Why This Role Stands Out
You can significantly advance your career by building cutting-edge Agentic AI capabilities into enterprise Java backend systems, leveraging AI-assisted development tools for impactful innovation. This hands-on role is perfect for experienced backend engineers with a passion for AI and a desire to shape the future of software development. Embrace this opportunity to grow your skills and contribute to a leading technology company.
Quick Overview
Job Description
Senior Java Engineer Agentic AI
Position Overview
We are hiring 3 Senior Software Engineers (Architect level) and 5 Senior Software Engineers (Technical Lead level) to join a team building Agentic AI capabilities into enterprise Java backend systems. This is a hands-on engineering role for candidates who combine deep backend expertise with practical, day-to-day use of AI-assisted development tools.
| Location | Toronto, ON (Hybrid - 3 days/week onsite) |
| Duration | 6-month contract, with possible extension up to 1 year - or FTE |
| Interview Process | 1-hour interview, including a live virtual whiteboarding session (candidates must have access to a diagramming tool such as Draw.io) |
Required Skills & Experience
- 8+ years of hands-on Java backend development experience.
- Strong expertise in Java, Spring Boot, and Microservices.
- Proven experience in software design, architecture, and end-to-end implementation.
- Hands-on experience with GitHub Copilot and/or Claude as part of the software development lifecycle.
- Good understanding of AI/ML concepts and AI-assisted software development.
- Experience working with Agentic AI, AI agents, workflows, skills, or AI-powered coding tools.
- Strong system design and problem-solving skills.
- Excellent communication and collaboration skills.
- Ability to work independently in ambiguous environments with minimal supervision.
What We're Looking For
- Technical Depth - Strong Java, Spring Boot, backend architecture.
- Research Mindset - Curiosity, innovation, asks insightful questions.
- AI Adoption - Uses AI tools extensively throughout the SDLC.
- System Design - Scalability, performance, trade-off analysis.
- Communication - Explains concepts clearly and confidently.
- Problem Solving - Breaks down complex problems methodically.
- Energy & Ownership - Demonstrates enthusiasm, confidence, and proactive thinking.
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