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Cloud Architect

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Abacus.AI

Business Products & Software Services

Cloud Architect

Remote in US
Remote
Full-time
Posted Sep 17, 2026
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Cloud Engineering
Remote

Summary

As a Cloud Architect on our Cloud Engineering team, you will design and implement scalable, resilient, secure, and cost-effective cloud solutions that address client business and technical requirements. You will serve as a technical subject matter expert for cloud services and work directly with clients and engineering teams to develop practical cloud architectures and support successful implementation.

 The Cloud Architect should have expert knowledge of at least one major public cloud platform, such as Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP), with a strong understanding of cloud networking, security, infrastructure, cost management, and operational requirements.

 This role will also support clients in the adoption of emerging cloud and enterprise AI capabilities. You will help evaluate and design solutions involving technologies such as Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Amazon Bedrock, and other enterprise AI platforms, with consideration for security, governance, data protection, and responsible adoption.

Responsibilities (including, but not limited to the following)

  • Design scalable, resilient, secure, and cost-effective cloud architectures tailored to client business
    requirements.
  • Design and implement cloud solutions across public cloud and hybrid environments.
  • Serve as a cloud services subject matter expert for clients and internal engineering teams.
  • Participate in client meetings and communicate cloud architecture recommendations to technical and
    business stakeholders.
  • Develop cloud architecture designs that address performance, availability, scalability, security, and
    operational requirements.
  • Apply cloud security best practices to infrastructure and solution designs.
  • Design cloud infrastructure with ongoing monitoring, management, support, and operational
    requirements in mind.
  • Estimate and help manage cloud consumption and infrastructure costs.
  • Conduct cloud assessments and identify opportunities for cost optimization and improved resource
    utilization.
  • Develop and maintain cloud architecture diagrams, technical documentation, standards, and
    implementation guidance.
  • Support cloud migration initiatives, including planning, assessment, architecture, and implementation.
  • Design and support workload migrations to public cloud environments.
  • Work with engineering teams to translate architecture designs into secure and maintainable
    implementations.
  • Support infrastructure automation using Terraform and other Infrastructure as Code tools

Skills 

  • Must be able to articulate complex technical architectures to executive leadership and diverse stakeholders
  • Ability to deliver innovative, enterprise-grade technology solutions for clients
  • Ability to lead projects under pressure and with competing priorities
  • Highly analytical thinker with advanced troubleshooting and problem-solving skills
  • Must have availability to occasionally work nights and some weekends
  • Expert knowledge of multiple major public cloud platforms (Azure, AWS, and/or Google Cloud) including advanced networking, compute, security, IAM, and cost optimization
  • Expert technical skills with Windows Server Technologies, including Active Directory and hybrid identity solutions
  • Proficiency with git and version control in conjunction with Azure DevOps repositories
  • Deep familiarity with containerization, Kubernetes, and cloud-native application architectures
  • Expert understanding of Windows and Linux environments at the enterprise scale
  • Expert understanding of deploying to Azure using Terraform and other Infrastructure as Code tools
  • Advanced understanding of deploying to Azure using CI/CD processes with complex pipelines
  • Advanced experience with administering Microsoft Fabric
  • Ability to align cloud solutions to complex business needs and strategic objectives
  • Solid proficiency in PowerShell and/or Python with working familiarity in Bash and other scripting languages
  • Ability to read, understand, and optimize complex code and infrastructure configurations
  • Deep understanding of cloud economics and ability to optimize costs at enterprise scale
  • Expert knowledge of security frameworks, compliance requirements, and risk management
  • Fundamental understanding of how generative AI and large language models work, including their limitations (hallucination, prompt injection, non-determinism) and practical mitigations for production use
  • Working knowledge of enterprise AI platforms such as Microsoft 365 Copilot, Copilot Studio, Claude Enterprise, and ChatGPT Enterprise, including their security, governance, and data handling considerations
  • Understanding of AI skills and agentic behavior, including tool use, orchestration patterns, and failure modes
  • Working knowledge of Microsoft Purview, particularly Data Loss Prevention (DLP), Information Protection, and Insider Risk Management, and how these underpin safe enterprise AI adoption
  • Familiarity with Azure AI Foundry, Amazon Bedrock, or Amazon SageMaker; Google Vertex AI experience a bonus
  • Understanding of data readiness principles for AI, including permissions hygiene, oversharing remediation, and sensitivity labeling
  • Awareness of AI regulatory considerations in the US or UK, particularly data residency and auditability (helpful, not required)

Qualifications

  • 3+ years of experience in cloud engineering and architecture
  • Proven track record designing and implementing complex, enterprise-scale cloud solutions
  • Senior-level certifications in multiple cloud platforms (e.g., AWS Solutions Architect Professional, GCP Professional Cloud Architect, AZ-305)
  • Demonstrated experience leading cloud architecture for organizations or major clients
  • Expert understanding of multi-cloud and hybrid cloud architectures
  • Proven experience with cloud migration strategies and execution at scale
  • Knowledge of industry standard security frameworks and compliance requirements (e.g., SOC 2, ISO 27001, NIST, HIPAA, PCI-DSS)
  • Expert problem-solving, troubleshooting, and analytical skills
  • Demonstrated leadership abilities including mentoring junior team members
  • Advanced automation capabilities with Infrastructure as Code and CI/CD pipelines
  • Expert understanding of Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), and serverless architectures
  • Understanding of enterprise AI deployments (e.g., Microsoft 365 Copilot rollouts, Copilot Studio agents, Azure AI Foundry, Amazon Bedrock, Amazon Q Business, Google Vertex AI, or Gemini for Google Workspace)
  • Strong project management and stakeholder communication skills
  • Experience architecting solutions in highly regulated industries (financial services, healthcare) strongly preferred
  • Experience in the financial sector a plus
  • Experience working at an MSP a plus

The Benefits of Working for Abacus:

  • Exposure to diverse array of technologies
  • Part of a team of experienced engineers who aim to deliver exceptional service
  • Competitive compensation
  • Robust benefits package: medical, dental, vision, disability, life insurance, 401k, and PTO
  • Opportunities to further education through our Employee Certification program
  • Positive, friendly, supportive office environment
  • Workplace perks such as healthy snacks, wellness program, and fun events

 

 

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Abacus.AI

Company profile

Abacus.AI enables organizations of all sizes to build and scale the kind of real-time deep learning systems used by Silicon Valley behemoths to build customer engagement and forecast trends. And there’s pedigree in its products. Cofounders include Siddartha Naidu, co-creator of Google’s BigQuery; Bindu Reddy, Amazon Web Services’ former manager of AI vertical services; and former Uber engineer Arvind Sundararajan. Abacus.AI helps some 6,000 clients capture real-time data from sources including social media interactions, online purchases and IoT sensors and use it to train deep learning models for search and personalization, sales and marketing, pricing prediction and supply chain management.

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Headquarters

San Francisco, California, United States

Team size

200

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