Sr. Staff Engineer, AI

About the Role

Uber\u2019s Customer Obsession team builds the platform and AI that powers world\u2011class support across mobile, web, and voice at global scale. We are now hiring a Senior Staff Engineer to architect, productionize, and scale an autonomous support agent that resolves customer issues end\u2011to\u2011end. Experience with voice agents and agentic architectures is a major plus. You\u2019ll push the state of the art in GenAI for customer service\u2014LLM orchestration, evaluation, safety guardrails, multilingual support, and real\u2011time voice\u2014while holding a very high bar for reliability and cost efficiency. We are still at an early stage and value candidates with bias for action who get creative with GenAI tools to accelerate execution and experimentation.

What the Candidate Will Need / Bonus Points

---- What the Candidate Will Do ----

1. Own the end\u2011to\u2011end agent architecture: agentic planning and execution loops, long-term memory, persona/voice, knowledge routing, and policy enforcement for compliant, on\u2011brand conversations.
2. Ship production systems that handle millions of conversations with rigorous SLOs, fallbacks, and canaries; design graceful degradation (e.g., human handoff) and safety guardrails (prompt\u2011injection, jailbreak, PII redaction).
3. Lead voice agent initiatives: Drive the development of Uber\u2019s voice support agent\u2014covering real-time speech recognition (ASR), text-to-speech, natural turn-taking (barge-in and endpointing), and reliable telephony/WebRTC integration. Ensure low-latency, high-quality interactions that remain robust even in noisy environments.
4. Advance retrieval & reasoning: Build next-generation retrieval and reasoning pipelines, where the agent can search across different knowledge sources, apply policy-driven tools, and call structured workflows and ensure that responses are consistently grounded.
5. Establish evals that matter: offline rubrics, simulated scenarios, safety tests, cost/latency tradeoff suites, and LLM\u2011as\u2011judge (with calibrated human review) wired into CI/CD and experiment platforms.
6. Drive automation at scale: partner with Product/Design/Operations on coverage, policy alignment, localization, and rollout strategy to better customer experience and reduce cost per contact.
7. Mentor/principal\u2011lead multiple pods; set technical strategy and quality bars; coach senior engineers on agentic patterns, reliability, and experiment velocity.

---- Basic Qualifications ----

1. 10+ years building production ML/AI systems; 4+ years leading complex ML initiatives end\u2011to\u2011end.
2. Deep expertise in LLM\u2011driven systems (inference optimization, prompt/program design, fine\u2011tuning, distillation/LoRA, safety/guardrails, evals).
3. Strong software engineering in Python plus one of Go/Java/C++; hands\u2011on with microservices, gRPC/HTTP, cloud infra, containers, CI/CD, and real\u2011time telemetry/observability.
4. Demonstrated ownership of high\u2011availability services (SLO/SLA design, incident response, on\u2011call leadership, postmortems).
5. Track record of shipping customer\u2011facing intelligent experiences with measurable impact (A/B testing, metrics literacy).

---- Preferred Qualifications ----

1. Voice agent background (ASR/TTS streaming, barge\u2011in, endpointing, telephony, WebRTC) and conversational quality/NLP evaluation. Patterns seen in peer roles emphasize speech + dialog quality as core skills.
2. Agentic architectures in production (planner/executor, memory, multi\u2011step reasoning) and RAG over complex, policy\u2011heavy knowledge bases.
3. Experience building support automation for large consumer platforms (routing, policy codification, internal tooling, co\u2011pilot/auto\u2011resolve).
4. Multilingual NLU/NLG (code\u2011switching, low\u2011resource languages), hallucination mitigation, safety red\u2011teaming, and privacy\u2011by\u2011design.
5. Practical expertise balancing speed and reliability at scale: experiment frameworks, feature flags, canary/guarded rollouts, and clear kill\u2011switches.

For San Francisco, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 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. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/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.