Sr. AI Java Developer

Role

We are seeking a Senior AI Java Developer to design, develop, and integrate AI-powered enterprise applications. The role focuses on leveraging Large Language Models (LLMs), Generative AI frameworks, and cloud AI services while building scalable Java-based microservices and backend services.

Key Responsibilities

• Design, develop, and deploy AI-powered enterprise applications using Java.
• Build intelligent applications utilizing Generative AI and LLMs.
• Use AI-assisted development tools (AI coding assistants and code generation agents) to accelerate development while ensuring code quality, security, and maintainability.
• Integrate AI capabilities with enterprise systems through REST APIs and microservices.
• Develop backend services using Spring Boot and Spring AI.
• Implement prompt engineering, AI orchestration, and agent-based workflows.
• Build scalable APIs to consume OpenAI, Azure OpenAI, Google Vertex AI, AWS Bedrock, or similar platforms.
• Collaborate with business analysts, architects, UX teams, and DevOps engineers.
• Optimize AI application performance, scalability, security, and cost.
• Participate in code reviews, testing, and CI/CD implementation.
• Stay current with emerging AI technologies and recommend improvements.

Requirements

Must have / Core technical skills

• Java 17+
• Spring Boot, Spring AI, Spring Security
• Hibernate / JPA
• REST APIs, Microservices
• Maven or Gradle
• Experience with LLMs, Generative AI, Prompt Engineering, AI Agents
• Experience with OpenAI / Azure OpenAI APIs
• Databases: PostgreSQL, SQL Server, MongoDB, Redis
• Cloud & DevOps: Azure, AWS, GCP, Docker, Kubernetes
• CI/CD and automation: GitHub Actions or Jenkins; Terraform preferred

Qualifications

• Bachelor’s degree in Computer Science or related field
• 3–8+ years of Java development experience
• 2+ years working on AI/GenAI solutions preferred
• Strong knowledge of software architecture and distributed systems
• Excellent analytical and communication skills

Preferred / Nice-to-have

• Kafka / event streaming
• Elasticsearch
• Azure AI Foundry, Azure AI Search
• AWS Bedrock
• MCP (Model Context Protocol)
• Semantic Kernel (Java interoperability)
• Observability tools: Grafana, Prometheus
• Experience with Git and Agile/Scrum methodologies
• Understanding of AI governance, responsible AI, data privacy, model monitoring, AI observability
• CI/CD pipelines and DevSecOps practices
• Familiarity with enterprise integration patterns and API management

Location & Schedule

• Hybrid: must be in downtown Toronto and/or client office a minimum of 4 days per week (subject to change).