Position Overview
We are seeking an accomplished Software Architect to lead the design, implementation, and governance of enterprise‑grade, cloud‑native Java applications. In this pivotal role, you will define architectural standards, mentor engineering teams, drive adoption of modern development practices — including AI‑augmented workflows — and ensure our systems are built for resilience, scalability, and long‑term maintainability.
You will serve as the technical authority across multiple product domains, collaborating closely with product management, DevOps, and senior leadership to align technology decisions with strategic business objectives.
Position Details
Job Title: Software Architect
Department: Engineering – Architecture & Platform
Reports To: VP of Engineering
Location: Remote
Employment Type: Full-Time, Permanent
Experience: 10+ Years Software Engineering; 5+ Years Architecture
Key Responsibilities
Architecture & Design
- Define and enforce enterprise architecture standards, patterns, and conventions across all product domains
- Lead technical design sessions and author Architectural Decision Records (ADRs) for major system changes
- Establish and refine microservices topology, service contracts, and inter‑service communication strategies
- Oversee database schema design, migration versioning, and data consistency strategies across distributed systems
Engineering Excellence
- Drive adoption of SOLID principles, Gang‑of‑Four design patterns, and reactive programming paradigms
- Establish code quality gates: minimum 85%+ test coverage enforced via CI/CD pipelines
- Introduce JMH micro‑benchmarking for performance‑critical paths and define SLOs for critical services
- Own OpenAPI/Swagger documentation standards and API versioning governance
- Guide proper exception hierarchy design, structured logging, and observability best practices (traces, metrics, logs)
AI‑Augmented Development
- Champion integration of AI‑assisted coding tools (GitHub Copilot, JetBrains AI, Cursor, Claude) into the SDLC
- Define guidelines for safe, productive, and auditable use of LLM‑generated code in production systems
- Evaluate and prototype AI/ML integration patterns: LLM API consumption, retrieval‑augmented generation (RAG), embedding pipelines, and vector store integrations within the Java/Spring ecosystem
- Develop internal AI‑powered productivity tooling (code reviewers, test generators, documentation assistants) using Spring AI or LangChain4j
- Ensure AI‑generated outputs comply with security, licensing, and intellectual property policies
Cloud‑Native & Infrastructure
- Architect cloud‑native solutions on GCP leveraging Kubernetes, service meshes, and managed data services
- Define containerisation, configuration management, and secret management standards
- Lead distributed transaction strategy using Saga patterns, idempotent consumers, and outbox patterns
- Oversee CI/CD pipeline architecture and promote GitOps workflows
Leadership & Mentorship
- Mentor senior and mid‑level engineers in architectural thinking, design patterns, and production‑readiness criteria
- Conduct architecture reviews, technical due diligence, and proof‑of‑concept evaluations
- Collaborate with Product and Business stakeholders to translate requirements into actionable technical roadmaps
- Represent the engineering organisation in cross‑functional architecture committees and vendor evaluations
Technical Requirements
Core Java & Spring Ecosystem
- Java 17+
- Spring Boot 3.x & Spring Framework 6.x
- Spring Security (OAuth 2.1, JWT, OIDC)
- Spring Data JPA / R2DBC / Redis
- Spring Cloud
- Reactive Streams
- Maven & Gradle build tooling
- Hibernate ORM & Flyway migrations
Enterprise Patterns & Architecture
- Domain‑Driven Design (Aggregates, Bounded Contexts)
- CQRS & Event Sourcing (Axon / custom)
- Saga Pattern (Choreography & Orchestration)
- Repository & Unit of Work Pattern
- Specification Pattern for query composition
- Strategy, Factory, Builder, and Decorator Patterns
- Dependency Injection mastery (Spring IoC)
Quality, Testing & Observability
- JUnit 5, Mockito, TestContainers, ArchUnit
- JMH Benchmarking & performance profiling
- SonarQube, OWASP Dependency Check
- OpenAPI 3.x / Swagger documentation
- Micrometer + Prometheus + Grafana
- Distributed tracing (OpenTelemetry, Jaeger, Zipkin)
- Resilience testing
Cloud, Messaging & Data
- GCP (container & serverless services)
- Kubernetes, Helm, ArgoCD
- Apache Kafka
- PostgreSQL, MySQL, MongoDB, Redis
- gRPC & Protocol Buffers
- GraphQL
- REST API design best practices
AI & Machine Learning Integration
- Spring AI / LangChain4j framework experience
- LLM API integration (OpenAI, Anthropic)
- Retrieval‑Augmented Generation (RAG) pipelines
- Vector databases
- Embedding models and semantic search
- AI‑assisted code generation tool governance
- Prompt engineering & chain‑of‑thought patterns
Qualifications
Required
- 10+ years of professional software engineering experience with 5+ years in a software architect or principal engineer role
- Deep expertise in Java 17+, Spring Boot 3.x, and the broader enterprise Java ecosystem
- Demonstrable production experience with microservices, event‑driven systems, and cloud‑native architectures
- Strong command of DDD, CQRS, Event Sourcing, and distributed transaction patterns
- Hands‑on experience with containerised deployments on Kubernetes in a major cloud provider
- Proven ability to mentor and elevate the technical skills of engineering teams
- Excellent written and verbal communication for both technical and non‑technical audiences
Preferred
- Experience with Spring AI, LangChain4j, or direct LLM/ML API integration in production Java services
- Familiarity with AI‑assisted development workflows: Copilot, Cursor, JetBrains AI, or equivalent
- Contributions to open‑source Java / Spring projects or published technical writing