Sr. Cloud Security Architect

Neptune Technology Group•Tallassee, GA

About The Position

As a Sr. Cloud Security Architect, you will play a critical role in Neptune’s cybersecurity program by designing, implementing, and governing secure cloud architectures across a hybrid environment (on‑prem, cloud, and SaaS). You will work closely with Cloud, Platform, DevOps, and Security Operations teams to embed security‑by‑design principles, enforce guardrails, and strengthen prevention, detection, and compliance capabilities across cloud workloads. In addition to architecture and engineering responsibilities, you will provide senior technical support to Incident Response activities involving cloud environments, assisting with investigation, containment, remediation, and post‑incident improvements when needed.

Requirements

Bachelor’s degree (or equivalent experience)
5+ years of experience in information security, with at least 3+ years focused on cloud security or cloud architecture
Hands‑on experience securing cloud environments (AWS and/or Azure)
Familiarity with NIST, CIS Benchmarks, zero trust principles, and cloud shared responsibility models
Strong analytical, problem‑solving, and communication skills

Nice To Haves

Security or cloud certifications (e.g., AWS Security Specialty, Azure Security Engineer, CCSP, CISSP)
Experience translating SOX or regulatory requirements into technical cloud controls
Exposure to DevSecOps practices, automation, and continuous compliance monitoring
Experience supporting cloudrelated incident response activities
Familiarity with AI-specific threat vectors such as prompt injection, model inversion, and training data poisoning
Demonstrated use of AI-assisted tools to improve security workflows and engineering productivity

Responsibilities

Design and implement secure cloud architectures, landing zones, and guardrails across AWS and Azure environments
Develop and maintain cloud security standards, reference architectures, and reusable patterns
Enforce security‑by‑design and least‑privilege principles across cloud networking, identity, and workloads
Support securebydefault provisioning and segmentation strategies
Design and implement security controls for AI/ML workloads and services (e.g., AWS Bedrock, Azure OpenAI, SageMaker), including data protection, access controls, and API security
Implement and maintain native and third‑party cloud security controls (IAM, CSPM, logging, posture management)
Translate regulatory and internal security requirements into enforceable technical controls
Integrate security controls into infrastructure‑as‑code and CI/CD pipelines
Develop automation to detect misconfigurations, reduce manual effort, and improve control consistency
Leverage AI-assisted tools to accelerate security engineering, threat modeling, and compliance automation, applying sound judgment on their limitations and avoiding over-reliance on automated outputs
Monitor and assess cloud security posture using telemetry, posture management, and logging platforms
Identify misconfigurations, control gaps, and emerging risks across cloud environments
Partner with Security Operations to improve visibility, prioritization, and response for cloudrelated risks
Evaluate and critically assess AI-driven security tooling (CSPM, SIEM) to ensure detection quality and avoid over-reliance on automated AI-generated findings
Provide technical support during cloud‑related security incidents, including investigation, containment, and remediation
Assist with root cause analysis and recommend architectural improvements following incidents
Participate in tabletop exercises, threat modeling, and readiness activities
Ensure cloud environments align with internal security standards and industry frameworks (e.g., CIS, NIST)
Support audit and compliance efforts by providing architecture artifacts, evidence, and technical explanations
Collaborate with stakeholders throughout the solution and product lifecycle to implement effective risk mitigations
Research emerging cloud threats, attack techniques, and technologies to proactively strengthen defenses
Support governance of enterprise AI tool consumption from a security and data privacy perspective, including controls to prevent sensitive data from flowing into third-party LLM APIs or AI-enabled SaaS platforms
Familiarity with AI governance frameworks such as NIST AI RMF and OWASP Top 10 for LLM Applications