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 explicit 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.

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