Job DescriptionEnterprise Architecture serves as the foremost technical authority and strategic leader for our AI discipline. This is role is an Enterprise Architect who combines profound technical expertise with the ability to influence and guide the entire organization's technical direction. The Principal Architect will be entrusted with our most complex, ambiguous, and highest-impact technical challenges.
You will operate across multiple teams and business units, setting a long-term vision for our AI architecture, platforms, and practices. Lead AI & Cloud architectures to future target-state architecture for a cloud-native, AI-enabled data/API ecosystem. This leader will define pragmatic reference architectures, patterns, and guardrails that accelerate delivery-shifting architecture from a "governance gate" to a product-minded enablement function that empowers teams to build secure, compliant, and scalable data products faster.
Your day to day- Define and drive the long-term Enterprise Architecture technical roadmaps for AI at the company. Identify and champion new technological paradigms that create step-change opportunities and sustainable competitive advantages.
- Design, and prototype foundational AI platforms, frameworks, and core services that will be leveraged by engineering teams across the entire organization. Your designs will set the standard for scalability, security, and innovation.
- Legacy Modernization & Target-State Architecture: Lead modernization of legacy data platforms into a cloud-native architecture, defining migration strategies, transitional architectures, and decommissioning roadmaps.
- Cloud Data Platforms (Warehouse/Lakehouse): Architect enterprise solutions using modern data warehousing and lakehouse platforms, including workload placement, cost/performance optimization, and resilience patterns.
- Data Engineering Enablement: Establish patterns for ingestion, transformation, orchestration, and observability (batch/streaming), and partner with engineering teams to improve delivery quality and velocity.
- AI-Driven Data Modernization: Apply AI concepts to modernize data engineering and delivery (e.g., intelligent metadata, automated lineage, code assist, testing/validation automation, anomaly detection, and policy enforcement).
- Guardrails, Standards & Reusable Blueprints: Define architecture guardrails, reference implementations, reusable templates, and "paved roads" that teams can adopt with minimal friction.
- Governance-by-Design: Embed security, privacy, risk, and regulatory requirements into architecture patterns and CI/CD practices enabling "continuous compliance" rather than after-the-fact reviews.
- Stakeholder Leadership: Influence senior stakeholders across business, products, engineering, security, and governance to align priorities, resolve tradeoffs, and drive measurable modernization outcomes.
What We Need from You - Bachelor's or Master's degree in a relevant field of work or an equivalent combination of education and work-related experience.
- Seven to ten years of architecture/design/delivery experience which includes five years of enterprise architecture experience or seven to ten years' solution architecture experience in technology and security, and five years of Hospitality/Retail business domain.
- Comprehensive experience with various architectural domains such as application, data, infrastructure, security and integration
- Strong analytical and broad architectural skills
- Strong verbal and written communication skills
- Strong negotiation/facilitation skills
- Significant knowledge of current and emerging architecture principles, methodologies and tools
- Experience as negotiator with vendors for relevant products and services
- Demonstrated competency in strategic thinking with ability to differentiate feasible from academic solutions
- Demonstrated thought-leadership skills with the ability to translate high-level business planning information into application needs/solutions
- Experience working with a set of geographically dispersed team and bringing a holistic view of development projects.
- A distinguished career with extensive experience in software engineering and AI, with a proven track record of operating at a Principal or equivalent level (e.g., Senior/Lead Staff Engineer, Architect).
- Recognized as a technical leader with experience setting the technical vision for multiple teams or an entire enterprise.
- Verifiable history of architecting, building large-scale, mission-critical AI systems that have delivered significant business impact.
- Deep experience navigating ambiguity and translating high-level business or product strategy into a concrete, multi-year technical roadmap.
- Experience presenting to and influencing executive leadership (VPs, CTO, CPO) on complex technical topics.
- Technical Skill & Knowledge
- Expert understanding of modern AI concepts, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic workflows.
- Deep, authoritative knowledge of major generative AI platforms. Proven ability to reason about and architect solutions using the Google Gemini family of models and their underlying infrastructure is highly preferred.
- Expert experience with a major cloud provider (GCP, AWS, Azure), including their AI/ML services. Familiarity with MLOps principles and tools for CI/CD, model deployment, and monitoring.
- Solid understanding of microservices architecture, API design (e.g., REST, gRPC), and containerization technologies (e.g., Docker, Kubernetes).
- World-class ability to design highly scalable, fault-tolerant, and elegant distributed systems. You don't just use the cloud; you architect for it.
- Strong analytical and problem-solving skills
- Ability to display effective verbal and written communication skills when explaining complex technical issues to a variety of technical audiences, including clients, vendors, senior management and staff.
- A history of contributions to open-source projects, publications in reputable conferences, or speaking at technical events is a strong plus.
- Ability to establish and maintain a high level of customer trust and confidence in the software engineering team's knowledge of the customer's business needs.
- Understands and implements work effectively utilizing agile best practices.
