Enterprise Data Security Architect

Enterprise Data Security Architect

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.

• 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, modelinversion/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 prevention (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.

• 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.
• Understanding of deploying and managing security tech such as DLP, SIEM systems (e.g., Splunk, ELK), tokenization/masking, and compliance frameworks (GDPR, HIPAA, SOC
  2).
• Ability to lead Incident Response activities such as monitoring for anomalies, investigating breaches, and lead recovery efforts while minimizing data exposure.
• Potential indirect or matrix supervisory responsibility as a project manager, although this does not mean formal supervision of team members (e.g., the position doesn’t complete performance evaluations, hire or terminate).

Location:

Duluth, GA

• Day one health, dental, and vision insurance
• 401(k) Plan with competitive employer match
• Vacation, sick, holiday and volunteer time off
• Life and disability insurance
• Flexible Spending Account & Health Savings Account
• Professional development
• Tuition reimbursement
• Company-sponsored social and philanthropy events