Senior Software Engineer – Performance & Resilience

About the role

Payments Network Technology is looking for a Senior Software Engineer focused on performance, resilience and chaos engineering for critical payment‑network services. The role will define test approaches, run controlled experiments and help teams improve capacity, recovery and operational behaviour.

Key responsibilities

• Define performance, scalability, resilience and chaos‑testing strategies for services and platforms.
• Design and execute load, stress, endurance, failover and controlled‑failure experiments.
• Analyze latency, throughput, resource consumption, bottlenecks and recovery behaviour.
• Partner with engineering and operations to set service‑level objectives and production‑readiness criteria.
• Automate performance and resilience tests and integrate them into delivery pipelines.
• Document findings, prioritize risks and track remediation to closure.
• Promote repeatable practices for capacity planning, observability and failure‑mode validation.
• Guide less‑experienced team members and own complex work from analysis through production support.

Required profile

• Experience working in Agile delivery environments across the software development lifecycle.
• Strong communication, collaboration and stakeholder‑management skills.
• Ability to work with globally distributed product, engineering, architecture, operations and business teams.
• Experience applying AI‑driven product validation to improve efficiency and identify defects early.
• Hands‑on experience with AI‑assisted engineering tools such as GitHub Copilot and Claude CLI.
• Payments or financial‑services domain knowledge is preferred.

Required skills

• Performance engineering tools: JMeter, LoadRunner, Gatling or equivalents.
• Java development and profiling with Dynatrace and Java Microbenchmark Harness (JMH).
• Knowledge of distributed systems, microservices, APIs, messaging, databases and cloud platforms.
• Experience with resiliency patterns, failover, capacity analysis and controlled chaos experiments.
• Ability to interpret system metrics and communicate actionable findings.
• Bachelor’s degree in Computer Science, IT, Engineering or equivalent practical experience.