Director, Platform & Performance Engineering

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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

Job type

Full Time

Experience level

Lead

Salary

Not specified

Degree requirement

No Education Requirement

Tech skills

AWSCloudDistributed SystemsDockerGrafanaJavaJMeterKubernetesMicroservicesMySQLPostgresPythonSpring

Location requirements

RemoteCanada

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