Observability Platform architecture, OpenTelemetry, Distributed SaaS platforms, large-scale telemetry pipelines, and platform-building experience)

Position : Observability Platform architecture, OpenTelemetry, Distributed SaaS platforms, large-scale telemetry pipelines, and platform-building experience) : Only USA

Location : USA -Remote : candidates to work with the India team (time zone)

Type of Job : Contract : 12 Months

Experience : 15+ Years Job description as per new update Strongly align with hands-on observability platform architecture, OpenTelemetry, distributed SaaS platforms, large-scale telemetry pipelines, and platform-building experience? stronger in the implementation and delivery of observability solutions rather than in architecting and building large-scale observability platforms. Please focus on sourcing candidates with strong hands-on experience in the following areas: • Observability platform architecture • OpenTelemetry • Large-scale distributed SaaS platforms • Telemetry pipeline design and implementation • Building and scaling observability platforms from the ground up • Strong platform engineering and architecture experience Please set the expectation with the candidate that they will be working closely with the India-based development team. As a result, they will be required to maintain approximately 3–4 hours of overlap with the India team each day to support effective collaboration and communication. Must-haves: - Hands-on OpenTelemetry — OTel Collector and OTTL, plus normalizing telemetry to OTel semantic conventions - Strong Java + Spring / Spring Boot microservices (built in production) - Multi-tenant, distributed SaaS platform engineering - Building scalable observability platforms with large-scale log processing and deriving inference - Deep streaming / data-pipeline work — Kafka + Kinesis / Event Hub / PubSub; Flink / Kafka Streams; data warehousing and analytics - Multi-cloud ingestion — CloudTrail, Azure Monitor, Google Cloud Platform Audit Logs, Splunk, Sentinel, API logs - Detection engine/service (rules + ML anomaly detection), analytics for usage patterns and risk scoring, real-time alerting, immutable audit logging, and DLQ / replay pipelines

Nice-to-haves: - Kubernetes and Infrastructure as Code The strongest profiles lead with what they've built — shipping an observability or telemetry platform to production — rather than SIEM operations or security governance. That's the filter that best separates fit from near-fit here. Note : Please reach out to me at