Uber Staff Software Engineer TLM 

United States, West Virginia 

346096119

About the Role

To create and advance a foundational AI infrastructure for the Developer Platform. This involves ensuring the development of robust systems for context, knowledge, and memory management, which are critical for enhancing AI-driven development experiences and improving agent functionality.

1. Increased accuracy and effectiveness of AI agents through enhanced data context and knowledge systems.
2. Enhanced developer productivity by providing immediate access to accurate and useful information.

What you'll do

1. Team Leadership: Lead and mentor a small team of 4-5 AI engineers, fostering a collaborative and innovative work environment.
2. Memory Systems Management: Design and manage shared memory systems, including the development of rules and best practice registries for AI agents.
3. AI Documentation: Implement and oversee strategies for AI-first documentation generation, ensuring the health and discoverability of documentation.
4. Code Context Infrastructure: Maintain repository and module summaries, providing comprehensive context for AI agents.
5. Knowledge Graph & Data Ingestion: Vectorize engineering data and create knowledge graphs to facilitate advanced knowledge retrieval.
6. Tooling and Client Development: Develop and maintain MCP servers/clients and other tools critical for enhancing the AI Developer Experience.
7. Collaboration and Integration: Engage with AI Platform and AI DevEx teams to ensure seamless integration and alignment with broader organizational goals.

What you'll need

Educational Background: Hold a degree in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field.

Expertise in Large Language Models (LLMs): Demonstrated experience with both unimodal and multimodal LLMs and agentic systems.

Framework Proficiency: Skilled in using frameworks such as CrewAI, LangChain, and LangGraph to facilitate autonomous decision-making and workflow automation.

Emerging AI Technology Awareness: Knowledgeable about emerging AI technologies, including agentic systems, MCP, and A2A protocol, and understanding their potential applications.

Programming Skills: Proficient in writing clean, elegant, and bug-free code, particularly in languages such as Java and Go.

Problem-solving Abilities: Possess exceptional analytical and problem-solving skills with a focus on delivering scalable solutions.

- - - - Preferred Qualifications ----

Cloud Computing Knowledge: Proficient in utilizing cloud computing infrastructure to support scalable AI/ML applications.

AI/ML Framework Expertise: Experience with leading AI/ML development frameworks and tools, including TensorFlow, PyTorch, and Hugging Face, for building advanced AI solutions.

AI Monitoring and Observability: Familiarity with AI monitoring and observability tools such as Langfuse, Prometheus, and Grafana, or similar platforms to ensure effective system performance and management.

Vector and RAG Models: Skilled in embedding generation and retrieval using VectorDB and RAG ingestion techniques for enhancing AI data processing capabilities.

* 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 .