Senior Cloud Architect Lead, AI Cloud

🕒 June 17

⚔️ Virginia – Remote

⚔️ Virginia – Remote

⏰ Full Time

🟠 Senior

☁️ Cloud Engineer

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SAIC

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1969

☁️ SaaS

📣 Marketing

🏢 Enterprise

🔥 Funding within the last year

💰 $500M Post-IPO Debt - SAIC on 2025-09

SaaS • Marketing • Enterprise

SAIC is represented in the supplied content by marketing and product copy that matches Bitly — a cloud-based link management and QR-code platform. The material describes a SaaS offering for URL shortening, dynamic QR Codes, link analytics, mobile-friendly landing pages, branded links, UTM campaign tracking, digital business cards, developer APIs and AI-enhanced features. It targets marketers, developers, and enterprises across industries (retail, CPG, hospitality, media, healthcare, finance, education) and emphasizes integrations, analytics, and enterprise-grade capabilities. Note: the provided text appears to be Bitly’s website content rather than information about SAIC; if you intended the defense/technology firm SAIC (Science Applications International Corporation), please provide relevant content.

📋 Description

• Serve as a cloud architecture leader, providing guidance and mentorship to team members, while supporting a DoD mission program. Design and deliver secure, compliant workloads within a platform-managed hub-and-spoke environment across AWS GovCloud and Azure Government, integrating advancements in AI Cloud capabilities for enhanced mission impact. • Architect and deliver secure, scalable AWS‑centric solutions (with multi‑cloud fluency across Azure Government/GCP) as a spoke workload team operating inside a platform‑managed hub‑and‑spoke environment. • Be well‑versed in platform management constructs (network hub, identity, operations, DevOps, shared services) to facilitate design discussions and articulate workload requirements to platform owners/providers for both traditional cloud services and emerging AI-enabled services. • Operate as a liaison between mission teams, leadership, and platform providers. Ensure workload strategies, including AI/ML-related initiatives, align with programmatic, operational, and compliance goals. • Translate complex requirements, including both traditional infrastructure needs and innovative AI-based workloads, into practical architectures while balancing compliance with DoD operational constraints (Cloud Computing SRG impact levels, RMF/ATO, DISA STIGs).

🎯 Requirements

• 10+ years in cloud architecture/engineering with deep hands‑on AWS experience; proven delivery of secure workloads in AWS GovCloud (US) and/or Azure Government supporting DoD missions within a platform‑managed hub‑and‑spoke environment. • Government program experience and proven team leadership skills, including managing, mentoring, and guiding technical teams toward achieving project and operational goals. • Demonstrated ability to translate system requirements into technical solutions and to negotiate workload needs with platform owners/providers (networking, identity, security, logging/monitoring, DevOps). • Strong grasp of DoD SRG, RMF (NIST SP 800‑53/53B), DISA STIGs, ATO/IATT processes, and continuous monitoring/POA&M practices; experience leading teams in the implementation of these practices into workload designs. • **Certifications (Required)** • CompTIA Security+ (CE). • At least one Professional/Expert‑level cloud certification (Associate/Foundation does not meet the requirement): • AWS Certified Solutions Architect – Professional (preferred), AWS DevOps Engineer – Professional, or another AWS Professional. • Microsoft Certified: Azure Solutions Architect Expert. • Google Professional Cloud Architect. • Relevant specialty certs (e.g., Advanced Networking, Security) are a plus when paired with a Professional/Expert certification. • Preferred Skills & Tools • Leadership Skills: Experience managing teams, driving cross-functional collaboration, and mentoring junior members to grow technical, compliance, and operational expertise. • AI & ML Integration: Experience with deploying AI/ML pipelines using SageMaker, TensorFlow, MLflow, Kubernetes (for serving/training ML models), or equivalents on AWS, Azure ML, or GCP Vertex AI. • IaC & automation: Terraform, CloudFormation, CDK, Bicep; configuration as code (Ansible/PowerShell/Bash). • CI/CD: GitLab/GitHub Actions/Azure DevOps with policy gates and security scanning aligned to platform controls. • Networking: Transit Gateway, VPC/VNet segmentation, PrivateLink/VPC endpoints, firewall policies; ability to specify correct TGW attachment parameters and route associations while respecting platform ownership. • Security services & monitoring: AWS Security Hub/GuardDuty/Config/KMS, Azure Sentinel/Defender; integration to centralized logging/telemetry required by the platform. • Documentation & compliance: Author SSP sections, control inheritance matrices, STIG baselines, and continuous monitoring playbooks for workloads.

🏖️ Benefits

• Health insurance • 401(k) matching • Remote work options