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Software Engineer II - Security Review Automation

Uber Seattle, WA

Seattle, WA

Today

$171k - $190k/yr Full time Backend Developer Ai Red Teaming Application Security

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Job Description

Uber’s Offensive Security team builds security tools, platforms, and AI-powered automation that enable continuous, scalable security testing and risk reduction. If you want to work on systems that support global teams and high-load production environments, this role focuses on turning security expertise into platforms integrated across CI/CD and developer workflows.

This Software Engineer II role is based in Seattle, WA (onsite), with a base salary range of USD 171,000 - 190,000 per year.

What you’ll do

Build software platforms and automation across SAST, DAST, SCA, 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.
Partner with security engineers to translate expertise into repeatable, scalable capabilities.
Build and scale foundational infrastructure and data pipelines, balancing technical debt and shifting priorities while keeping long-term impact in view.
Integrate security capabilities with source control, CI/CD pipelines, service inventories, and issue-tracking systems to support continuous and on-demand testing.
Create shared services for assessment orchestration, findings normalization and deduplication, and remediation tracking to reduce duplicate findings and manual effort.
Design, develop, and maintain high-quality code for features of moderate complexity across projects with multiple dependencies.
Develop evaluation frameworks and operational safeguards for AI-driven security workflows, measuring accuracy, coverage, latency, and cost, and enforcing access controls, execution boundaries, and auditability.
Own the software lifecycle end-to-end, from drafting design docs to debugging production issues and managing incidents independently.
Collaborate across disciplines, including Product, Data Science, and Ops, to convert ambiguous inputs into clear system designs.
Support engineering best practices through quality code reviews, comprehensive tests, and improvements to system performance.
Navigate internal complexity and stakeholder inquiries to unblock dependencies and help ensure reliability of the production environment.

What you’ll need

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 (for example: Go, Java, Python, or C++).
Experience with data modeling, query optimization, and translating customer problems into system design.
Bachelor’s Degree (or equivalent experience) in Computer Science, Engineering, or a related technical field.
Experience writing tests to verify functionality and establishing monitoring to ensure code stability.
Experience building APIs, service integrations, or automated workflows that connect multiple systems in production.
Understanding of secure software development fundamentals, including authentication, authorization, data protection, and safe handling of credentials.
Familiarity with source control, CI/CD, and automated testing practices for reliable delivery.

Technologies you may work with

Go, Java, Python, C++, SAST, DAST, SCA, CI/CD, Spark, Flink, Kafka, LLMs

Compensation and benefits

Eligible to participate in Uber’s bonus program (for all US locations).
May be offered an equity award and other types of comp.
All full-time employees are eligible to participate in a 401(k) plan.
Various benefits (details not provided).

About the team

As part of Uber’s Offensive Security team, you’ll build the security tools, platforms, and AI-powered automation that support security testing and risk reduction at Uber scale. The work involves handling messy, global systems, making smart decisions with imperfect information, owning outcomes end-to-end, and maintaining reliability when systems are under heavy load.

Preferred qualifications

Experience building agentic security workflows that gather technical context, reason across multiple data sources, invoke security tools, validate conclusions, and produce evidence-backed assessments.
Experience applying frontier LLMs to complex security reasoning, including architecture analysis, attack-path identification, threat enumeration, vulnerability discovery, and security control validation.
Experience developing multi-agent or multi-model architectures, including specialized agents, model routing, or model-as-judge techniques.
Experience identifying and reducing code-level technical debt in high-load distributed systems.
Background in mentoring new team members and contributing to engineering culture.
Proficiency with Big Data frameworks (for example: Spark, Flink) or real-time streaming (for example: Kafka).
Demonstrated ability to exercise sound judgment on engineering trade-offs for complex systems.
Experience building security tools or automation in domains such as SAST, DAST, SCA, penetration testing, AI red teaming, security design reviews, or threat modeling.
Experience developing LLM-powered applications or agentic workflows, including model integration, tool execution, context retrieval, and orchestration.
Experience building evaluation frameworks for AI-driven systems, including reproducible benchmarks, regression testing, and output quality and reliability measurement.
Familiarity with source-code analysis, dependency graphs, API testing, or isolated execution environments for automated security testing.
Experience using AI-assisted development tools to accelerate software implementation, testing, debugging, and maintenance.

Work location and onsite expectations

Unless approved for full remote work, employees must spend at least 50% of their time in-office.
Some roles may require full-time in-office presence.

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