Senior Software Engineer (JAVA)
HybridMontréal, Quebec, Canada
Job Summary
Lead high-level design for complex, cross-service features and drive the engineering agenda for assigned product areas. Own and implement critical product components using advanced Java, ensuring correctness, performance, and long-term maintainability with comprehensive test coverage. Direct agentic AI tools across the full engineering workflow, including code generation, testing, refactoring, and debugging, while critically evaluating outputs for quality and security. Produce architecture documentation, design docs, and ADRs, and communicate technical decisions clearly across engineering, product, and DevOps teams. Participate in hiring processes and identify architectural limitations to contribute to product roadmap planning.
Required Qualifications
- Expert Java engineering: Deep understanding of Java internals — GC tuning, Collections Framework, advanced concurrency (java.util.concurrent, multithreading), NIO/NIO2, performance profiling, and heap-dump analysis
- Mastery of Spring Framework (IoC/DI, bean lifecycle, Spring Boot)
- SOLID principles, Clean Code practices, and GoF design patterns
- Expertise in monolith and microservices architectural styles — including migration patterns and domain-driven decomposition
- Inter-process communication design (REST, gRPC, messaging)
- Transaction management in distributed systems (Sagas, 2PC)
- CQRS, Event Sourcing, and external API design focused on scalability, security, and documentation
- Experience designing high-availability and high-load systems on GCP (preferred), AWS, and Azure
- Cloud security best practices: IAM, VPC, data encryption, JWT/JWS/JWE
- Infrastructure as Code (Terraform or equivalent) and Twelve-Factor App methodology
- Implementing full observability stacks: structured logging, distributed tracing, metrics, and alerting
- SLI/SLO/SLA frameworks
- Deployment strategies: Rolling Updates, Blue/Green Deployments, Canary Releases
- Practitioner-level command of agentic AI tools applied to software engineering — encompassing prompt engineering techniques, AI context management and its limitations, sub-agents, skills and plugins, multi-agent orchestration, and team-of-agents architectures
- Experience with Claude Code (Anthropic), Codex (OpenAI), or equivalent is mandatory
Desired Qualifications
- Experience with GCP (preferred)
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