Sr. Software Engineer – Platform Performance & Resilience (AI-Enabled)

Responsibilities

• Architect Reliability Across Edge–Store–Cloud
• Design and implement platform mechanisms that ensure transaction integrity and availability across POS terminals, store middleware, and cloud services.
• Define and validate failure-mode strategies for intermittent connectivity, tier isolation, data replay, and synchronization conflicts.
• Engineer patterns that prevent cascading failures and support graceful degradation under real-world load.
• Engineer Performance at Retail Scale
• Define latency budgets and performance envelopes across all tiers.
• Build systems that measure and validate throughput, concurrency limits, and resource saturation.
• Collaborate with development teams to eliminate bottlenecks before production.
• Build Automated Resilience Validation
• Develop AI-enabled systems that automatically generate and execute performance and resilience validation scenarios.
• Integrate non-functional quality gates into CI/CD workflows.
• Continuously evaluate timeout, retry, circuit breaker, and backoff strategies under stress.
• Elevate Observability & Signal Quality
• Architect structured telemetry across edge, store, and cloud tiers.
• Ensure end-to-end transaction traceability.
• Improve root-cause detection by strengthening monitoring signal-to-noise ratio.
• Own Engineering Outcomes End-to-End
• Produce technical designs and failure-mode analyses.
• Implement and deploy platform components in Node.js and companion services in Java.
• Drive production-readiness improvements based on performance data.

Required Qualifications

• 4–6+ years of professional software engineering experience.
• Strong proficiency in Node.js and Java.
• Proven experience in performance engineering, reliability engineering, or distributed systems architecture.
• Demonstrated experience designing systems with deterministic timeouts, retry/backoff strategies, circuit breakers, and concurrency controls.
• Experience modeling multi-tier systems (edge, middleware, cloud).
• Solid understanding of SLOs, SLIs, and non-functional validation.
• Experience deploying services in Kubernetes-based cloud environments.
• Strong debugging and profiling skills for distributed systems.

Preferred Qualifications

• Experience building automated resilience or fault-injection systems.
• Familiarity with event-driven architectures (Kafka, Pub/Sub, MQ).
• Experience implementing structured observability frameworks.
• Exposure to AI-enabled automation or workflow orchestration.
• Experience optimizing systems in intermittently connected environments.