Principal Software Engineer; Agentic​/MCP - Boston, MA - Hybrid

Company Description

At Red Hat, we connect an innovative community of customers, partners, and contributors to deliver an open source stack of trusted, high-performing solutions. We offer cloud, Linux, middleware, virtualization, and AI technologies, together with award-winning global customer support, consulting, and implementation services. Red Hat is a rapidly-growing company supporting more than 90% of Fortune 500 companies.

At Red Hat, our commitment to open source innovation extends beyond our products - it’s embedded in how we work and grow. Red Hatters embrace change – especially in our fast-moving technological landscape – and have a strong growth mindset. That's why we encourage our teams to proactively, thoughtfully, and ethically use AI to simplify their workflows, cut complexity, and boost efficiency.

This empowers our associates to focus on higher-impact work, creating smart, more innovative solutions that solve our customers' most pressing challenges.

Red Hat’s Global Engineering team is looking for a Principal Software Engineer to join the Agentic and AI Engineering Tools team. In this role, you’ll contribute directly to Red Hat’s rapidly growing AI/ML family of products and will be responsible for the design, development, and refinement of software adding features that enable agents to achieve enterprise readiness.

The ideal candidate will have a proven background in developing robust and scalable code. As part of your responsibilities, you will need to adhere to coding best practices and standards, including well-documented, and efficient code; building and implementing upstream unit and E2E automated tests, maintaining updated code documentation and comments, following security best practices, participating in code reviews and other peer review in upstream projects, and staying up-to-date with software engineering technologies, frameworks, and methodologies.

• Architect and develop a platform for Agentic AI applications.
• Collaborate with Staff Engineers, Engineering, Product Management, and User Experience to define customer needs and use cases.
• Collaborate with Quality Engineers to develop and implement comprehensive unit, integration, and end-to-end tests to guarantee the reliability and performance in the upstream project, maintaining CI/CD workflows in Git Hub, and ensuring downstream quality.
• Participate in AI-assisted code reviews, utilizing tools that provide real-time feedback, identify potential bugs, security vulnerabilities, and adherence to coding standards, contributing to a more thorough and efficient review process.
• Proactively utilize AI-assisted development tools (e.g., Git Hub Copilot, Cursor, Claude Code) for code generation, auto-completion, and intelligent suggestions to accelerate development cycles and enhance code quality.
• Create and maintain clear, concise upstream technical documentation including API references and user guides and collaborating with our internal tech writers to create robust downstream documentation.

• 10+ years of advanced Python development experience,
• Advanced knowledge designing robust and scalable software used in highly scaled and performant Distributed Systems
• Experience with building agents, agentic workflows, or developing with LLMs
• Knowledge of Kubernetes/Open Shift and operational knowledge building/deploying containers.
• Experience creating automation for Git Hub, using Git Hub Actions or related continuous integration tools.
• Experience developing, deploying or maintaining On-prem or Cloud Infrastructure
• Advanced knowledge developing unit, functional, and end-to-end (E2E) test cases and automation
• Ability to quickly learn and use new tools and technologies.

• Experience with open source projects.
• Experience with Security, Observability, Performance or Scale.
• Understanding of Dev Ops methodology, scrum, and/or Jira.
• Experience with AI and Machine Learning platforms, tools, and frameworks, such as MLFlow, Llama Stack, Lang Chain, PyTorch, LLaMA.cpp, vLLM, Lang Graph, and Kubeflow.
• Bachelors or Masters degree in computer science or related discipline.

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