Uber

Sr. Staff Engineer (GenAI)

Remote, United States remote Entry Salary not listed
remote Technology & IT Curated
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About the role

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.
Ready to Ride?
This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.
You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.
Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.
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.

Interview prep

Walk in with sharper answers.

Use this as a quick practice sheet before you speak with the employer.

Role
Technology & IT Customer Service Operations Python Remote Collaboration remote

Likely questions

  1. Tell us about work you have done that is close to the Sr. Staff Engineer (GenAI) role.
  2. How would you approach your first 30 days at Uber?
  3. Which of Customer Service, Operations and Python have you used recently, and what did it help you achieve?
  4. Describe a time you solved a problem without waiting to be told exactly what to do.
  5. How do you stay organised and communicate clearly when working remotely?

Prepare before the call

  • A recent example that proves your experience with Customer Service, Operations and Python.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the Sr. Staff Engineer (GenAI) role because I can bring practical experience in Customer Service, Operations and Python, learn the team quickly, and contribute to the outcomes Uber needs from this hire.

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