Clean Architecture
Layered design: controllers, application services, domain, persistence. Dependencies point inward. Domain logic stays independent of frameworks and infrastructure.
Spring Boot & Next.js Specialist
Yassine REMMANI
I build full-stack platforms that land big jobs: resilient Spring Boot backends, modern Next.js frontends, and AI-ready integrations. PostgreSQL, Docker, Kafka—production-grade systems that scale.
4,000+dealer sites
Spring Boot + Next.jsfull-stack at scale
AI-readyLLM & API integration
About
I'm a senior full-stack engineer specializing in Spring Boot and Next.js, with 6+ years building production systems. I focus on stack that lands big jobs: resilient backends, modern frontends, and AI-ready integrations.
I build scalable APIs, event-driven workflows, and multi-tenant platforms. Real systems—inventory sync, campaign attribution, real-time search—that run at scale. I integrate AI (e.g. AWS Bedrock, LLM APIs) where it adds value.
Clean architecture, DDD, proper auth (JWT, OAuth2, Keycloak). Docker, CI/CD, PostgreSQL optimization. Open to senior full-stack (Spring Boot + Next.js) and roles that combine backend, frontend, and AI integration.
Methodology
How I Build Software
Backend-first discipline: clear boundaries, testability, and production readiness. No shortcuts on architecture or operations.
SOLID
Single responsibility, open/closed, dependency injection. Interfaces for external systems and cross-cutting concerns. Easier testing and evolution.
Testing
Unit tests for domain and critical paths. Integration tests for APIs and persistence. Contract and resilience where needed. CI runs the suite before merge.
CI/CD
Automated build, test, and deploy. Branch strategy and safe rollbacks. No manual deploys for routine releases. Infrastructure and config as code where applicable.
Observability
Structured logs, metrics, and alerts. Enough visibility to debug production and detect regressions. No blind deployments.
Skills
Backend
- Spring Boot
- Hibernate / JPA
- REST APIs
- Kafka / Event-Driven Systems
Frontend
- Next.js
- React
- TailwindCSS
- shadcn/ui
Databases
- PostgreSQL
- MySQL
- Redis
- Typesense
Cloud & DevOps
- Git
- AWS (EC2, S3, RDS)
- Docker & Docker Compose
- CI/CD pipelines
Architecture
- Microservices
- Monolith → Microservice migration
- Multi-tenant systems
- Scalable system design
AI & Integration
- AWS Bedrock
- LLM APIs
- RAG-style flows
- AI-powered features
Backend Architecture
Microservices & Production Systems
I build and maintain event-driven, multi-tenant backend systems at scale. Spring Boot, Kafka, PostgreSQL, Redis. Focus on scalability, resilience, and production-readiness.
API GatewayRouting · Auth
Inventory APISpring Boot
Digital ADS APISpring Boot
Dealer APIMulti-tenant · Next.js + Spring
CRM APISpring Boot
Search APITypesense
KafkaEvents · Streams
Event-driven microservices: Spring Boot services, Kafka for async workflows, PostgreSQL + Redis. Production-grade.
Spring Boot Backend Services
REST APIs, domain-driven design, clean architecture. Stateless services designed for horizontal scaling and container deployment.
Event-Driven Systems (Kafka)
Async processing, inter-service communication, eventual consistency. Built event pipelines for inventory sync, campaign attribution, and analytics.
Multi-Tenant APIs
Next.js frontend with Spring Boot backend. Tenant-scoped data isolation, shared infrastructure. Platforms serving 4,000+ dealer sites with tenant-specific configurations.
4,000+dealer sites
Event-drivenKafka pipelines
Multi-tenantNext.js + Spring
Projects
Scalable, production-grade platforms. Travel discovery (TravelOS), automotive tech, multi-tenant systems. Spring Boot & Next.js architecture.
TravelOS
Travel discovery & content platform. SEO-first architecture, high-performance REST APIs, and production-ready deployment with Spring Boot & Next.js.
Spring BootPostgreSQLRedisNext.jsDocker
Automotive Digital Platform
Large-scale platform powering inventory management, CRM workflows, dealer websites, and digital advertising campaigns. Event-driven architecture with Kafka.
Spring BootKafkaPostgreSQLRedisKeycloakDocker
Multi-Tenant Classified Ads Platform
Multi-tenant classified ads platform for car dealerships with real-time search, autocomplete, and optimized APIs for high-volume listings.
Spring BootPostgreSQLRedisTypesense
Experience
Senior Backend Engineer
Auto Dealers Digital · Casablanca, Morocco
Automotive digital platform (inventory, CRM, dealer websites, digital ads)
Dec 2019 → Present
ContextUnified inventory, CRM, dealer sites, and ad campaigns at scale. Data consistency, production stability, and performance were non-negotiable.
ActionDesigned high-traffic REST APIs, event-driven workflows with Kafka, campaign management (budgets, targeting, KPIs). Built back-office tools with Next.js. Auth (JWT, RBAC) across domains. PostgreSQL optimization, Redis caching, Dockerized CI/CD.
TechSpring Boot · Next.js · PostgreSQL · Redis · Kafka · Docker · JWT · Keycloak
Impact- →4,000+ dealer sites powered by the platform
- →Event-driven pipelines for inventory sync and campaign attribution
- →Optimized DB performance for high-volume read workloads
- →Zero-downtime deployments via CI/CD
- →Designed and maintained high-traffic REST APIs powering a large automotive business platform.
- →Implemented event-driven workflows using Kafka for data consistency, async processing, and scalable inter-service communication.
- →Built campaign management systems: budgets, targeting, performance tracking, lead attribution, and business KPIs.
- →Built and maintained internal back-office tools with Next.js for operational teams.
- →Implemented authentication and authorization (JWT, RBAC) across multiple business domains.
- →Optimized PostgreSQL schemas, indexes, and complex queries for high-volume workloads.
- →Leveraged Redis for caching, job queues, and rate limiting for resilience.
- →Dockerized services and standardized dev/prod environments. Contributed to CI/CD pipelines for automated testing and safe rollbacks.
AI
AI in Production
I use AI where it delivers measurable value: automation, RAG, and smarter APIs. With clear boundaries, fallbacks, and cost control.
Use cases
RAG for internal knowledge and support. LLM-backed automation for repetitive workflows. Structured outputs and validation. No AI for critical auth or payments.
Guardrails
Input validation, output checks, rate limits, and timeouts. Fallbacks when providers fail. Cost and usage monitoring. Human review where appropriate.
Stack
OpenAI APIs, embedding + vector store for RAG. Spring Boot services with dedicated AI boundaries. Same standards for security, logging, and deployment as the rest of the system.
Ready to Build Something Great?
Open to senior full-stack roles (Spring Boot + Next.js) and teams building AI into products. Let's discuss how I can help your team ship.