Senior Java Backend Developer – AI Integration

Java Backend Developer (JAVA + AI)

Toronto, ON – Hybrid (4 Days WFO)

6–12 Months

• Design, develop, and maintain high performance backend services using Java (17+), Spring Boot, and Microservices architecture.
• Build and expose RESTful and event driven APIs supporting enterprise scale applications.
• Integrate Generative AI / LLM capabilities (e.g., text generation, summarization, Q&A, classification) into backend workflows.
• Design, test, and optimize prompts and prompt orchestration strategies to ensure accuracy, determinism, and performance.
• Develop AI aware backend components such as:
  • Prompt templates and prompt pipelines
  • Retrieval Augmented Generation (RAG) services
  • AI inference orchestration layers
• Implement secure API integrations with AI platforms and internal data sources, ensuring compliance with enterprise security standards.
• Apply prompt versioning, evaluation, and monitoring techniques to improve AI output quality over time.
• Ensure non functional requirements: scalability, resiliency, performance, and observability.
• Contribute to CI/CD pipelines, containerization, and cloud native deployments.
• Participate in code reviews, architecture discussions, and technical design decisions.
• Support production systems and troubleshoot complex backend or AI integration issues.

• 5+ years of strong hands on experience in Java backend development.
• Expertise in Java 11/17+, Spring Boot, Spring MVC, Spring Security.
• Solid experience in Microservices, REST APIs, and API design (OpenAPI/Swagger).
• Experience with containers and cloud platforms (Docker, Kubernetes, Open Shift, Azure/AWS).
• Strong knowledge of SQL and No
  
  SQL databases (e.g., DB2, Postgre
  
  SQL, Mongo
  
  DB).
• Experience in CI/CD, Dev Ops practices, and automated testing.

• Hands on experience integrating Large Language Models (LLMs) into backend systems.
• Strong understanding of prompt engineering techniques, including:
  • Zero shot, few shot, and chain of thought prompting
  • Prompt templates and dynamic prompt generation
  • Guardrails, validation, and hallucination reduction
• Experience building RAG based solutions using vector stores and embeddings.
• Familiarity with AI orchestration frameworks or SDKs (enterprise or open source).
• Ability to evaluate prompt and model responses for quality, bias, and consistency.

• Experience implementing OAuth
  2.0, JWT, SSL/TLS, and secure API patterns.
• Awareness of data privacy, PII handling, and AI governance in regulated environments (BFSI preferred).