Software Architect - Enterprise Java * Cloud-Native * AI-Augmented Development

Job description

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: 15+ 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 15+ 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