AI Architect

Position: AI Knowledge Architect
About the Role

The AI Knowledge Architect (customer support) role sits within the Global Digital Experience (GDX) team and is responsible for building and maintaining the knowledge portion of the brain of our customer-facing AI agents. You will develop the knowledge needed by LLMs to craft empathetic responses, design conversational logic, and provide business context that allow our AI agents to respond against complex customer problems autonomously.

You will be the connector between expressed customer requests, support policies and customer data and convert these into intuitive, empathetic and brand-aligned AI responses.

Your role requires a combination of skills - precision of a Technical Writer, empathy of a UX Designer, and the logic of a Prompt Engineer.

Your role starts with writing articles but extends to structuring knowledge so an AI agent can reason, retrieve, and act upon it accurately.

This role sits at the intersection of Community Operations (Comm Ops) and Customer Obsession (CO) Product. You will work closely with Comm Ops frontline teams to deeply understand their customer requirements and collaborate with engineering and product teams to build knowledge that optimizes segmented customer experience.

What the Candidate Will Do

* AI Knowledge authoring:
Author and structure prompt-aware content for AI agents to ensure the AI provides accurate, empathetic responses without hallucinations. Decide where the AI does not need any additional content, where it needs some context, where it can pull data from upstream systems for context and where it needs a lot of details, and tailor knowledge accordingly. Incorporate tribal knowledge from various parts of Uber into the knowledge base to ensure the AI agents are able to respond to customer queries effectively.

* AI Information architecture:
Ensure the content provided to the AI agents are relevant, accurate, updated, non-conflicting and succinct. Identify gaps in content leading to AI agents not being able to help customers or providing wrong responses and fix those quickly. Ensure easy knowledge access for AI agents (e..g., clean up metadata where needed, improve vector match probabilities, decide how to chunk knowledge so that retrieval is highly accurate and efficient from a latency and cost perspective).

* AI Performance Tuning and standards improvement:
Analyze failed AI conversations to identify knowledge gaps, then update documentation or metadata to improve future performance. Use your knowledge of the Tech stack to ensure retrieval accuracy is high and AI responses are crafted according to segmentation requirements and decision logic. Provide feedback to the Global Content team to improve content standards in case they are hindering the delivery of good responses.

* Product Thinking:
Provide feedback to product and Engineering teams to improve prompts to effectively leverage AI knowledge and on platform enhancements needed for authoring effective AI knowledge. Operate in an agile fashion to adapt knowledge to Technology and product advancements in a rapidly changing AI ecosystem.

* Experiment with Knowledge options:
Lead the product and use case evolution to better response patterns by experimenting with options to decide what amount of deterministic knowledge inputs is necessary and where to depend on LLM reasoning.

* Cross-functional Partnership:
Engage deeply with Comm Ops teams to identify customer experience needs and usability requirements for AI agents and address them through knowledge improvements. Engage with the Global Content team to ensure content standards, tone of voice and strategy is adhered to. Engage with Legal teams where relevant to get relevant approvals for the knowledge created.

Basic Qualifications

* 8+ years of experience in Technical Writing, Information Architecture, Conversation Design, or Product Operations

* 1+ year of demonstrated hands-on work with AI Knowledge

Preferred Qualifications

* Experience of working with leading LLMs (e.g., GPT-4, Claude, Gemini) and Gen AI concepts like RAG, Agentic AI, chain-of-thought prompting, decision flows, AI reasoning, etc

* Excellent collaboration skills with both…