Principal Software Engineer, Enterprise AI Platform

GitHub is looking for a Principal Software Engineer to define and build the foundational systems for its Enterprise AI Platform. The role sits at the intersection of distributed systems, AI and agent platforms, developer tooling, identity, policy, and platform architecture: you will shape how AI agents operate safely and consistently across IDEs, CLI, MCP, long-running agents, and future Copilot experiences. This is a highly strategic, high-ambiguity role with broad technical influence across Copilot, platform infrastructure, client experiences, identity, billing, and enterprise products, defining platform primitives that shape enterprise AI adoption for millions of developers and tens of thousands of organizations.

Responsibilities

• Define the Enterprise AI control plane architecture: drive the technical direction for a unified control plane spanning models, agents, tools, MCP, permissions, spend, plugins, and client settings, with policy authored once and enforced consistently everywhere.
• Build foundational platform primitives: scalable policy engines, governance SDKs, client-side enforcement frameworks, and extensible schemas for agentic workflows.
• Drive cross-client consistency, partnering across Copilot CLI, IDE, agent, and platform teams to standardize policy enforcement through reusable APIs, contracts, and SDK patterns.
• Solve hard distributed systems problems at scale: reliable, secure, resilient systems for policy evaluation, spend enforcement, permissions, auditability, and observability.
• Influence GitHub's AI platform strategy, partnering with engineering and product leaders on the long-term enterprise AI roadmap and cross-organizational alignment.
• Raise the engineering bar, mentoring senior engineers and elevating architectural rigor and systems thinking across teams.

Qualifications

• 11+ years of software engineering experience delivering production software in languages such as C, C++, C#, Java, JavaScript, Go, Ruby, Rust, or Python (less with a relevant degree, or equivalent experience).
• Deep experience building and operating large-scale distributed systems or platform infrastructure.
• Strong expertise designing scalable systems across APIs, identity, policy engines, security, reliability, and infrastructure platforms.
• Demonstrated success driving architecture, platform adoption, and alignment across multiple teams, with a track record of influence without authority.
• Comfort operating in ambiguity and fast-moving environments, balancing long-term platform investments with pragmatic execution.
• Preferred: background in AI/LLM systems, agentic platforms, developer tooling, governance systems, enterprise software, or cloud-native systems (Azure, Kubernetes, AKS).