AI Security Engineer

The role

This person will own data collection, mining, curation, and continuous evaluation for AI security products. They will build automated data ingestion pipelines, manage dataset curation, and operate benchmark and evaluation harnesses.

What you will do

• Design and operate automated data collection, mining, and web-scraping pipelines.
• Build data processing, annotation, and dataset curation workflows.
• Train and re-train various models including Prompt Injection SLMs and Shadow-AI detection models.
• Build mechanisms to capture false-positive samples from live flows and integrate them into retraining pipelines.
• Develop automated benchmarking and evaluation harnesses.
• Build automated pipelines for model training.
• Work with research and software engineering teams to turn telemetry into model improvements.

Required qualifications

• 2–4 years of experience in software engineering, data engineering, or automated QA/evaluation roles.
• Strong programming proficiency in Python.
• Experience in model training and various ML, AI algorithms.
• Experience building data pipelines, web scrapers, or automated data processing systems.
• Familiarity with data structures, storage formats, and database configurations.
• Methodical approach to dataset labeling, validation, bug logging, and metric tracking.

Nice to have

• Hands-on experience with ML evaluation frameworks, dataset curation, or annotation tools.
• Familiarity with text extraction, NLP preprocessing, or document parsing techniques.
• Understanding of cybersecurity concepts (Prompt Injection, Malicious Macros, DLP/PII).
• Basic experience with cloud storage, object stores, and basic containerization (Docker).
• Experience with AWS, GCP, Terraform, Kubernetes, and Linux.
• C++
• SQL

About the company

Menlo Security is the leader in Browser Security for human and agentic workforces. The Menlo Browser Security Platform protects organizations from cyberattacks by stopping threats across the web, documents, and email.