Amanda M.

Key Skills

Software

Internal/Proprietary Tooling

Top Subject Matter

AI governance

AI security

risk management

Top Data Types

Text

Image

Document

Top Task Types

Prompt + Response Writing (SFT)

Fine-tuning

Freelancer Overview

Sr. Technical Consultant | Cybersecurity | AI Security | Governance (Remote). Brings 20+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Don't disclose, Google Workspace, and ServiceNow GRC. Education includes Master of Business Administration, University of Michigan - Stephen M. Ross School of Business (2009) and Bachelor of Science, University of Illinois Chicago. AI-training focus includes data types such as Text and labeling workflows including Prompt + Response Writing (SFT) and Fine-tuning.

Labeling Experience

Sr. Technical Consultant | Cybersecurity | AI Security | Governance (Remote)

Don't discloseTextPrompt + Response Writing (SFT)

In her current role, she authored AI governance and security guidance intended to standardize how AI outputs should be evaluated and managed by governance teams. She built an AI security “single source of truth” covering assessments, AI change management, vulnerability management, and data privacy controls to support consistent labeling and evaluation practices. She also delivered public-facing AI security and governance education through presentations and authored materials for governance professionals. • Authored a handbook focused on AI security management, risk management, and ethics • Defined an AI security framework for assessments, AI change and vulnerability management • Produced governance handbooks and training materials for AI adoption and security • Presented on staying relevant in the age of AI, reinforcing practical governance expectations

2024 - Present

Principal Technical Consultant | Enterprise Security Architect (Remote)

TextFine-tuning

In this enterprise architecture role, she implemented governance and security programs that operationalized AI-driven SIEM insights and accelerated AI-enabled requirements and test planning workflows. While not described as training an ML model on labeled datasets, her work established structured processes for generating and managing security-relevant assessment artifacts and testing documentation. She used AI prompt engineering to speed creation of agile requirements and test plans that functionally support downstream evaluation and annotation workflows. • Streamlined high-risk project workflows using ServiceNow GRC and Collibra • Leveraged AI prompt engineering (RAG and Google Workspace integration) to accelerate JIRA requirement gathering • Used AI-assisted creation of test plans in qTest to reduce development time • Applied secure governance and IAM controls to support risk-managed AI-enabled operations

2019 - 2023

Education

Work History