Adversarial Machine Learning Engineer

The Opportunity

We are building a dedicated AI Red Team to rigorously test and harden enterprise-scale AI products.

We are looking for an adversarial machine learning specialist who thinks like an attacker.

This role focuses on identifying vulnerabilities in LLM-driven systems, breaking model guardrails, exploiting data pathways, and stress-testing AI deployments before they reach enterprise customers.

This is a hands‑on technical role at the core of AI security.

• Conduct adversarial testing across LLM and AI-based systems
• Execute real‑world attack simulations, including:
• Prompt injection
• Jail breaking and guardrail bypass
• Data exfiltration attempts
• Model inversion and evasion techniques
• RAG manipulation
• Develop scripts and tooling to automate attack scenarios
• Analyse model behaviour under adversarial pressure
• Identify systemic vulnerabilities in:
• APIs
• Embedding pipelines
• Vector databases
• Fine‑tuned model implementations
• Collaborate with engineering teams to validate remediation
• Document findings clearly and concisely

You will help ensure AI systems are resilient before they are deployed at scale.

• Strong experience in adversarial ML or AI security research
• Experience working with LLM-based systems (OpenAI, Anthropic, open‑source models, etc.)
• Deep understanding of:
• Prompt injection techniques
• Model jailbreak methodologies
• AI system exploitation vectors
• Strong Python skills
• Experience building custom attack tooling or experimentation frameworks

• Familiarity with:
• RAG architectures
• Vector databases
• Model fine‑tuning workflows
• API‑based model deployments
• Understanding of model safety mechanisms and guardrails

• Background in cybersecurity or penetration testing
• Familiarity with OWASP LLM Top 10
• Experience working in enterprise environments

• Curious and relentless
• Comfortable thinking like an attacker
• Creative in finding non‑obvious vulnerabilities
• Detail‑oriented but fast‑moving
• Comfortable operating in ambiguity
• Independent but collaborative

You don’t just run test cases — you design new ones.

• Comprehensive Private Medical Coverage
• Support for Mental Health Expenses
• Life Insurance Options
• Attractive Compensation Package