About the role

The core requirements for the job include the following:

Education and experience:

15+ years of overall software engineering experience, with 4+ years at the principal architect, senior 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 organisations delivering at enterprise scale.
Experience working in global, distributed engineering environments across multiple time zones.

Architectural Leadership and 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 organisations.
Familiarity with enterprise architecture frameworks and structured decision-making methods.
Experience driving technology rationalisation (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 and Angular, is 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 and Engineering Practices:

Strong experience architecting on AWS (preferred); working knowledge of Azure or GCP.
Deep understanding of cloud-native patterns: serverless, containers (Docker), Kubernetes, and 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 modelling, 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 and 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, and 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.

Enterprise Architect