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Chief Architect

Summary

Chief Architect defines and governs enterprise-wide cloud-native, multi-tenant SaaS architectures, internal developer platforms, and security standards across AWS, Azure, and GCP to drive reliability, cost efficiency, and developer productivity.

Title: Chief Architect – Advisory Digital

Key responsibilities

  • Architecture strategy and roadmap
    • Own target-state enterprise architecture for distributed, cloud-native platforms and products across multiple business units.
    • Define and govern reference architectures, blueprints, and standards for multi-tenant SaaS, microservices, and event-driven systems.
    • Establish architecture metrics and outcomes tied to business objectives (e.g., lead-time reduction, reliability, cost).
  • Platform engineering and IDP
    • Lead design and rollout of Internal Developer Platforms to standardize golden paths, improve developer experience, and accelerate delivery.
    • Define platform SLAs/SLOs, golden templates, and paved roads for services, data, observability, and security.
  • Cloud architecture and vendor neutrality
    • Architect solutions across AWS, Azure, and GCP with a vendor-neutral mindset; leverage managed services where it creates strategic advantage.
    • Define multi-cloud landing zones, tenancy models, and portability patterns (12-factor, containers, IaC).
  • Multi-tenant SaaS at scale
    • Design and operate secure, scalable, cost-efficient multi-tenant architectures including tenant isolation, entitlements, billing/quotas, and data protection.
    • Establish patterns for regionalization, data residency, and compliance controls (GDPR, PCI, SOC 2 as applicable).
  • Security, identity, and compliance by design
    • Embed security and privacy controls into architecture (Zero Trust, IAM, secrets management, KMS/HSM, network segmentation).
    • Partner with security and risk teams to implement governance, threat modeling, and continuous compliance automation.
  • DevSecOps and engineering excellence
    • Drive CI/CD, GitOps, policy-as-code, and SRE practices; improve DORA metrics and engineering productivity.
    • Introduce AI-driven SDLC accelerators and guardrails to reduce cycle time and increase quality.
  • Integration, APIs, and service connectivity
    • Define API strategy (gateway management, versioning, monetization) and service connectivity (service mesh, mTLS, traffic management).
    • Establish event streaming and data-in-motion patterns for real-time use cases.
  • Data and AI platform architecture
    • Guide modern data architectures (lakehouse, streaming, governance) and AI/ML platforms for model training, deployment, and monitoring.
    • Partner with data and product teams to operationalize ML/GenAI responsibly at scale.
  • Governance and operating model
    • Lead architecture governance across a matrixed enterprise; run ARBs, standards councils, and technology guardrails.
    • Build and mentor a high-performing architecture community of practice; scale via accelerators, reusable IP, and knowledge assets.
  • Stakeholder leadership and communication
    • Translate complex technical concepts into clear business narratives for executives and non-technical stakeholders.

Minimum qualifications

  • 15+ years in software engineering and architecture with significant time in senior/principal/chief architect roles.
  • Deep expertise in cloud-native and distributed systems: microservices, event-driven architectures, CQRS, caching, resiliency patterns.
  • Proven experience designing and operating multi-tenant SaaS platforms at enterprise scale.
  • Strong hands-on experience on Azure,
  • Security and identity: OAuth2/OIDC, SSO, SAML, RBAC/ABAC, secrets management, KMS, network policies, and zero trust principles.
  • Container orchestration and connectivity: Kubernetes, Helm/Kustomize, service meshes (e.g., Istio/Linkerd), and API management (e.g., Apigee, Kong, Azure/API Gateway).
  • DevSecOps and automation: CI/CD, GitOps (Argo CD/Flux), IaC (Terraform, CloudFormation, Bicep), policy-as-code (OPA), and supply-chain security.
  • Data and AI: familiarity with lakehouse platforms (e.g., Databricks, BigQuery, Snowflake), event streaming (Kafka/Pulsar), and AI/ML platforms (SageMaker, Vertex AI, Azure ML); understanding of MLOps and responsible AI practices.
  • Experience leading architecture governance in large, complex enterprises; established ARB processes and standards.
  • Background in regulated industries (banking, insurance, public sector) or large enterprise SaaS products.
  • Demonstrated ability to communicate crisply with executives and non-technical stakeholders and to influence cross-functional teams.

Preferred qualifications

  • Prior responsibility for technology strategy across multiple products or business units and for P&L- or portfolio-impacting decisions.
  • Track record building platform engineering functions/CoEs and internal developer platforms.
  • Experience modernizing legacy systems at scale (e.g., monolith-to-microservices, application server migrations, language/runtime upgrades).
  • Experience creating IP/accelerators that reduce delivery effort and standardize modernization.
  • Certifications such as TOGAF, cloud provider certifications, and advanced DevSecOps/AI credentials.

Key competencies

  • Enterprise technology leadership and strategic thinking
  • Platform engineering and developer experience
  • Architecture governance and operating model design
  • Vendor-neutral multi-cloud design and FinOps awareness
  • Executive communication and stakeholder management
  • Innovation mindset with bias for measurable outcomes
  • Team leadership, coaching, and global delivery governance

What success looks like (12–18 months)

  • Target-state platform and SaaS architecture defined and adopted with clear reference implementations and guardrails.
  • IDP and golden paths established, improving developer productivity by 20–30% and reducing lead time to production.
  • Secure, compliant multi-tenant capabilities implemented with measurable improvements in reliability, performance, and cost.
  • AI-driven SDLC accelerators embedded with quality improvements and cycle-time reductions.
  • Architecture governance operationalized with consistent standards and reduced deviation across products/business units.

  • Architecture strategy and roadmap
    • Own target-state enterprise architecture for distributed, cloud-native platforms and products across multiple business units.
    • Define and govern reference architectures, blueprints, and standards for multi-tenant SaaS, microservices, and event-driven systems.
    • Establish architecture metrics and outcomes tied to business objectives (e.g., lead-time reduction, reliability, cost).
  • Platform engineering and IDP
    • Lead design and rollout of Internal Developer Platforms to standardize golden paths, improve developer experience, and accelerate delivery.
    • Define platform SLAs/SLOs, golden templates, and paved roads for services, data, observability, and security.
  • Cloud architecture and vendor neutrality
    • Architect solutions across AWS, Azure, and GCP with a vendor-neutral mindset; leverage managed services where it creates strategic advantage.
    • Define multi-cloud landing zones, tenancy models, and portability patterns (12-factor, containers, IaC).
  • Multi-tenant SaaS at scale
    • Design and operate secure, scalable, cost-efficient multi-tenant architectures including tenant isolation, entitlements, billing/quotas, and data protection.
    • Establish patterns for regionalization, data residency, and compliance controls (GDPR, PCI, SOC 2 as applicable).
  • Security, identity, and compliance by design
    • Embed security and privacy controls into architecture (Zero Trust, IAM, secrets management, KMS/HSM, network segmentation).
    • Partner with security and risk teams to implement governance, threat modeling, and continuous compliance automation.
  • DevSecOps and engineering excellence
    • Drive CI/CD, GitOps, policy-as-code, and SRE practices; improve DORA metrics and engineering productivity.
    • Introduce AI-driven SDLC accelerators and guardrails to reduce cycle time and increase quality.
  • Integration, APIs, and service connectivity
    • Define API strategy (gateway management, versioning, monetization) and service connectivity (service mesh, mTLS, traffic management).
    • Establish event streaming and data-in-motion patterns for real-time use cases.
  • Data and AI platform architecture
    • Guide modern data architectures (lakehouse, streaming, governance) and AI/ML platforms for model training, deployment, and monitoring.
    • Partner with data and product teams to operationalize ML/GenAI responsibly at scale.
  • Governance and operating model
    • Lead architecture governance across a matrixed enterprise; run ARBs, standards councils, and technology guardrails.
    • Build and mentor a high-performing architecture community of practice; scale via accelerators, reusable IP, and knowledge assets.
  • Stakeholder leadership and communication
    • Translate complex technical concepts into clear business narratives for executives and non-technical stakeholders.
  • 15+ years in software engineering and architecture with significant time in senior/principal/chief architect roles.
  • Deep expertise in cloud-native and distributed systems: microservices, event-driven architectures, CQRS, caching, resiliency patterns.
  • Proven experience designing and operating multi-tenant SaaS platforms at enterprise scale.
  • Strong hands-on experience on Azure,
  • Security and identity: OAuth2/OIDC, SSO, SAML, RBAC/ABAC, secrets management, KMS, network policies, and zero trust principles.
  • Container orchestration and connectivity: Kubernetes, Helm/Kustomize, service meshes (e.g., Istio/Linkerd), and API management (e.g., Apigee, Kong, Azure/API Gateway).
  • DevSecOps and automation: CI/CD, GitOps (Argo CD/Flux), IaC (Terraform, CloudFormation, Bicep), policy-as-code (OPA), and supply-chain security.
  • Data and AI: familiarity with lakehouse platforms (e.g., Databricks, BigQuery, Snowflake), event streaming (Kafka/Pulsar), and AI/ML platforms (SageMaker, Vertex AI, Azure ML); understanding of MLOps and responsible AI practices.
  • Experience leading architecture governance in large, complex enterprises; established ARB processes and standards.
  • Background in regulated industries (banking, insurance, public sector) or large enterprise SaaS products.
  • Demonstrated ability to communicate crisply with executives and non-technical stakeholders and to influence cross-functional teams.

Preferred qualifications

  • Prior responsibility for technology strategy across multiple products or business units and for P&L- or portfolio-impacting decisions.
  • Track record building platform engineering functions/CoEs and internal developer platforms.
  • Experience modernizing legacy systems at scale (e.g., monolith-to-microservices, application server migrations, language/runtime upgrades).
  • Experience creating IP/accelerators that reduce delivery effort and standardize modernization.
  • Certifications such as TOGAF, cloud provider certifications, and advanced DevSecOps/AI credentials.

See also