About this role
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.