Systems programmer analyst developing, testing, deploying, and maintaining Desjardins IT software and infrastructure solutions. Analyzing complex incidents and coordinating standardized technology solutions with business partners and architects.
About the role
- Director of Platform & Performance Engineering at Agiloft ensuring backend platform scalability and performance. Leading a backend engineering team to support AI-driven contract lifecycle management solutions.
Responsibilities
- Build and lead a high-performing Core Platform Engineering team that:
- Rapidly improves scalability, reliability, and observability of the core backend platform
- Establishes systematic load testing, regression detection, and performance benchmarking practices
- Drives measurable reductions in latency, error rates, and infrastructure cost per transaction
- Leverages modern tooling, including AI-assisted analysis, to accelerate bottleneck identification and remediation
- Partners closely with application engineering and Cloud Operations to ensure platform stability under real-world production load
- Own and drive the performance, scalability, and reliability roadmap for the backend platform in close partnership with the CTO and engineering leaders
- Prioritize performance and stability investments while balancing near-term delivery commitments.
- Establish practical performance engineering practices, including load testing, benchmarking, and regression detection.
- Proactively identify and eliminate performance bottlenecks to ensure fast, responsive user experiences at scale.
- Design and execute realistic production-scale load testing scenarios that mirror customer behavior.
- Establish performance regression gates in CI/CD pipelines.
- Drive systematic root-cause analysis of production performance incidents.
- Quantify and publish performance baselines and improvement targets.
- Establish performance baselines and drive measurable improvements in throughput, latency, and resource efficiency.
- Drive excellence in relational database architecture across MySQL and PostgreSQL environments in AWS (RDS/Aurora).
- Lead database optimization strategies, indexing improvements, and schema evolution practices.
- Partner with Cloud Operations to align infrastructure and data-layer scaling strategies.
- Improve transactional integrity, concurrency handling, and data reliability at scale.
- Lead query optimization initiatives based on real production workload analysis.
- Identify and resolve lock contention, connection pool saturation, and concurrency bottlenecks.
- Partner with Cloud Operations to right-size database infrastructure based on performance data.
- Strengthen metrics instrumentation, structured logging and tracing across backend services.
- Partner with SRE and Cloud Operations to enhance diagnostic capabilities and operational transparency.
- Define measurable performance and reliability KPIs.
- Ensure comprehensive instrumentation across critical backend paths.
- Correlate load testing results with runtime metrics and tracing data.
- Improve mean time to detect (MTTD) and mean time to resolve (MTTR) for performance incidents.
- Engage directly in cross-team architectural design reviews, complex system decisions, and strategic refactoring initiatives.
- Provide technical mentorship and elevate backend engineering standards.
- Balance strategic direction-setting with practical, hands-on execution where needed.
- Serve as a senior escalation point for complex backend performance or architectural challenges.
- Clarify backend platform ownership boundaries in partnership with Product Engineering and Cloud Operations.
- Recruit and develop a team of strong backend, database, and platform engineers.
- Set clear expectations for engineering rigor, delivery accountability, and code quality.
- Foster a culture of accountability, speed, craftsmanship, and continuous improvement.
- Partner effectively with Product Engineering and Cloud Operations to ensure cohesive platform evolution.
- Build a strong team capable of independently owning critical platform domains.
- Influence engineering standards and platform practices across multiple application teams through collaboration and technical leadership.
Requirements
- 12+ years of backend engineering experience, including senior technical leadership roles.
- Deep hands-on expertise with Java (JEE, Spring, or comparable enterprise frameworks).
- Strong proficiency in Python for tooling, automation, or services development.
- Strong understanding of distributed systems, concurrency, and scalable SaaS architectures
- Experience designing and implementing load tests.
- Experience using performance, observability, and scalability testing tools (Grafana, Jmeter, query EXPLAIN/ANALYZE, OpenTelemetry).
- Strong expertise in performance optimization of relational database access patterns, including MySQL and PostgreSQL.
- Experience evolving large-scale applications toward modular or microservices-based architectures.
- Familiarity with containerization technologies (Docker, Kubernetes).
- Experience using modern engineering tools, including AI-assisted development tools, to improve productivity and code quality.
- Ability to apply AI tools pragmatically while maintaining architectural integrity and engineering standards.
- Demonstrated ability to collaborate effectively across engineering, infrastructure, and product organizations.
Benefits
- floating holidays
- quarterly, no-questions-asked wellness day
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