Staff Software Engineer
Indexed description
The integration of autonomous and agentic AI into our internal platforms and products necessitates a shift in our security paradigms. Because standard data security measures are no longer adequate, we need a Staff Software Engineer possessing superior AI capabilities to preemptively detect and address data security threats specific to AI agents before they impact Uber.
Your primary responsibilities will be the creation and implementation of a system designed to bolster Uber's data security. This role requires you to proactively test and stress-test current safeguards. By identifying and mitigating potential vulnerabilities ahead of time, this strategy will markedly enhance the robustness of our data security framework.
- What the Candidate Will Do ----
- Basic Qualifications ----
- 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.
- Preferred Qualifications ----
- 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.
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