Senior Level Cloud AI Architect Jobs
Senior level cloud ai architect jobs put experienced professionals in charge of cloud AI strategy, end-to-end solution ownership, and the cross-functional teams that bring complex systems to production. Roles are spread across on-site, remote, and hybrid settings in Technology & Software, Banking & Financial Services, and Investment & Asset Management, with employers like Goldman Sachs, Citi, and JPMorganChase hiring at this level now.
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Job ID: 2613783
Location: Remote Work, VA, US
Date Posted: 2026-06-17
Category: Information Technology
Subcategory: Enterprise Architect
Schedule: Full-Time
Shift: Day Job
Travel: Yes - 10% of the time
Minimum Clearance Required: Top_Secret
Clearance Level Must Be Able to Obtain: None
Potential for Remote Work: ORA_REMOTE
Description
SAIC is seeking Senior Cloud Architect with AI Cloud. Make a difference for national security by joining a team of dedicated IT professionals who will sustain, modernize and transform the enterprise IT capabilities for the Defense Counterintelligence and Security Agency (DCSA). The Air Force, Space & Intel Business Group (AFSI) of SAIC is seeking a Senior Cloud Architect Lead to support a transformational infrastructure program for DCSA.
SAIC is proud to be supporting DCSA in safeguarding our nation’s information. DCSA is the designated oversight authority on the accreditation of classified facilities, information systems, and the insider threat program. This involves security oversight of more than 10,000 companies and approximately 13,000 facilities involved in classified work throughout the DoD and 31 Federal agencies.
Specifically, on the DCSA One IT program, SAIC will provide an enterprise IT solution that delivers highly secure and adaptable IT infrastructure, provide customer support, and cutting-edge technologies that support operations and advance the DCSA mission under a single IT environment (i.e., One IT).
This position is remote with limited travel.
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).
Key Responsibilities
- Leadership & Team Management
- Mentor and manage team members involved in workload architecture and cloud deployment to ensure technical proficiency, adherence to compliance requirements, and timely delivery of mission objectives.
- Foster a collaborative team environment, driving alignment on priorities and ensuring clear communication.
- Act as the primary technical point of contact for workload-related activities, providing direction to the team while coordinating with external stakeholders, including platform owners, vendor teams, and mission partners.
- Requirements & Coordination with Platform Providers
- Define and communicate workload requirements for routing, firewall/inspection, DNS, identity trust, logging/telemetry, secrets, and egress, and AI infrastructure, packaged as intake/change requests to the platform team with clear technical specifications and risk/treatment rationales.
- Manage cross-functional teams and discussions, ensuring alignment between workload needs and platform provisioning. Clarify roles and responsibilities for components like TGW attachments, VPCs, AI inference endpoints, and secured data pipelines supporting AI workflows.
- Architecture & Delivery (Spoke Workloads)
- Drive the creation of workload reference architectures and IaC templates (Terraform/CloudFormation/Bicep/CDK) while expanding these assets to support AI/ML pipelines (training, inference, monitoring) under RL and mission compliance guardrails.
- Lead the team in Implementing secure network zoning and service exposure (PrivateLink/VPC endpoints, ALB/NLB, WAF) ensuring both traditional and AI-based services.
- Design end-to-end AI/ML solutions by incorporating CI/CD pipelines with security/compliance gates, model versioning, artifact storage policies, and data lineage tracing that comply with RMF and logging/monitoring requirements (CloudTrail/Config/Security Hub, Azure Log Analytics/Sentinel).
- DoD Compliance & Security Engineering (Within Workload Scope)
- Map workload data and mission needs to SRG IL2–IL6 and engineer control implementations that leverage platform inheritance where available; drive RMF documentation, STIG hardening/SCAP automation, and ATO/IATT artifacts for the workload.
- Provide team guidance on applying Zero Trust principles, including identity‑centric access, micro‑segmentation, and DevSecOps, ensuring alignment with DoD mission cloud practices.
- Vendor/ISV Collaboration & Technical Assessments
- Lead collaboration efforts with external vendors and industry solution providers to evaluate AI Cloud/COTS/ISV solutions for mission-specific use cases while ensuring DoD compliance.
- Facilitate engineering design reviews, ensuring the ability to document trade-offs, residual risks, and mitigation plans in alignment with DoD guidelines.
- Reliability, Resilience & Cost Management
- Define and manage workload resilience strategies, including Multi‑AZ/Region configurations, backups, and failover mechanisms within impact level boundaries; document DR strategies and exercise runbooks compatible with platform‑managed services.
- Guide team members in implementing and monitoring FinOps practices for cost optimization in managing both cloud compute resources and AI/ML workloads (e.g., cost-efficiency of training jobs, instance rightsizing, serverless inference optimization).
Qualifications
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.
Education/Clearance Requirements:
- Bachelor's degree with 10+ years of hands-on and leadership experience as a Cloud Architect specializing in AWS, Azure, and/or AI Cloud solutions; master’s degree with 7+ years of experience.
- Ability to obtain DoD 8570 certification if not already held.
- US Citizenship required.
- Currently holding an active Top Secret Security Clearance.
Job ID: 2613783
Location: Remote Work, VA, US
Date Posted: 2026-06-17
Category: Information Technology
Subcategory: Enterprise Architect
Schedule: Full-Time
Shift: Day Job
Travel: Yes - 10% of the time
Minimum Clearance Required: Top_Secret
Clearance Level Must Be Able to Obtain: None
Potential for Remote Work: ORA_REMOTE
Description
SAIC is seeking Senior Cloud Architect with AI Cloud. Make a difference for national security by joining a team of dedicated IT professionals who will sustain, modernize and transform the enterprise IT capabilities for the Defense Counterintelligence and Security Agency (DCSA). The Air Force, Space & Intel Business Group (AFSI) of SAIC is seeking a Senior Cloud Architect Lead to support a transformational infrastructure program for DCSA.
SAIC is proud to be supporting DCSA in safeguarding our nation’s information. DCSA is the designated oversight authority on the accreditation of classified facilities, information systems, and the insider threat program. This involves security oversight of more than 10,000 companies and approximately 13,000 facilities involved in classified work throughout the DoD and 31 Federal agencies.
Specifically, on the DCSA One IT program, SAIC will provide an enterprise IT solution that delivers highly secure and adaptable IT infrastructure, provide customer support, and cutting-edge technologies that support operations and advance the DCSA mission under a single IT environment (i.e., One IT).
This position is remote with limited travel.
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).
Key Responsibilities
- Leadership & Team Management
- Mentor and manage team members involved in workload architecture and cloud deployment to ensure technical proficiency, adherence to compliance requirements, and timely delivery of mission objectives.
- Foster a collaborative team environment, driving alignment on priorities and ensuring clear communication.
- Act as the primary technical point of contact for workload-related activities, providing direction to the team while coordinating with external stakeholders, including platform owners, vendor teams, and mission partners.
- Requirements & Coordination with Platform Providers
- Define and communicate workload requirements for routing, firewall/inspection, DNS, identity trust, logging/telemetry, secrets, and egress, and AI infrastructure, packaged as intake/change requests to the platform team with clear technical specifications and risk/treatment rationales.
- Manage cross-functional teams and discussions, ensuring alignment between workload needs and platform provisioning. Clarify roles and responsibilities for components like TGW attachments, VPCs, AI inference endpoints, and secured data pipelines supporting AI workflows.
- Architecture & Delivery (Spoke Workloads)
- Drive the creation of workload reference architectures and IaC templates (Terraform/CloudFormation/Bicep/CDK) while expanding these assets to support AI/ML pipelines (training, inference, monitoring) under RL and mission compliance guardrails.
- Lead the team in Implementing secure network zoning and service exposure (PrivateLink/VPC endpoints, ALB/NLB, WAF) ensuring both traditional and AI-based services.
- Design end-to-end AI/ML solutions by incorporating CI/CD pipelines with security/compliance gates, model versioning, artifact storage policies, and data lineage tracing that comply with RMF and logging/monitoring requirements (CloudTrail/Config/Security Hub, Azure Log Analytics/Sentinel).
- DoD Compliance & Security Engineering (Within Workload Scope)
- Map workload data and mission needs to SRG IL2–IL6 and engineer control implementations that leverage platform inheritance where available; drive RMF documentation, STIG hardening/SCAP automation, and ATO/IATT artifacts for the workload.
- Provide team guidance on applying Zero Trust principles, including identity‑centric access, micro‑segmentation, and DevSecOps, ensuring alignment with DoD mission cloud practices.
- Vendor/ISV Collaboration & Technical Assessments
- Lead collaboration efforts with external vendors and industry solution providers to evaluate AI Cloud/COTS/ISV solutions for mission-specific use cases while ensuring DoD compliance.
- Facilitate engineering design reviews, ensuring the ability to document trade-offs, residual risks, and mitigation plans in alignment with DoD guidelines.
- Reliability, Resilience & Cost Management
- Define and manage workload resilience strategies, including Multi‑AZ/Region configurations, backups, and failover mechanisms within impact level boundaries; document DR strategies and exercise runbooks compatible with platform‑managed services.
- Guide team members in implementing and monitoring FinOps practices for cost optimization in managing both cloud compute resources and AI/ML workloads (e.g., cost-efficiency of training jobs, instance rightsizing, serverless inference optimization).
Qualifications
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.
Education/Clearance Requirements:
- Bachelor's degree with 10+ years of hands-on and leadership experience as a Cloud Architect specializing in AWS, Azure, and/or AI Cloud solutions; master’s degree with 7+ years of experience.
- Ability to obtain DoD 8570 certification if not already held.
- US Citizenship required.
- Currently holding an active Top Secret Security Clearance.
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Find JobsSenior Level Cloud AI Architect Job Market
Who's Hiring
- Goldman Sachs3
- Citi2
- JPMorganChase2
- CACI International2
- SAIC1
Top Industries Hiring
- Technology & Software11
- Banking & Financial Services10
- Investment & Asset Management9
- Healthcare & Medical Services5
- Fintech2
Senior Level Cloud AI Architect Jobs: Frequently Asked Questions
How do I get a senior level cloud ai architect job?
Employers at this level expect candidates who have led cloud AI initiatives from design through deployment, not just contributed to them. Demonstrating ownership of architecture decisions, experience guiding engineering teams, and a portfolio of production-grade AI systems on major cloud platforms gives candidates a clear edge. Relevant certifications and a history of influencing technical direction across an organization strengthen an application further.
Which companies hire senior level cloud ai architects?
Companies hiring senior level cloud ai architects right now include Goldman Sachs, Citi, and JPMorganChase, based on current listings on Migrate Mate as of July 2026. Hiring at this level covers large enterprises building internal AI platforms, cloud-native consultancies, and technology companies scaling production AI infrastructure.
Are there remote senior level cloud ai architect jobs?
Yes, remote and hybrid options are well established at this level. About 35% of senior level cloud ai architect openings are remote or hybrid as of July 2026, reflecting how broadly distributed cloud work has become for senior technical roles. Fully on-site positions do still exist, typically at organizations with strict data governance or security requirements.
What makes a cloud ai architect role senior level?
Senior level cloud ai architect roles are defined by scope and accountability rather than task execution. These professionals set the architectural vision for cloud AI systems, own technology decisions that affect the entire organization, and are expected to mentor engineers and principal contributors. They lead complex, multi-stakeholder projects and are responsible for outcomes, not just deliverables.
Which industries hire the most senior level cloud ai architects?
Senior Level cloud ai architect roles concentrate in Technology & Software, Banking & Financial Services, and Investment & Asset Management, based on current listings on Migrate Mate as of July 2026. These sectors drive hiring at this level because they are investing heavily in scalable, production AI systems that require experienced architects to design, govern, and evolve the underlying cloud infrastructure.