Enterprise Architect

All about the role:

As Enterprise Architect, you will define and own the enterprise-wide architectural vision and technology strategy for our client. You will lead the architecture for new product capabilities and platforms — selecting the right tools, technologies, and patterns, setting standards and governance practices, and shaping the long-term technology roadmap that guides Principal Architects, Technical Architects, and engineering leaders. Even where Principal Architects own the architecture for specific initiatives, you serve as the senior reviewing voice, ensuring consistency, quality, and alignment across the enterprise. You will also drive technology rationalization and vendor strategy — consolidating overlapping tools, evaluating build-vs-buy trade-offs, and ensuring the technology landscape remains coherent, cost-effective, and future-ready.

A core priority of this role is driving AI-assisted engineering at scale — establishing the practices, tools, and guardrails that enable every engineering team to leverage AI in how they design, build, test, and maintain software. You will also identify high-impact AI opportunities across products and ensure responsible AI design and governance.

While most of your time will go into architecture, governance, and elevating other architects, you are expected to remain hands-on when the situation demands it — whether that means diving into code, leading critical reviews, or prototyping to validate key architectural decisions. You will partner with senior business and engineering leaders to align architecture with business strategy, evaluate emerging technologies, and ensure platform stays modern, secure, scalable, and future-ready.

Required Skills & Experience

Must-Have Experience & Education

• 15+ years of overall software engineering experience, with 4+ years at Principal Architect, Sr. Architect, or Enterprise Architect level.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proven track record of designing and governing large-scale distributed systems in production
• Demonstrated experience operating in product-based or SaaS organizations delivering at enterprise scale.
• Experience working in global, distributed engineering environments across multiple time zones.

Architectural Leadership & Governance

• Demonstrated experience setting enterprise-wide architectural standards, principles, and reference architectures.
• Experience leading architecture review forums, design councils, or governance bodies across multiple product lines or business units.
• Track record of mentoring Principal/Senior Architects and elevating architectural maturity across organizations.
• Familiarity with enterprise architecture frameworks and structured decision-making methods.
• Experience driving technology rationalization (tool/platform consolidation) and vendor evaluations (build-vs-buy decisions).

Core Technical Stack

• Deep expertise in Java and the Spring / Spring Boot ecosystem as a primary foundation.
• Strong architectural capability across modern backend ecosystems — Python (FastAPI/Django), Node.js, microservices, RESTful APIs, event-driven systems (Kafka, JMS), and integration frameworks.
• Architectural awareness of frontend ecosystems — React, Angular — sufficient to make full- stack decisions.
• Hands-on capability to dive into code, lead code/design reviews, and prototype when architectural decisions require it.

Cloud, Infrastructure & Engineering Practices

• Strong experience architecting on AWS (preferred); working knowledge of Azure or GCP.
• Deep understanding of cloud-native patterns — serverless, containers (Docker), Kubernetes, service mesh.
• Experience setting standards for CI/CD, Infrastructure as Code, DevOps maturity, and observability across engineering teams.
• Strong grasp of non-functional requirements at enterprise scale — scalability, availability, performance, security, compliance, resilience, and cost efficiency.

Data Architecture

• Proficiency with RDBMS (PostgreSQL, MySQL) and NoSQL systems (MongoDB, Cassandra, DynamoDB).
• Understanding of data architecture patterns at scale — data modeling, partitioning, replication, and event-sourced/streaming data systems.

AI-Assisted Engineering

• Hands-on familiarity with AI-assisted development tools (code copilots, AI testing assistants, AI documentation tools) and demonstrated experience driving their adoption across teams.

Stakeholder & Business Skills

• Experience partnering with senior business, product, and engineering leadership to align technology strategy with business goals.
• Strong communication and presentation skills with the ability to clearly articulate technical strategy and trade-offs to non-technical executives.

Good-to-Have

• Strong architectural understanding of AI solution patterns — GenAI, LLM integration, embeddings, vector databases, RAG, and agentic workflows.
• Awareness of responsible AI principles — governance, security, data privacy, and ethical considerations in AI design.
• Hands-on experience building or integrating AI-powered SaaS platforms in production.
• Exposure to Databricks or similar modern data/AI platforms.
• Experience with domain-driven design (DDD) and event-storming techniques for complex domains.
• Exposure to platform engineering initiatives (internal developer platforms, golden paths, paved roads).
• Experience with API management, service mesh (Istio, Linkerd), and modern API security patterns (OAuth 2.0, OIDC, JWT).
• AWS Certified Solutions Architect (Associate or Professional) or equivalent senior cloud certifications.
• Experience contributing to technology investment decisions or representing engineering in board-level discussions.
• Public speaking, technical writing, or open-source contributions on architecture or AI topics.

Preferred Background

• Experience at a B2B or B2C product / SaaS company delivering software at enterprise scale.

Prior experience in enterprise SaaS, HCM, or talent acquisition is a plus.