Sr. Service Resiliency Engineer

Genesys Telecommunications Laboratories, Inc.
Ontario
CAD 80,000 - 120,000
Job description

Sr. Service Resiliency Engineer page is loaded

Sr. Service Resiliency Engineer

Apply locations Ontario, Canada time type Full time posted on Posted 17 Days Ago job requisition id JR107509

Genesys empowers organizations of all sizes to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, organizations can accelerate growth by delivering empathetic, personalized experiences at scale to drive customer loyalty, workforce engagement, efficiency and operational improvements.

Join our Resiliency Engineering team at Genesys, where you’ll drive platform reliability at scale. As a Senior Service Resiliency Engineer, you will analyze system trends, lead resilience initiatives, and shape the architectural direction of our microservices platform. This is a hands-on, high-impact role where you’ll work closely with engineering teams to implement innovative resilience strategies across our global infrastructure.

Key Responsibilities:

  1. Analyze system stability trends and identify areas for improvement across distributed services
  2. Implement resilience patterns (e.g., circuit breakers, retries, bulkheads, load shedding) to reduce system failures
  3. Develop and maintain automated tools for service health measurement and static analysis
  4. Guide engineering teams in applying best practices in system resilience and observability
  5. Apply chaos engineering principles to proactively identify weaknesses in the platform
  6. Research and evaluate emerging technologies related to service resilience and high availability
  7. Drive enablement efforts through documentation, standards, and presentations to technical and non-technical audiences
  8. Manage the full development lifecycle for resilience-focused tools and enhancements
  9. Collaborate with platform and service teams to embed reliability into design decisions
  10. Contribute to team-wide initiatives that support Genesys’ innovation and customer trust

Qualifications:

  1. Minimum 5 years of experience in software engineering using Python, Go, Java, or TypeScript
  2. Strong understanding of microservices architecture and distributed systems
  3. Minimum 2 years of hands-on experience with AWS
  4. Proven ability to diagnose and resolve complex systems issues
  5. Proficient with observability tools such as CloudWatch, New Relic, or SumoLogic
  6. Clear and effective communication skills, both technical and non-technical
  7. Data-driven approach to problem-solving with strong analytical skills
  8. Commitment to continuous learning and embracing empathy in technical collaboration

Preferred Qualifications:

  1. Previous experience in SRE or DevOps roles
  2. Experience implementing resilience patterns such as retries, timeouts, and bulkheads
  3. Exposure to chaos engineering or failure injection frameworks
  4. Familiarity with performance testing tools and techniques
  5. Hands-on experience with AWS CloudFormation, Terraform, and CI/CD pipelines
  6. Experience with OpenTelemetry and distributed tracing
  7. Understanding of SLIs, SLOs, and error budgets
  8. Contributions to open-source projects or technical blogs

Why Join Us?
Be part of a team that’s redefining resilience at Genesys—where your ideas will directly impact the experiences of millions of users worldwide. We foster a culture of empathy, innovation, and collaboration, and we’re looking for leaders who thrive on solving tough engineering problems with creativity and heart.

About Genesys:

Genesys empowers more than 8,000 organizations in over 100 countries to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, Genesys delivers the future of CX to organizations of all sizes so they can provide empathetic, personalized experience at scale.

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