Cloud Architect

Guidehouse•Tysons Corner, VA

About The Position

Guidehouse is seeking a Senior Cloud Architect to lead the modernization and migration of large, mission-critical applications from AWS to Google Cloud. This role provides architectural leadership across cloud platforms, data modernization, security, DevSecOps, and enterprise systems engineering. The Architect will support a high‑visibility federal system, ensuring secure, reliable, and scalable cloud operations aligned with federal SDLC/SELC methodologies. Key Responsibilities Cloud Architecture & Modernization: Lead the end-to-end strategy, design, and implementation of cloud modernization initiatives for a complex federal enterprise system. Architect secure, scalable environments in Google Cloud and drive migration from AWS using industry-standard patterns (rehost, re-platform, refactor). Establish cloud governance, resource hierarchy, network architecture, IAM policies, and resiliency strategies. Support teams in deploying managed Google Cloud AI products (e.g., Vertex AI endpoints, Gemini-based developer tools, Dialogflow agents) as part of broader cloud modernization efforts. Migration Leadership (AWS → Google Cloud): Assess existing architectures and develop migration roadmaps, sequencing, and cutover plans. Map AWS services to Google Cloud equivalents and ensure platform readiness for production workloads. Oversee containerization, orchestration (e.g., Kubernetes/GKE), data migration, and modernization of legacy components. DevSecOps, CI/CD, and Infrastructure Automation: Define and implement Terraform-based IaC, GitOps workflows, automated deployments, security gates, and policy-as-code. Mature CI/CD pipelines to support release-on-demand, automated testing, and compliance validation. SDLC / SELC Compliance (Federal Environment): Ensure all architecture deliverables, design artifacts, security documentation, readiness reviews, and testing approaches comply with federal SDLC/SELC standards, including traceability, documentation, verification/validation, and audit readiness. Partner with program management, engineering teams, and federal stakeholders to meet lifecycle governance requirements. Operational Excellence & Reliability: Implement observability across logging, monitoring, tracing, performance tuning, and resilience testing. Maintain high availability and continuity-of-operations (COOP) expectations required for critical federal systems. Technical Leadership & Collaboration: Advise senior leadership and technical teams; guide architectural decisions and modernization direction. Mentor engineering teams across multiple Agile squads and support PI planning, backlog refinement, and architectural reviews. Represent the cloud architecture discipline in stakeholder engagements, technical forums, and enterprise planning sessions. AI-Enablement: Demonstrates expertise in designing, implementing, and governing AI-enabled cloud solutions. Applies knowledge of generative AI, machine learning, and large language model (LLM) technologies to architect scalable, secure, and cost-effective enterprise solutions. Develops Retrieval-Augmented Generation (RAG) architectures, vector search solutions, and AI-driven automation workflows that integrate enterprise data sources while adhering to security, privacy, and regulatory requirements.

Requirements

Bachelor's or Master's degree in Computer Science, Information Systems, Electrical Engineering, or a related technical field.
TEN (10+) years of progressive experience in cloud architecture and enterprise modernization.
Demonstrated experience migrating complex systems from AWS to Google Cloud at scale.
Deep expertise across GCP services: Compute, GKE, VPC networking, IAM, Cloud SQL/AlloyDB, BigQuery, KMS, logging/monitoring.
Strong understanding of federal SDLC/SELC or similar structured lifecycle methodologies.
Expert-level proficiency with Terraform, CI/CD pipelines, DevSecOps, and security engineering principles.
Experience leading large cloud engineering teams in Agile environments.
Google Professional Cloud Architect certification ( or obtained within first 6 months ).

Nice To Haves

Experience modernizing large federal systems or other regulated enterprise environments.
Hands-on experience with data modernization, analytics platforms, and cloud-native data pipelines.
Experience developing cloud governance frameworks, COE structures, FinOps practices, and cost‑optimization strategies.
Experience deploying or integrating cloud-based AI/ML services—such as Google Cloud Vertex AI, Gemini, or Dialogflow—into enterprise applications.

Responsibilities

Lead the end-to-end strategy, design, and implementation of cloud modernization initiatives for a complex federal enterprise system.
Architect secure, scalable environments in Google Cloud and drive migration from AWS using industry-standard patterns (rehost, re-platform, refactor).
Establish cloud governance, resource hierarchy, network architecture, IAM policies, and resiliency strategies.
Support teams in deploying managed Google Cloud AI products (e.g., Vertex AI endpoints, Gemini-based developer tools, Dialogflow agents) as part of broader cloud modernization efforts.
Assess existing architectures and develop migration roadmaps, sequencing, and cutover plans.
Map AWS services to Google Cloud equivalents and ensure platform readiness for production workloads.
Oversee containerization, orchestration (e.g., Kubernetes/GKE), data migration, and modernization of legacy components.
Define and implement Terraform-based IaC, GitOps workflows, automated deployments, security gates, and policy-as-code.
Mature CI/CD pipelines to support release-on-demand, automated testing, and compliance validation.
Ensure all architecture deliverables, design artifacts, security documentation, readiness reviews, and testing approaches comply with federal SDLC/SELC standards, including traceability, documentation, verification/validation, and audit readiness.
Partner with program management, engineering teams, and federal stakeholders to meet lifecycle governance requirements.
Implement observability across logging, monitoring, tracing, performance tuning, and resilience testing.
Maintain high availability and continuity-of-operations (COOP) expectations required for critical federal systems.
Advise senior leadership and technical teams; guide architectural decisions and modernization direction.
Mentor engineering teams across multiple Agile squads and support PI planning, backlog refinement, and architectural reviews.
Represent the cloud architecture discipline in stakeholder engagements, technical forums, and enterprise planning sessions.
Demonstrates expertise in designing, implementing, and governing AI-enabled cloud solutions.
Applies knowledge of generative AI, machine learning, and large language model (LLM) technologies to architect scalable, secure, and cost-effective enterprise solutions.
Develops Retrieval-Augmented Generation (RAG) architectures, vector search solutions, and AI-driven automation workflows that integrate enterprise data sources while adhering to security, privacy, and regulatory requirements.

Benefits

Medical, Rx, Dental & Vision Insurance
Personal and Family Sick Time & Company Paid Holidays
Parental Leave
401(k) Retirement Plan
Group Term Life and Travel Assistance
Voluntary Life and AD&D Insurance
Health Savings Account, Health Care & Dependent Care Flexible Spending Accounts
Transit and Parking Commuter Benefits
Short-Term & Long-Term Disability
Tuition Reimbursement, Personal Development, Certifications & Learning Opportunities
Employee Referral Program
Corporate Sponsored Events & Community Outreach
Care.com annual membership
Employee Assistance Program
Supplemental Benefits via Corestream (Critical Care, Hospital Indemnity, Accident Insurance, Legal Assistance and ID theft protection, etc.)