Direct message the job poster from Ascendion I may have your next Awesome Job Opportunity || Talent Acquisition || Ascendion Role Overview As a Backend Engineer, you will be key in building and maintaining Studio AI's core infrastructure. You will work closely with AI engineers, front-end developers, and cloud architects to develop scalable backend solutions using Java, Spring Boot, and Azure cloud services. This role requires expertise in API development, microservices architecture, and cloud-based deployments. You will be responsible for designing robust and scalable backend services, ensuring seamless integration with AI models, and optimizing system performance for enterprise-scale workloads. Key Responsibilities Backend Architecture & Development: Design, develop, and maintain scalable, high-performance backend systems using Java, Spring Boot, and microservices architecture. API & Microservices Development: Build RESTful and GraphQL APIs to support AI-driven content creation, retrieval, and automation workflows. Cloud Infrastructure & Deployment: Deploy and optimize backend services on Azure Cloud, leveraging Azure Kubernetes Service (AKS), Azure Functions, and Azure DevOps pipelines. Database & Storage Optimization: Design and maintain efficient SQL and NoSQL databases (e.g., PostgreSQL, CosmosDB) for AI-powered data processing. Security & Compliance: Implement enterprise-grade authentication, authorization, and data protection mechanisms using OAuth, JWT, and Azure Active Directory. Scalability & Performance Tuning: Optimize API response times, database queries, and caching strategies to support large-scale AI applications. AI Model Integration: Work with AI engineers to integrate LLMs , vector search, and machine learning models into the backend pipeline. Monitoring & Troubleshooting: Implement observability tools such as Prometheus, Grafana, and Azure Monitor to track system health, performance, and error rates. Cross-functional collaboration: Work closely with front-end developers, AI engineers, and cloud architects to ensure seamless integration between backend services and AI workflows. Required Skills & Qualifications Education: Bachelor’s or Master’s in Computer Science, Software Engineering, or a related field. Experience: 5+ years of experience in backend development with a focus on Java and cloud-based architectures. Technical Proficiency: Strong proficiency in Java, Kotlin, Spring Boot, and microservices architecture. Experience with RESTful and GraphQL API development. Experience with SQL and NoSQL databases such as PostgreSQL, CosmosDB, or MongoDB. Familiarity with event-driven architectures and message queues (e.g., Kafka, RabbitMQ). Strong knowledge of authentication and security frameworks (OAuth2, JWT, SAML). Experience with CI/CD pipelines, containerization (Docker, Kubernetes), and Infrastructure as Code (Terraform, Bicep). Preferred Skills & Experience AI-Driven Backend Development: Experience integrating backend services with AI and machine learning models. Vector Databases & Search Optimization: Knowledge of Milvus, Pinecone, or Elasticsearch for AI-powered knowledge retrieval. GraphQL & Event-Driven APIs: Experience with GraphQL, gRPC, and asynchronous event processing. Azure Cognitive Services & AI Integration: Understanding of Azure OpenAI, Azure AI Services, and LLM deployment. Performance Monitoring & Observability: Hands-on experience with Prometheus, Grafana, Azure Monitor, and distributed tracing tools. Seniority level Mid-Senior level Employment type Full-time Job function Information Technology Industries Technology, Information and Internet #J-18808-Ljbffr