Staff Software Engineer_Search platform_AI

About the Role

This is a pivotal leadership role to redefine 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 -

• 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.
• 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.
• 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.
• 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.
• Build and Integrate: Remain hands-on, writing production-quality code for critical custom components, integration layers, and core platform infrastructure.
• 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 -

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

- Preferred Qualifications -

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