-enabled CLI assistants (i.e Goose).
Engineering experience with Gemini on Vertex AI (prompting, model parameter tuning for reliability, safety settings, structured outputs/function calling) and understanding how these impact determinism, latency, and CI stability.
Familiarity with Fedora, upstream/downstream practices, and community contribution processes.
Familiarity with virtualization and containerization.
Rust experience (or interest), especially for CLI/tooling.
Familiarity with Ansible or similar automation for provisioning/test environments.
About Red Hat
Red Hat is the world’s leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. Spread across 40+ countries, our associates work flexibly across work environments, from in-office, to office-flex, to fully remote, depending on the requirements of their role. Red Hatters are encouraged to bring their best ideas, no matter their title or tenure. We're a leader in open source because of our open and inclusive environment. We hire creative, passionate people ready to contribute their ideas, help solve complex problems, and make an impact.
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