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Senior, niche platform role in a metro location with moderate employer brand yields medium applicant competition.
Specialized platform, JVM, and workflow orchestration expertise reduces cross-industry transferability.
Explicit 10+ years and mandatory deep JVM, workflow, cloud, and observability expertise create strict shortlisting filters.
Design, build, and operate the core serverless execution engine and workflow orchestration platform that underpin Cognite Data Fusion's AI and automation capabilities.
Ensure platform reliability by owning uptime, latency SLOs, incident response, and preventing data loss or silent failures in workflow executions.
Architect scalable, multi-tenant, multi-cloud solutions with API-first design, observability, CI/CD, and performance optimization for industrial workloads.
10+ years of experience building and operating backend distributed systems at scale.
Expertise in JVM languages (Kotlin preferred, Java acceptable), Python (FastAPI), distributed systems, and cloud-native platforms (Kubernetes, Azure, GCP, AWS).
Hands-on experience with workflow engines (e.g., Conductor, Apache Airflow) and event-driven architectures (Kafka, Pub/Sub).
Strong knowledge of relational (PostgreSQL), non-relational databases, object storage, caching layers, and observability tools (Open-telemetry, Prometheus, Grafana).
Experienced principal-level engineer comfortable leading platform design and reliability ownership for high-throughput, multi-tenant industrial data infrastructure.
Deep understanding of distributed systems and workflow orchestration in cloud environments with a focus on composable, automated platform solutions for ML and engineering teams.
Familiar with ML workload support and industrial contextualization pipelines; values clean API and instrumentation to empower downstream teams and customers.