Software Architect

Job Overview:

We are seeking a hands-on Software Architect to lead the enterprise architecture, cloud-agnostic platform architecture, application framework design, and security architecture of the Linnk AI-native enterprise platform.

The Linnk product ecosystem consists of:

• LinnkMe AI-powered recruitment platform (ATS & talent intelligence)
• LinnkUp Operational Intelligence ERP for Finance, HR, and Project Management
• LinnkUs Cross-product communication and collaboration platform
• Linnk IQ AI intelligence layer powered by domain-specific models, AI agents, and enterprise knowledge graph

The architect will design a scalable, secure, AI-native SaaS architecture that integrates these platforms into a unified enterprise ecosystem.

This role requires deep architecture leadership combined with hands-on engineering capability, with responsibility for designing a cloud-agnostic application framework architecture using modern technologies such as Next.js and NestJS, enabling modular, scalable, and portable enterprise systems.

The architect will work closely with product leadership, AI teams, platform engineers, and security teams to build an enterprise-grade AI platform capable of supporting global SaaS scale.

Key Responsibilities:

1. Enterprise Architecture & Platform Strategy

• Define, own, and evolve the enterprise architecture framework for the Linnk product ecosystem.
• Architect a modular, AI-native SaaS platform integrating LinnkMe, LinnkUp, LinnkUs, and Linnk IQ.
• Establish architecture standards across application, data, integration, security, AI systems, and cloud deployment.
• Define and implement architectural patterns including microservices, event-driven systems, domain-driven design (DDD), and API-first architecture.
• Design scalable, multi-tenant SaaS architecture ensuring high performance, security, and tenant isolation.
• Develop comprehensive architecture documentation including system diagrams, data flows, and service interaction models.

(Enterprise architects typically define frameworks, standards, and align technology with business goals)

2. Application Framework & Platform Engineering

• Design and standardize a cloud-agnostic application framework supporting deployment across AWS, Azure, and GCP.
• Define frontend architecture using Next.js and React, including SSR and component-driven UI systems.
• Define backend architecture using Node.js and NestJS, including modular services and scalable microservices design.
• Establish reusable engineering patterns such as monorepo architecture, shared libraries, and API gateway orchestration.
• Build platform-level capabilities including authentication services, workflow orchestration, messaging, and SDK frameworks.
• Ensure architecture supports scalability, developer productivity, and seamless cross-product integration.

3. Distributed Systems & Platform Architecture

• Design and implement highly scalable distributed systems supporting AI agents, automation, and enterprise data orchestration.
• Architect systems leveraging asynchronous event-driven communication and distributed computing models.
• Ensure high availability through multi-region deployments and horizontally scalable infrastructure.
• Define best practices for system resilience, failure recovery, observability, and distributed tracing.

4. Application Security & Secure Architecture

• Own and drive the application security architecture across the entire platform ecosystem.
• Implement secure-by-design principles aligned with enterprise standards and best practices.
• Design and enforce security frameworks including IAM, RBAC, OAuth2, OpenID Connect, and JWT authentication.
• Ensure compliance with OWASP Top 10, Secure SDLC, Zero Trust Architecture, and API security standards.
• Architect data protection mechanisms including encryption, secrets management, and audit logging.
• Integrate DevSecOps practices including automated security testing, vulnerability management, and threat modeling.
• Ensure compliance readiness for SOC2, ISO 27001, and GDPR.

5. AI & Intelligence Architecture

• Architect AI-powered capabilities across the platform using Linnk IQ.
• Design systems for AI agents, recruitment intelligence models, workflow automation, and predictive analytics.
• Enable contextual enterprise intelligence through knowledge graphs and cross-product learning systems.
• Implement Responsible AI practices including model monitoring, explainability, and auditability.

6. Cloud Architecture & Infrastructure

• Design and maintain cloud-agnostic infrastructure architecture supporting multi-cloud deployments.
• Architect containerized microservices using Kubernetes and serverless architectures.
• Design distributed event streaming and scalable infrastructure for enterprise workloads.
• Ensure infrastructure supports high availability, disaster recovery, redundancy, and multi-region scalability,

7. DevOps, DevSecOps & Engineering Excellence

• Establish best practices for CI/CD, infrastructure-as-code, and automated deployment pipelines.
• Implement DevOps platforms using Docker, Kubernetes, and Git-based CI/CD workflows.
• Integrate DevSecOps practices including automated security scanning and runtime monitoring.
• Drive engineering excellence through standardized practices, tools, and governance.

8. Cross-Product Integration Architecture

• Architect seamless integration across all Linnk products, enabling unified data flow and workflows.
• Define API governance, integration standards, and interoperability frameworks.
• Ensure alignment across hiring workflows, employee lifecycle, project execution, and communication platforms.

9. Strategic Technology Leadership

• Define and drive the long-term technology vision and platform roadmap.
• Ensure architecture aligns with Linnk's goal of building an AI-native enterprise operating system.
• Evaluate emerging technologies across AI, SaaS platforms, and distributed systems.
• Provide architectural governance and strategic direction across all engineering initiatives.

10. Stakeholder Collaboration & Communication

• Act as the technical bridge between leadership, product, AI, and engineering teams.
• Translate complex architecture into clear, actionable insights for business stakeholders.
• Provide visibility into architecture maturity, risks, scalability, and security posture.
• Support client and leadership engagements with data-driven insights and recommendations.

11. Team Leadership & Mentorship

• Support hiring and development of high-performing engineering teams.
• Mentor engineers in system design, scalable architecture, and secure coding practices.
• Promote a culture of engineering excellence, innovation, and platform thinking.
• Drive adoption of best practices across architecture, security, and AI integration.

12. Programme Transition & Scalability

• Ensure architecture and processes support seamless transition to a permanent US operational team.
• Build scalable, well-documented systems to support future programme growth.
• Enable knowledge transfer, operational continuity, and long-term sustainability.