Principal Software Engineer

[Industry: Software Development | Type: Full-time | Level: Not Applicable] OverviewModern ads platforms run on always-on, real-time data: streaming events, feature computation, near-real-time aggregations, and low-latency serving to power ML models that operate at massive scale under strict freshness, cost, and reliability requirements.Microsoft Ads builds and operates large-scale, latency-sensitive systems that serve billions of requests. We are looking for a Principal Software Engineer who is hands-on with production coding and system design to build the real-time data pipelines and feature/embedding materialization systems that feed online stores/caches and integrate tightly with ML inference serving.This Role Is Ideal For Engineers Who Enjoybuilding robust streaming + ETL systems (correctness, idempotency, backfills, late data),owning SLOs with strong observability and operational maturity,and optimizing end-to-end performance and cost across compute, storage, and serving integrations.Primary success metrics are freshness, correctness, latency, reliability, and cost in production.ResponsibilitiesDesign and implement real-time streaming ETL / feature pipelines (e.g., Flink or Spark Structured Streaming) that meet strict freshness and correctness constraints.Build and operate reliable messaging and ingestion with Kafka/Pulsar (partitioning strategy, retries, ordering guarantees, DLQs, backpressure handling).Own data contracts between producers, pipelines, and consumers: schema evolution, versioning, compatibility, validation, and safe rollout.Implement production-grade backfill/replay workflowsDefine and meet SLOs using OpenTelemetry/Prometheus/Grafana for metrics, tracing, dashboards, alerting, and incident response readiness.Integrate pipelines with online stores/caches and ML consumers (feature stores, embedding pipelines, LLM API calls, online/offline consistency patterns).Partner with applied scientists on feature/embedding definitions, validation, and end-to-end quality measurement.Optimize end-to-end performance and efficiency: CPU/memory/I/O, serialization, caching, network overhead, concurrency, and pipeline compute cost.Contribute to serving/inference integrations where needed (e.g., Triton/ONNX Runtime/TensorRT) including batching and latency/cost tradeoffs.Ship safely with CI/CD, automated testing (unit/integration/data quality), and operational playbooks/runbooks.QualificationsRequired Qualification:Bachelor’s or Master’s degree in Compu...