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AI Agentic Operations
Mexico City, Mexico; Santiago, Chile; São Paulo, Brazil
·
On-site
·
Full-time
·
4d ago
About the Role
Global Intelligent Operations (GiO) is building the intelligence and automation capabilities that enable Uber to operate at scale with increasing autonomy. As AI Agentic Operations,you will own how insights translate into action across Operations by designing, rolling out, and scaling agentic workflows that automate or augment operational work.
This role focuses on the operationalization of agentic systems**. You will define how agents are orchestrated, how decision loops are structured, and how human oversight and guardrails are embedded so these systems are reliable, safe, and scalable. Your work ensures agentic solutions move beyond experiments and into sustained, day-to-day use across teams.**
This role sits at the intersection of Operations, Product, Engineering, and AI teams, and is ideal for someone who understands how complex systems behave in the real world.
- What You'll Do
- Design agentic workflows:** Define how insights, signals, and recommendations trigger automated or assisted actions in Ops workflows.- Own orchestration and decision loops: Establish patterns for agent coordination, escalation, retries, and human-in-the-loop oversight.- Operationalize agentic systems: Partner with Product, AI/ML Engineering, and Ops teams to move agentic solutions from pilot to production.- Set reliability and safety standards: Define guardrails, monitoring, and fallback mechanisms to ensure agentic systems behave predictably and responsibly.- Drive adoption and scale: Work with Ops teams to embed agentic solutions into existing processes and ensure sustained usage.- Measure impact: Track outcomes such as reduced manual effort, faster decision cycles, and improved execution quality.**
- What You'll Need
- 3+ years of experience in operations, product operations, strategy & ops, automation, or a similarly execution-focused role.
- Demonstrated interest in AI systems and modern analytics, with the curiosity and discipline to keep up with a fast-moving AI landscape through reading, experimentation, and practical application.
- Experience owning or scaling complex workflows that involve automation, decision logic, or AI-enabled systems.
- Working experience with coding or analytical tools (e.g., Cursor, Python, notebooks, or similar) and comfort getting hands-on when needed.
- technical fluency and comfort partnering closely with Product, Data, and AI/ML Engineering teams.
- Proven ability to lead cross-functional initiatives in ambiguous environments.
- Strong communication skills, with the ability to translate complex systems into clear operational guidance.
Preferred Qualifications:
- Experience working with agentic systems, automation platforms, or decision engines.
- Familiarity with human-in-the-loop design, monitoring, and governance models.
- Comfort working across regions or globally distributed teams
- Analytical mindset with the ability to define and interpret operational success metrics.
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 fuelds progress. What moves us, moves the world - let's move it forward, together.
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.
Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.
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About Uber
Reviews
3.1
10 reviews
Work Life Balance
4.2
Compensation
2.3
Culture
3.5
Career
2.0
Management
2.5
45%
Recommend to a Friend
Pros
Flexible hours and schedule
Meeting different people and cultures
Make your own hours
Cons
Inconsistent and low pay
Safety concerns with passengers
Traffic and difficult drivers
Salary Ranges
23,534 data points
Mid/L4
Mid/L4 · Data Analyst
3 reports
$209,300
total / year
Base
$161,000
Stock
-
Bonus
-
$203,580
$209,300
Interview Experience
5 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer Rate
40%
Experience
Positive 80%
Neutral 20%
Negative 0%
Interview Process
1
Application Review
2
Online Assessment
3
Recruiter Screen
4
Technical Phone Screen
5
Case Study/Analytics Test
6
Final Loop/Panel Interview
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Case Study
Technical Knowledge
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