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Staff Software Engineer_Search platform_AI

Uber

Staff Software Engineer_Search platform_AI

Uber

Bangalore, India

·

On-site

·

Full-time

·

4d ago

About the Role

This is a pivotal leadership role toredefine the future of search and knowledge access at Uber**. We are looking for a visionary Staff Engineer and Tech Lead to spearhead the evolution of our internal search platform, transforming it from a traditional information retrieval tool into a conversational, intelligent, and action-oriented experience.**
Your primary mission will be to architect a world-class search ecosystem for all Uber employees. This requires a dual-pronged technical strategy: leading the in-house development of novel AI components while also conducting deep evaluations of cutting-edge third-party solutions. You will be the key technical decision-maker on when to build and when to integrate.

As a Tech Lead, you will be responsible for the high-level technical architecture, the strategic roadmap, and the leadership of a talented team of engineers. You will set the technical vision, mentor your team architecting critical systems and integration points. This is a unique opportunity to own the strategy for a mission-critical platform and leverage the entire AI landscape-both internal and external-to deliver profound impact.

---- What the Candidate Will Do ----

  1. Architect the Ecosystem: Design and own the technical vision for Uber's next-generation enterprise search platform, creating a cohesive strategy that integrates first-party AI models with best-in-class third-party technologies.2. Lead AI Implementation: Drive the exploration and implementation of advanced AI capabilities. This includes architecting conversational interfaces, enabling multi-step reasoning, and bringing agentic AI functionalities to our users, whether through in-house development or strategic integration.3. Make Critical Build-vs-Buy Decisions: Conduct deep technical evaluations of industry-leading AI solutions. You will own the process of vetting vendors, prototyping integrations, and providing clear recommendations to leadership.4. Lead and Mentor: Lead a world-class team of software and machine learning engineers. Provide technical guidance, conduct architectural reviews, and foster a culture of innovation and engineering excellence.5. Build and Integrate: Remain hands-on, writing production-quality code for critical custom components, integration layers, and core platform infrastructure.6. Collaborate and Influence: Work closely with senior leadership, product managers, and stakeholders across the company to define the roadmap and ensure your team's work aligns with Uber's strategic goals.

---- Basic Qualifications ----

  1. Bachelor's degree in Computer Science, Machine Learning, a related technical field, or equivalent practical experience.
  2. 8+ years of professional experience in software engineering, with a proven track record of shipping complex.
  3. Strong programming proficiency in Python and experience with systems programming languages (e.g., Go, Java, C++).
  4. Significant experience in designing and building production systems leveraging machine learning, especially in Search, NLP, or Conversational AI.
  5. 2+ years of experience in a technical leadership role, including mentoring engineers and setting technical direction for a team.

---- Preferred Qualifications ----

  1. Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
  2. Experience architecting systems that involve Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and vector databases.
  3. Demonstrated experience making strategic build-vs-buy decisions and integrating large-scale third-party software or SaaS platforms into a complex enterprise environment.
  4. Experience with the architecture of AI agentic systems or complex, multi-step LLM-powered workflows (either through building or integration).
  5. Expertise with both traditional search technologies (e.g., Elasticsearch) and modern semantic search paradigms.
  6. Excellent communication skills, with the ability to articulate complex technical trade-offs to diverse audiences and influence technical strategy at a senior level.
  7. A strong product intuition and a passion for creating user-centric AI experiences that solve real-world problems.

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

Uber

Uber 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

3.1

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