Base Salary
$171k - $190k/yr
Responsibilities
- Build software platforms and automation for SAST, DAST, software composition analysis, penetration testing, AI red teaming, security design reviews, and threat modeling.
- Develop AI-powered agents and workflows that analyze source code and technical designs, orchestrate assessments, generate test cases, and validate findings.
- Build foundational infrastructure, data pipelines, shared assessment services, findings normalization and deduplication, and remediation tracking capabilities.
- Integrate security capabilities with source control, CI/CD pipelines, service inventories, and issue-tracking systems.
- Develop evaluation frameworks and operational safeguards for AI-driven security workflows, including accuracy, coverage, latency, cost, access controls, execution boundaries, and auditability.
- Own software design, implementation, testing, production debugging, incident management, code reviews, and performance improvements.
- Collaborate with Product, Data Science, Ops, and security engineers to translate ambiguous requirements into scalable systems.
Requirements
- 3+ years of professional software engineering experience in backend development, distributed systems, or data engineering.
- Proficiency in one or more object-oriented or functional programming languages, such as Go, Java, Python, or C++.
- Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent experience.
- Experience with data modeling, query optimization, system design, production APIs, service integrations, or automated workflows connecting multiple systems.
- Experience writing tests and establishing monitoring systems for code stability.
- Understanding of authentication, authorization, data protection, credential handling, source control, CI/CD, and automated testing practices.
- Preferred: experience with agentic security workflows, frontier LLMs, multi-agent or multi-model architectures, LLM-powered applications, model evaluation frameworks, security tools or automation, Big Data frameworks such as Spark or Flink, real-time streaming such as Kafka, source-code analysis, dependency graphs, API testing, or isolated execution environments.
- Preferred: experience reducing technical debt in high-load distributed systems, mentoring new team members, exercising judgment on complex engineering trade-offs, and using AI-assisted development tools.
Benefits
- Full-time employees are eligible to participate in a 401(k) plan and receive various benefits.
- US-based roles may participate in Uber’s bonus program and may be offered equity awards and other compensation.
Tech Stack
About Uber
We are Uber. The go-getters. The kind of people who are relentless about our mission to help people go anywhere and get anything and earn their way. Movement is what we power. It’s our lifeblood. It runs through our veins. It’s what gets us out of bed each morning. It pushes us to constantly reimagine how we can move better. For you. For all the places you want to go. For all the things you want to get. For all the ways you want to earn. Across the entire world. In real time. At the incredible speed of now. The idea for Uber was born on a snowy night in Paris in 2008, and ever since then our DNA of reimagination and reinvention carries on. We’ve grown into a global platform powering flexible earnings and the movement of people and things in ever expanding ways. We’ve gone from connecting rides on 4 wheels to 2 wheels to 18-wheel freight deliveries. From takeout meals to daily essentials to prescription drugs to just about anything you need at any time and earning your way. From drivers with background checks to real-time verification, safety is a top priority every single day. At Uber, the pursuit of reimagination is never finished, never stops, and is always just beginning.