We are seeking a senior architecture leader who will drive data architecture coherence across globally distributed engineering teams and accelerate delivery through reusable foundations. This individual will shape the platforms evolution toward AI-native product experiences, ensuring strong security, governance, reliability, and cost efficiency.

This is a high-impact individual contributor role that collaborates across Data Engineering, Product Engineering, Security/Compliance, and SRE.

Key Responsibilities :

Data Architecture & Data-as-a-Product Enablement :

- Establish and operationalize standards for data products : ownership, data contracts, schema evolution, quality SLAs, lineage expectations, access controls, and lifecycle management.

- Reduce fragmentation by driving canonical domain modelling and shared semantics that enable downstream product features.

AI Platform Enablement & Embedded Intelligence :

- Architect foundations for embedding AI into product experiences (automation, recommendations, copilots/assistants, insights) with guardrails and governance.

- Define scalable patterns for AI enablement : data pipelines for training/inference, evaluation, versioning, monitoring/observability, and controls appropriate for enterprise HR contexts.

Google Cloud Partnership & Cloud-Native Architecture :

- Design and optimize cloud-native architectures leveraging Google Clouds infrastructure, data, and AI services.

- Drive best practices for reliability, security posture, and cost optimization (FinOps mindset), including performance tuning and operational excellence.

Technical Governance & Cross-team Collaboration :

- Lead asynchronous-first technical governance through RFC/ADR processes for high-impact decisions.

- Provide architectural reviews and mentoring to senior engineers; create reusable golden paths and shared components to improve delivery velocity.

- Collaborate with global architects and engineering leaders across time zones

Required Qualifications (Must-Have) :

- 15+ years in software engineering with significant experience in Data Platform architecture for B2B SaaS.

- Strong data architecture background : data modelling, data contracts/schema evolution, governance and quality frameworks, lineage/discoverability concepts.

- Experience building platforms that enable AI/ML and deploying AI-powered product features (governance, monitoring, evaluation).

- Cloud architecture experience with Google Cloud Platform (preferred) or equivalent depth on AWS/Azure with ability to ramp quickly to GCP.

- Strong distributed systems fundamentals and experience with event-driven and/or streaming architectures.

- Demonstrated ability to influence across multiple teams without direct authority; excellent written communication (design docs, RFCs).

Preferred Qualifications (Nice-to-Have) :

- Experience with enterprise security/compliance requirements (e.g., SOC 2, ISO 27001, GDPR) and privacy-by-design.

- Experience with data residency / multi-region architectures.

- Experience building developer platforms, internal tooling, or paved road enablement.