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

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

• 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