Software Engineer AI Context Engineering

Job description

**About the Role:** The Red Hat Advanced Cluster Management (ACM) team is looking for a Software Engineer to help build and evolve enterprise-grade cloud-native platform products for Kubernetes and hybrid cloud environments. This is a platform product engineering role focused on designing, developing, and delivering core product capabilities that enable customers to manage Kubernetes clusters at scale. The role is centered on building reusable platform components, APIs, controllers, operators, and multicluster management capabilities that become part of Red Hat''s product portfolio. You will work on foundational capabilities including multicluster orchestration, placement, governance, policy management, GitOps integration, and cluster lifecycle management. In addition, you will help pioneer AI-native software engineering practices through context engineering, AI-assisted development workflows, and agentic software development lifecycle initiatives. You will collaborate with globally distributed engineering teams across North America, Europe, and APAC while contributing to Open Cluster Management (OCM), a CNCF Sandbox project, and the broader Kubernetes and CNCF open source ecosystem. **What You''ll Do :** **Platform Product Engineering** - Design, develop, and maintain core product capabilities for Red Hat''s multicluster management platform using Go (Golang), Kubernetes, and distributed systems technologies. - Build cloud-native platform services, APIs, controllers, operators, and control-plane components that enable enterprise-scale Kubernetes management. - Design scalable and reusable platform features that address broad customer needs and become part of the product roadmap. - Participate in reviews, technical design discussions, code reviews, testing, debugging, and continuous product improvement initiatives. **AI Context Engineering Developer Productivity** - Design, optimize, and orchestrate context-building strategies for Large Language Models (LLMs) to improve software engineering workflows. - Build and enhance context pipelines, context harnesses, and evaluation mechanisms that improve the accuracy, determinism, and effectiveness of AI-generated outputs. - Contribute to the evolution of an Agentic Software Development Lifecycle (SDLC) through intelligent agents, autonomous workflows, and AI-native engineering practices. - Apply context engineering techniques to ensure AI tools generate context-aware, reliable, and high-quality software artifacts. - Evaluate and leverage AI-assisted development tools to improve developer productivity, engineering velocity, and software quality. - Help establish best practices for integrating AI into modern software development workflows. **Open Source Engineering** - Actively contribute to Open Cluster Management (OCM) and related Kubernetes and CNCF ecosystem projects.. **What You''ll Bring:** - 3+ years of software engineering experience building platform products, infrastructure software, cloud-native platforms, or distributed systems. - 1+ year of hands-on experience in AI context engineering, context orchestration, prompt engineering, retrieval optimization, or AI-native developer workflows. - Practical experience using AI-assisted development tools such as Claude Code, Gemini Code Assist, GitHub Copilot, Cursor, Aider, Continue, or similar platforms. - Experience with either Go (Golang) development or Kubernetes platform technologies. - Strong understanding of distributed systems, APIs, microservices, and cloud-native architecture principles. - Strong analytical, debugging, troubleshooting, and problem-solving skills. - Familiarity with modern software engineering practices including CI/CD, automated testing, observability, and Agile development methodologies. - Strong communication and collaboration skills with the ability to work effectively in globally distributed teams. - Passion for platform engineering, open source development, and emerging AI technologies. **The follwing are considered as a plus:** - Experience building or extending AI-powered developer tools, coding assistants, software engineering agents, or autonomous development workflows. - Familiarity with Context Engineering concepts including context construction, retrieval strategies, context optimization, prompt orchestration, context harnesses, evaluation frameworks, and techniques for improving LLM reliability and determinism. - Experience designing, evaluating, or operationalizing AI-assisted software development workflows. - Understanding of prompt engineering, agent frameworks, tool-calling patterns, memory systems, and AI workflow orchestration. - Experience improving developer productivity through AI-enabled workflows, agentic SDLC practices, or developer experience initiatives. - Familiarity with Kubernetes platform development, including Operators, Controllers, CRDs, controller-runtime, reconciliation patterns, or multicluster management concepts. - Experience developing software in Go (Golang) and building cloud-native platform capabilities, distributed systems, or infrastructure software. - Experience with multicluster management, fleet orchestration, governance, or policy management platforms. - Contributions to open source projects, CNCF ecosystem initiatives, Kubernetes-related projects, AI tooling communities, or other community-driven software efforts are a strong plus. #LI-AK1