Staff Software Engineer

Uber Uber · Consumer · Seattle, WA +2 · Engineering

Staff Software Engineer with advanced ML expertise to join the Data Governance team within Engineering Security. Responsible for designing, developing, and managing distributed systems to protect large-scale data infrastructure, specifically focusing on detecting and addressing data security threats related to AI agents. This role involves building user-facing products, managing high-throughput systems, and developing intelligent fraud prevention strategies using AI and Data Security techniques, with a technical leadership component.

What you'd actually do

  1. The integration of autonomous and agentic AI into our internal platforms and products necessitates a shift in our security paradigms.
  2. Your primary responsibilities will be the creation and implementation of a system designed to bolster Uber's data security.
  3. This role requires you to proactively test and stress-test current safeguards.
  4. By identifying and mitigating potential vulnerabilities ahead of time, this strategy will markedly enhance the robustness of our data security framework.
  5. You will build user-facing products, manage high-throughput transaction systems, and develop intelligent fraud prevention strategies using cutting-edge AI and Data Security techniques.

Skills

Required

  • Minimum of seven years of professional experience in software engineering.
  • Bachelor's or Master's degree in Computer Science, a related technical field, or an equivalent level of practical experience.
  • Proficiency in programming with Go, Python, Java, or C++.
  • Demonstrated expertise in practical AI applications, specifically: Integrating AI models within production software and products.
  • Overseeing AI systems in live environments, including maintenance, performance monitoring, and compliance management.
  • Strong foundation in computer science fundamentals, including data structures, algorithms, complexity analysis, and a systematic approach to troubleshooting.
  • Prior experience in technical leadership roles.
  • Excellent interpersonal and communication skills with the ability to collaborate effectively across teams and with various stakeholders.

Nice to have

  • Practical knowledge of AI agents and models, with a focus on evaluating risks like excessive agency, prompt injection, jailbreaks, Model DoS, and harmful behaviors.
  • History of integrating Machine Learning algorithms directly into production-grade products.
  • Proficiency in privacy-enhancing technologies (PETs) and security frameworks, including data minimization, anonymization, and diverse encryption protocols.
  • Deep technical understanding of large-scale, fault-tolerant storage and data processing systems, or experience with cluster orchestration and cloud platforms like Google BigQuery, Kubernetes, Amazon RedShift, Apache Impala, or Mesos.
  • Familiarity with the internal workings of open-source big data tools, such as Spark, Hive, Presto, Parquet, or Apache Hadoop (YARN/HDFS).
  • Significant expertise in Spark internals is highly valued, particularly regarding SQL optimization, resource management, and the integration of deep learning or multi-language support.

What the JD emphasized

  • advanced ML expertise
  • superior AI capabilities
  • AI agents
  • data security threats specific to AI agents
  • AI and Generative AI
  • AI agents and models
  • risks like excessive agency, prompt injection, jailbreaks, Model DoS, and harmful behaviors

Other signals

  • AI agent security
  • data governance for AI
  • production AI systems