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Google
Google

Organizing the world's information and making it universally accessible.

Engineering Analyst, Cloud AI Abuse

RoleEngineering
LevelMid Level
WorkOn-site
TypeFull-time
Posted3 weeks ago
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  • Monitor Google Cloud AI products for signs of abuse, including prompt injection, jailbreaking, data poisoning, distillation, and generation of policy-violating content.

  • Perform in-depth analysis of risks associated with both generative and agentic AI. Measure these risks using benchmarking, evaluations, red teaming, and scaled usage monitoring.

  • Develop, tune, and deploy rules, heuristics, and rate limits to proactively block abusive actors and mitigate automated attacks

  • Effectively collaborate with engineering, product, and legal teams to ensure that the risks of AI are understood and robust solutions are adopted.

  • Educate cross-functional teams about Gen AI safety risks and advocate for secure design principles. Promote a culture of safety and user trust throughout the product development process.

  • Bachelor's degree or equivalent practical experience.

  • 2 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.

  • Experience with SQL.

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About Google

Google

Google

Public

Google specializes in internet-related services and products, including search, advertising, and software.

10,001+

Employees

Mountain View

Headquarters

$1,700B

Valuation

Reviews

10 reviews

4.5

10 reviews

Work-life balance

3.2

Compensation

4.3

Culture

4.1

Career

4.2

Management

3.8

82%

Recommend to a friend

Pros

Great benefits and perks

Innovative and interesting work

Career development and learning opportunities

Cons

High pressure and expectations

Long hours and heavy workload

Fast-paced and overwhelming environment

Salary Ranges

57,503 data points

Mid/L4

Mid/L4 · Accessibility Analyst

1 reports

$214,500

total per year

Base

$165,000

Stock

-

Bonus

-

$214,500

$214,500

Interview experience

9 interviews

Difficulty

3.4

/ 5

Duration

14-28 weeks

Offer rate

44%

Experience

Positive 0%

Neutral 56%

Negative 44%

Interview process

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

Common questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense