Jobs
About the Role:
Uber's Developer Platform is in the middle of a paradigm shift. The industry moved from text editors to IDEs. We're now moving from IDEs to Agentic Dev Environments (ADEs), where AI agents are first-class participants in the software development lifecycle.
The AI Foundations & Developer Experience (AIFX) team is building the infrastructure that makes this shift real.
We own:
The agent runtime. Claude Code, Codex, and Minions, our background agent orchestration system for autonomous code generation.
The MCP platform layer. Giving agents structured access to Uber's tools, data, and developer lifecycle.
The Skill Marketplace. Encoding tribal knowledge into loadable, composable expertise so any engineer can be instantly productive in any monorepo.
We're hiring engineers who think in systems, not features. You'll own foundational pieces of Uber's agentic infrastructure. Getting it right means every team at Uber ships faster.
---- What the Candidate Will Do ----
Design and ship the skill pack framework. How skills are authored, versioned, distributed, and loaded across Go, Java, Python, iOS, Android, and Web monorepos. Skills are the differentiator: portable expertise that makes any agent instantly productive.
Build the multi-agent runtime inside Uber's Dev Pod cloud environments. Persistent background agents, swarm orchestration, cross-agent context passing. Agents working 24/7 in parallel, not one-shot interactions.
Develop AI-powered code intelligence. Semantic code search, dependency-aware context, codebase understanding that gives agents deep structural knowledge (not just text search).
Own and evolve the MCP platform layer. Consolidating code-mcp, docs-mcp, and developer lifecycle MCPs into a unified, low-latency context infrastructure that agents actually depend on.
Partner with Code Infra, Dev Pod, Mobile Platform, Web Platform, and Backend Platform teams to ship the foundational systems that make agentic engineering work at Uber's scale. ~5K microservices, 6 monorepos, 5,000+ engineers.
Set technical direction for agentic infrastructure across Uber's Developer Platform. Define the architecture, verification frameworks, and trust models for agent-generated code at org scale.
Mentor engineers in agentic fluency. Raise the bar on how teams think about, build with, and ship through AI agents.
---- Basic Qualifications ----
Experience building and scaling developer tooling or platform infrastructure (e.g., SDKs, CLIs, APIs, runtime systems) in large-scale engineering environments
Strong proficiency in at least one major programming language (Go, Java, Swift, Kotlin, Python, or TypeScript) with demonstrated experience integrating AI/ML models into developer workflows
System design experience for high-reliability, observable, developer-facing services and agentic systems
---- Preferred Qualifications ----
Experience building and scaling developer tooling or platform infrastructure (e.g., SDKs, CLIs, APIs, runtime systems) in large-scale engineering environments
Strong proficiency in at least one major programming language (Go, Java, Swift, Kotlin, Python, or TypeScript) with demonstrated experience integrating AI/ML models into developer workflows
System design experience for high-reliability, observable, developer-facing services and agentic systems
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For San Francisco, CA-based roles: The base salary range for this role is USD**$267,000 per year**
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USD**$297,000 per year**.
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For Seattle, WA-based roles: The base salary range for this role is USD**$267,000 per year**
-
USD**$297,000 per year**.
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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. More details can be found at the following link https://jobs.uber.com/en/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.
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About Uber

Uber
PublicUber develops, markets, and operates a ride-sharing mobile application that allows consumers to submit a trip request.
10,001+
Employees
San Francisco
Headquarters
$120B
Valuation
Reviews
3.7
10 reviews
Work-life balance
3.2
Compensation
4.0
Culture
4.1
Career
3.4
Management
2.8
68%
Recommend to a friend
Pros
Good compensation and pay
Flexible hours and schedule
Great team culture and colleagues
Cons
Long hours and tight deadlines
High pressure and stressful environment
Poor management and lack of support
Salary Ranges
15,354 data points
Mid/L4
Mid/L4 · Data Analyst
3 reports
$209,300
total per 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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