About the Role:
We are looking for a hands-on Software Architect with deep expertise in Java, Spring Boot, and React to spearhead the modernization of legacy monolithic enterprise applications into resilient, scalable microservices architectures. This role sits at the intersection of engineering excellence and AI-led innovation — the ideal candidate will embed AI tooling across the software development lifecycle (SDLC), from AI-assisted design and code generation through to automated testing and deployment. You will lead a small, high-performing team and work closely with business stakeholders to deliver modern, production-grade enterprise software.
What You'll Do:
- Lead the end-to-end modernization of monolithic enterprise applications into microservices, applying domain-driven design (DDD), event-driven architecture, and API-first principles.
- Architect and build scalable backend services using Java and Spring Boot (Spring Cloud, Spring Security, Spring Data), and deliver modern, responsive frontend interfaces with React.
- Champion AI-led SDLC practices across the team — integrating AI-assisted coding (GitHub Copilot, Cursor, or equivalent), automated code review, AI-generated test suites, and intelligent CI/CD pipelines.
- Lead and mentor a small team of engineers (3–6), conducting code reviews, setting technical standards, and driving a culture of engineering excellence and continuous improvement.
- Define and execute the migration strategy from monolith to microservices, including service decomposition, strangler-fig pattern adoption, and data decoupling.
- Design and implement RESTful and event-driven APIs, ensuring clean contracts, versioning, and robust integration with enterprise systems.
- Embed AI-driven automation across development workflows — automated test generation, infrastructure-as-code, monitoring, and intelligent alerting.
- Collaborate with product owners and business stakeholders to translate requirements into scalable technical solutions with clear delivery milestones.
- Ensure engineering best practices: SOLID principles, clean architecture, TDD, contract testing, observability, and security-by-design.
- Drive adoption of DevOps/DevSecOps practices including containerization (Docker, Kubernetes), CI/CD, and cloud-native deployment on AWS/GCP/Azure.
What You'll Need:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
- 12–15 years of progressive software engineering experience, with at least 5 years in a software architect, principal, or senior lead role.
- Demonstrated experience delivering enterprise-grade modernization projects — ideally involving monolith-to-microservices migration at scale.
- Experience working with cross-functional teams in agile delivery environments.
- Java & Spring Boot: Deep hands-on expertise in Java (17+), Spring Boot, Spring Cloud (Gateway, Config, Eureka), Spring Security (OAuth2/JWT), and Spring Data JPA/Hibernate.
- Frontend – React: Proficient in React (Hooks, Context API, Redux), TypeScript, and building responsive, accessible enterprise UIs.
- Microservices & Architecture: Strong command of microservices patterns — service decomposition, API gateway, CQRS, event sourcing, saga pattern, and distributed tracing.
- AI-Led SDLC & Development: Practical experience embedding AI tools into the development lifecycle — AI-assisted coding, AI-driven code review, automated test generation (unit, integration, contract), and intelligent deployment pipelines.
- AI Integration: Ability to integrate LLM-based capabilities and AI services into enterprise applications, including prompt engineering, RAG, and API-based AI service consumption.
- Data & Messaging: Experience with relational databases (PostgreSQL, Oracle), NoSQL (MongoDB, Redis), and messaging systems (Kafka, RabbitMQ).
- Cloud & DevOps: Hands-on with AWS/GCP/Azure, Docker, Kubernetes, Helm, Terraform, and CI/CD tools (Jenkins, GitHub Actions, ArgoCD).
- Testing & Quality: Strong grounding in TDD, BDD, JUnit, Mockito, contract testing (Pact), and code quality tooling (SonarQube, Checkstyle).
LEADERSHIP & WAYS OF WORKING
- Proven ability to lead and mentor small engineering teams (3–6 engineers), driving technical growth and delivery quality.
- Strong engineering ownership mindset — takes accountability for design decisions, delivery timelines, and code quality across the team.
- Bias for action and pragmatic decision-making — able to balance technical rigour with the need for fast, iterative delivery.
- Collaborative stakeholder engagement — able to communicate technical trade-offs clearly to non-technical audiences.
- Commitment to continuous learning, staying current with AI tooling, modern Java ecosystem developments, and cloud-native best practices.
GOOD TO HAVE
- Experience with AI automation frameworks (LangChain, LlamaIndex) and integrating agentic workflows into enterprise software.
- Familiarity with legacy modernisation tools and platforms (e.g., AWS Migration Hub, Replit, or similar).
- Experience in commercial real estate, financial services, or property-adjacent enterprise domains.
- Certifications in AWS/GCP/Azure architecture or Kubernetes.
- Prior exposure to Palantir, Salesforce, or ServiceNow integration patterns.
OTHER SKILLS AND ABILITIES
- Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to both engineering teams and business stakeholders.
- Strong analytical and problem-solving skills, particularly in diagnosing and resolving architectural debt and legacy system constraints.
- Ability to manage multiple priorities in a fast-paced, delivery-focused environment.
- Collaborative mindset with a focus on knowledge sharing, documentation, and building team capability.
