Enterprise Data Security Architect

Primerica•Duluth, GA

1d•$180,000 - $250,000•Hybrid

About The Position

The Cybersecurity Security Architect serves a significant role in strategic planning, product design, and solution testing. The position is instrumental in leading the evaluation of technology acquisitions and managing integrations for the company's technology acquisitions. The architect must have extensive knowledge of multiple disciplines/environments as they will be considered a subject matter expert across the enterprise. The role will serve as a leader and guide on projects, providing frameworks, architecture documents, emerging technologies, enterprise data programs, sample application code, and adherence to enterprise standards. Salary range is between $180K - $250K USD Annual

Requirements

This position would require 10 years of security architecture or senior security engineering experience as previously described.
3+ years of direct experience securing AI/MK/GenAI systems, data science platforms, or large-scale data environments
CISSP, CCSP, and CISM highly preferred
NIST Cybersecurity Framework practical experience is required
SABSA or TOGAF framework experience is also preferred.
Deep knowledge of modern cloud security (Azure, AWS, GCP), container/kubernetes security, and zero-trust principles.
Strong understanding of AI/ML concepts: model lifecycle, training/inference pipelines, embeddings, RAG, agents, fine-tuning, and common attack vectors.
Proven track record performing threat modeling and risk assessments for both traditional systems and AI workloads.
This person would specifically also understand how to deploy and manage security tech such as DLP (Data Loss Prevention), SIEM systems (e.g., Splunk, ELK), tokenization/masking, and compliance frameworks (GDPR, HIPAA, SOC 2).
This person would specifically also understand how to lead Incident Response activities such as monitoring for anomalies, investigating breaches, and lead recovery efforts while minimizing data exposure.

Responsibilities

Defining overarching security reference architectures, patterns, standards, and blueprints that align with business objectives while incorporating secure-by-design strategies.
Design controls to mitigate AI-specific risks: prompt injection, data poisoning, model inversion/extraction, adversarial attacks, hallucination exploitation, supply-chain attacks on models/datasets, and agentic/multi-agent system vulnerabilities.
Define secure patterns for generative AI deployments including RAG architecture, vector databases, LLM gateways, output filtering, guardrails, red-teaming processes, and responsible AI governance.
Lead threat modeling using frameworks such as MITRE ATLAS, OWASP, NIST AI RMF, etc.
Architect and support enterprise data security controls: classification, encryption (at-rest, in-transit, in-use), data loss preventions (DLP), data security posture management (DSPM), access governance, and tokenization.
Secure big data / analytics environments (data lakes, warehouses, feature stores, model registries) and ensure lineage, provenance, and integrity in data use.
Collaborate with data engineering teams to embed privacy-preserving techniques (differential privacy, federated learning, secure multi-party computation) where appropriate.
Command the ability to properly assess security architecture against regulatory requirements and frameworks.