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Salary
$267k – $297k per year
Location
In office (San Francisco)
Seniority
Staff · 10+ years exp

Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Sep 11, 2026. Uber scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Uber is an American mobility and delivery company founded in San Francisco in 2009 that connects independent drivers and couriers with riders and customers through its apps. It operates ride hailing in thousands of cities, a food and grocery delivery business built on the same courier network, a freight brokerage matching shippers with carriers, and an advertising business that sells placement inside those apps. Listed on the New York Stock Exchange since 2019, the company reached sustained profitability in the mid 2020s and now partners with autonomous vehicle developers rather than building self-driving technology itself.

Sr. Staff Engineer (GenAI)

About the Role

Uber’s Customer Obsession team builds the platform and AI that powers world-class 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-to-end. Experience with agentic architectures is an important pre-requisite to be successful in this role. You’ll push the state of the art in GenAI for customer service-LLM orchestration, evaluation, safety guardrails, multilingual support, and real-time voice-while 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 ----

  • Own the end-to-end agent architecture: agentic planning and execution loops, long-term memory, persona/voice, knowledge routing, and policy enforcement for compliant, on-brand conversations.
  • 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-injection, jailbreak, PII redaction).
  • 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.
  • Establish evals that matter: offline rubrics, simulated scenarios, safety tests, cost/latency tradeoff suites, and LLM-as-judge (with calibrated human review) wired into CI/CD and experiment platforms.
  • 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.
  • Mentor/principal-lead multiple pods; set technical strategy and quality bars; coach senior engineers on agentic patterns, reliability, and experiment velocity.

---- Basic Qualifications ----

  • 10+ years building production ML/AI systems; 4+ years leading complex ML initiatives end-to-end.
  • Deep expertise in LLM-driven systems (inference optimization, prompt/program design, fine-tuning, distillation/LoRA, safety/guardrails, evals).
  • Strong software engineering in Python plus one of Go/Java/C++; hands-on with microservices, gRPC/HTTP, cloud infra, containers, CI/CD, and real-time telemetry/observability.
  • Demonstrated ownership of high-availability services (SLO/SLA design, incident response, on-call leadership, postmortems).
  • Track record of shipping customer-facing intelligent experiences with measurable impact (A/B testing, metrics literacy).

---- Preferred Qualifications ----

  • Agentic architectures in production (planner/executor, memory, multi-step reasoning) and RAG over complex, policy-heavy knowledge bases.
  • Experience building support automation for large consumer platforms (routing, policy codification, internal tooling, co-pilot/auto-resolve).
  • Multilingual NLU/NLG (code-switching, low-resource languages), hallucination mitigation, safety red-teaming, and privacy-by-design.
  • Practical expertise balancing speed and reliability at scale: experiment frameworks, feature flags, canary/guarded rollouts, and clear kill-switches.

For San Francisco, CA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 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.

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