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 (CommOps) and Customer Obsession (CO) Product. You will work closely with CommOps 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 CommOps 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 technical (e.g., product managers, engineers, data scientists, and UX teams) and non-technical stakeholders
- Systems thinking, especially ability ejhgcto identify downstream implications of knowledge gaps and judgment around edge cases, ambiguity, and exception handling
- Strong business acumen and customer understanding; exposure to cognitive sciences is a plus
- Analytical mindset with attention to precision and clarity; ability to read latency and accuracy logs to see where the AI "got lost" in the knowledge base
- Understanding of semantic precision in the AI context
- Ability to thrive in a fast-paced, ambiguous environment
- Experience in Operations or program management is a plus
- Experience of working on human-computer interactions is a plus
- Exceptional verbal communication skills
- Familiarity with SQL, Python, JSON, etc is a plus
For San Francisco, CA-based roles: The base salary range for this role is USD$162,000 per year - USD$180,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$162,000 per year - USD$180,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.