Kpmg India Services Llp

Chief Architect

Kpmg India Services Llp
Gurgaon/Gurugram
Not disclosed
Work from OfficeWork from Office
Full TimeFull Time
Min. 15 yearsMin. 15 years

Job Description

Chief Architect

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.

Experience Level

Senior Level

Job role

Work location
Work locationGurgaon, Haryana, India
Department
DepartmentSoftware Engineering
Role / Category
Role / CategorySoftware Backend Development
Employment type
Employment typeFull Time
Shift
ShiftDay Shift

Job requirements

Experience
ExperienceMin. 15 years

About company

Name
NameKpmg India Services Llp
Job posted by Kpmg India Services Llp

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