Security Engineer (AI & Agentic Systems)

Uber
New York, NY, United States
3 months ago
Apply on indeed.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Compensation
$171,000.0 - $190,000.0
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Artificial Intelligence Software System Penetration Testing Python (Programming Language) Role-Based Access Control Red Team (Cyber Security) Large Language Models Multi-Agent Systems Software Security AI Platforms Golang

Job description

As AI systems-especially agentic and autonomous AI-become deeply embedded in our products and internal platforms, the security model must evolve. Traditional application security alone is no longer sufficient. We are looking for an AI Red Team Engineer to help us proactively identify, understand, and mitigate AI-native and agent-specific security risks before they reach production.

In this role, you will build and execute adversarial red-teaming exercises against AI models and AI agents, focusing on how they can be manipulated into unsafe, unintended, or harmful behavior. You will work closely with AI platform teams, product engineers, and security partners to stress-test agent logic, tool usage, memory, and autonomy-and translate findings into concrete guardrails and defenses.

This role is ideal for someone who enjoys thinking like an attacker, understands modern AI systems, and wants to work at the intersection of security, AI, and real-world impact. - What the Candidate Will Do -

This role sits at the intersection of offensive security and AI engineering. You will not be limited to traditional penetration testing; instead, you will focus on behavioral, logical, and contextual attacks that cause AI systems to fail in subtle but dangerous ways-often without exploiting classic vulnerabilities. Success in this role means uncovering unknown unknowns,” clearly articulating risk, and helping teams build safer AI systems by design.

Design and execute AI red-teaming exercises against LLMs and AI agents, including:

  • prompt injection (direct & indirect)
  • jailbreaking and policy bypass
  • model and tool poisoning
  • memory and context poisoning
  • behavioral drift and unsafe autonomy
  • tool misuse and emergent privilege escalation

Analyze agent workflows, logic, and tool graphs to identify systemic security weaknesses beyond prompt-level attacks.

Develop reusable adversarial test cases, attack libraries, and red-team playbooks for AI systems.

Collaborate with AI platform and product teams to translate red-team findings into actionable mitigations, guardrails, and design changes. - Basic Qualifications -

Requirements

  • 3+ years of experience in security engineering, offensive security, red teaming, or AI security.
  • Hands-on experience red-teaming AI models or AI agents, including testing for prompt injection, jailbreaks, unsafe behavior, Excessive agency, Model DoS.
  • Strong understanding of security fundamentals (threat modeling, secure design, least privilege, defense in depth).
  • Ability to clearly document findings and communicate risk to both technical and non-technical stakeholders
  • Proficiency in at least one programming language (e.g., Python, Go, Java, or similar)

  • Preferred Qualifications -

  • Familiarity with AI security tools and frameworks (e.g., PyRIT, AgentDojo, Promptfoo, custom harnesses).
  • Good understanding of GenAI and LLM architectures, including: embeddings, RAG, or agent frameworks.
  • Hands-on experience executing AI Red Teaming exercises, including prompt injection/jailbreaking, unsafe behavior/behavioral drift, model/tool poisoning.Offensive security / penetration testing background (e.g., red team, bug bounty, exploit development).

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on indeed.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:08 min

Building solutions with open source GoLang infrastructure tools

Jad Wahab · LIVE

2:36 min

Choosing between managed AI platforms and custom governance

Péter Farkas Péter Farkas · Europe 2026 Virtual

1:30 min

The universal and shared team responsibility of software security

Julia Wilson Julia Wilson +1 · World Congress 2025

3:00 min

Top security vulnerabilities for AI applications

Deepu Deepu · World Congress 2025

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

6:16 min

Event-driven Golang backend architecture and cloud deployment

Irina Branovic Irina Branovic · World Congress 2026 Europe

Videos

See all

Related articles

See all