Principal Engineer, Technical Content Experience Team (TCX)

Technical Direction For AI-First Content Platform

Define the technical direction for a 60-person engineering organization building the AI-first content platform for AWS documentation — one of the most visited technical documentation sites in the world. You'll work across six engineering teams spanning content management, publishing infrastructure, content automation, AI/ML, knowledge graphs, and content delivery to drive architectural coherence and make the hard technical bets that determine whether this platform succeeds. The fundamental question you'll help answer: in an era where developers increasingly interact with AI agents instead of reading documentation, what should a content platform actually be? The answer isn't obvious, and it's changing fast. You'll operate in a space where the right architecture depends on assumptions about AI capabilities 2–3 years out, where you're balancing a live production system serving millions of users against a platform transformation, and where the technical decisions have direct product implications. This is a role for an engineer who wants to shape how a large organization navigates a genuine technology inflection point — not incrementally improving an existing system, but figuring out what the system should become.

Key job responsibilities:

• Set technical direction across six engineering teams, ensuring architectural decisions compound rather than conflict
• Make high-judgment calls on build-vs-integrate-vs-deprecate for systems spanning content management, publishing, AI agents, knowledge graphs, and automation
• Drive resolution of cross-cutting technical problems that no single team owns — data flow architecture, API contracts, platform boundaries, migration strategy
• Evaluate and de-risk the organization's technical bets on AI, particularly around agentic content operations and autonomous workflows
• Raise the engineering bar across the organization through design reviews, mentorship, and establishing technical standards
• Represent TCX Engineering's technical perspective to senior leadership and partner organizations

A day in the life:

Our morning might start with a design review for the knowledge graph team's approach to ingesting content metadata — you'll need to assess whether their schema will support the agentic search use cases the AI team is planning for Q3, or whether they're building something that will need to be reworked. After that, you're working through the architectural implications of a partner team's integration proposal that would change how API reference documentation flows through the platform. After lunch, you're in a room with the publishing and content platform leads working through a disagreement about where content validation should live in the architecture. Both teams have reasonable positions. You need to make a call that accounts for the current system constraints, the target architecture, and the migration path between them — and then clearly communicate the rationale so both teams can execute. You'll also spend time on the harder strategic questions. The organization is betting that AI agents will handle most routine content operations within 2–3 years. What does that mean for the systems we're building today? How do you architect for a future where the primary consumers of your APIs are AI agents, not humans? These aren't theoretical questions — they drive real resource allocation and design decisions every quarter.

About the team:

TCX Engineering builds and operates the infrastructure behind AWS documentation — the website, publishing systems, content automation, AI authoring tools, and the knowledge graph that connects it all. We serve millions of developers and are in the middle of a significant platform transformation driven by AI. The organization has six engineering teams, each led by a strong L6 engineer or manager. What's missing is a principal engineer who can look across all six teams and drive technical coherence. Today, each team makes sound local decisions, but the cross-cutting architectural questions — how data flows between systems, where platform boundaries should be, which components to consolidate versus keep separate — need dedicated senior technical leadership. The technical landscape is genuinely interesting. We operate at the intersection of content management, publishing infrastructure, knowledge graphs, and applied AI. Our systems range from traditional build pipelines processing XML documentation to AI agents that generate API reference documentation from service models. The challenge is evolving this heterogeneous landscape into a coherent platform while keeping production systems running and delivering incremental value along the way. We value engineers who form strong technical opinions based on evidence, communicate them clearly, and change their minds when presented with better information.