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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Enterprise Data Security Architect - **Company:** Primerica, Inc. - **Location:** Duluth, GA, United States - **Experience:** Experienced - **Salary:** $180,000.0 - $250,000.0 - **Contract:** Permanent contract - **Skills:** Kubernetes Security, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Cyber Security, Information Engineering, Information Leak Prevention, Data Loss, Data Security, Identity and Access Management, Machine Learning, Open Web Application Security, Zero Trust Network Access, Sherwood Applied Business Security Architecture, Security Information and Event Management, Enterprise Data Management, Google Cloud, Delivery Pipeline, Large Language Models, Multi-Agent Systems, Togaf, Data Lakes, Splunk - **Published:** September 4, 2026 - **Apply:** https://primerica.wd1.myworkdayjobs.com/PRI/job/Duluth-GA/Enterprise-Data-Security-Architect_R-099032026 ## About the Role * 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. * If requested, provide some 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) ## Description 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, 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. * Leverage threat modeling 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. ## Related Videos - [Our journey with Spring Boot in a microservice architecture](https://www.wearedevelopers.com/videos/511-our-journey-with-spring-boot-in-a-microservice-architecture) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [The Private AI Platform: Why Agentic Apps Need a Private Application Platform](https://www.wearedevelopers.com/videos/100162-the-private-ai-platform-why-agentic-apps-need-a-private-application-platform) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) ## Related Articles - [Events like RSAC Get You CISOs. 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