Principal Engineer I – Prepurchase Platform

• Identify and act on production problems without being prompted.
• Build end-to-end, high-availability systems that handle extreme traffic spikes during high-demand on-sales without degradation.
• Lead platform modernization initiatives - migrating legacy services to cloud-native, microservice-based architectures.
• Design and implement streaming and event-driven solutions using Kafka/g RPC, enabling real-time data flow across services.
• Embed deeply in a specific service area when needed, or work horizontally across teams to solve cross-cutting problems.
• Champion resilience patterns: circuit breakers, graceful degradation, bulkheads, and auto-scaling strategies.
• Collaborate with the Enterprise Architecture team on architectural decisions and evolve engineering standards across the Prepurchase domain.
• Partner with product, security, and SRE teams to align technical decisions with business priorities.
• Drive observability improvements - ensuring services are instrumented for monitoring, alerting, and rapid incident response.
• Identify and eliminate single points of failure, improving system reliability and reducing on-call burden.
• Apply AI and machine learning tools to improve developer productivity, automate operational tasks, and enhance system capabilities.
• Evaluate and introduce new technologies that improve performance, reliability, or engineering velocity.

Requirements

• Proven ability to reason about distributed systems tradeoffs - scalability, consistency, availability, latency and make defensible design decisions under real constraints.
• Proven experience writing production code and building high-traffic systems at scale.
• Expertise in Java (17+); and the JVM, with strong command of JVM internals, garbage collection behavior, and performance tuning under load.
• Hands‑on experience with a reactive, non-blocking framework (Vert. x, Spring Web Flux, or equivalent) and asynchronous, event‑driven service design.
• Deep experience with stream processing and event‑driven architecture - Kafka Streams, Apache Flink, or equivalent.
• Proven track record building high‑throughput, low‑latency systems where tail latency, backpressure, and memory pressure are first‑class design concerns.
• Strong command of g RPC (including streaming RPC) and binary serialization formats such as Flat Buffers, Avro, or Protobuf, with schema evolution via a registry.
• Familiarity with Data‑Oriented Design (Do D) - structuring code around how data is laid out, accessed, and transformed for cache efficiency and throughput.
• Experience with compact, search‑oriented data structures (e. g. Roaring Bitmap, succinct/bitset representations) for representing large in‑memory state efficiently.
• Experience with search engines (Elasticsearch, Solr) for discovery workloads is a plus.
• Strong grasp of microservice design, service mesh (Istio/Envoy), API contract evolution, and backend‑for‑frontend patterns, including Graph QL APIs and Web Socket subscriptions for real‑time client delivery.
• Hands‑on experience with AWS (EKS) and cloud‑native operations - containerization (Docker, Kubernetes), packaging and deploy tooling (Helm, Kustomize), and infrastructure‑as‑code (Terraform).
• Proficiency with caching strategies (Redis, CDN layer caching) and their application to high‑traffic systems.
• Solid understanding of CI/CD pipelines (Git Lab CI), and progressive deployment strategies (blue‑green, canary).
• Experience designing for high availability - mult‑region active‑active/active‑passive architectures, failover strategies, disaster recovery.
• Proficiency with AI/ML tools and techniques - using LLMs, AI‑assisted development, and automation to accelerate engineering workflows.
• Familiarity with observability tooling: Grafana, Splunk, Prometheus, Open Tracing, or equivalent.
• Strong understanding of security best practices - OAuth/OIDC, input validation, secrets management.
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