Job Description

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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

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