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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 voice agents and agentic architectures is a major plus. 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.
Job Responsibility:
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)
Lead voice agent initiatives: Drive the development of Uber’s voice support agent—covering real-time speech recognition (ASR), text-to-speech, natural turn-taking (barge-in and endpointing), and reliable telephony/WebRTC integration
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
Requirements:
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