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Cognite is seeking a Senior Software Engineer to design, build, and operate the core serverless execution engine and Workflows orchestration layer that power the Cognite Data Fusion (CDF) platform. This role sits at the heart of industrial digitalization, serving Fortune 500 companies managing critical operational data.
You will own platform reliability, scalability, and performance across multi-tenant, multi-cloud environments. Key responsibilities include:
• Design and operate serverless execution engines and workflow orchestration primitives that enable AI and automation capabilities
• Own uptime, latency SLOs, and incident response for platform services, ensuring deterministic function execution and zero-loss workflow progression
• Architect for high-throughput, multi-tenant workloads with graceful degradation under pressure; design scheduling, queueing, and retry mechanisms
• Define clean, API-first architecture with versioned REST and event-driven APIs that internal teams and external customers depend on
• Instrument services with distributed tracing, structured logging, and alerting (OpenTelemetry, Prometheus, Grafana, Honeycomb) to surface failures proactively
• Champion test automation (unit, integration, smoke) and maintain CI/CD pipelines for confident production deployments
• Profile and resolve bottlenecks in execution throughput, cold-start latencies, and cross-service call chains
• Model compute and storage costs; identify optimizations that reduce cloud spend without sacrificing reliability
Required: 6–8 years building and operating production backend services at scale. Deep expertise in JVM languages (Kotlin preferred, Java acceptable), Python (FastAPI), distributed systems patterns, and cloud-native design (Kubernetes, Azure, GCP, AWS). Hands-on experience with workflow engines (Conductor, Apache Airflow), event-driven architectures (Kafka, Pub/Sub), relational and non-relational databases, object storage, caching layers (Redis), and observability stacks (OpenTelemetry, Prometheus, Grafana).
Bonus: Experience supporting ML workloads in production, industrial knowledge graphs, entity resolution, NLP/CV pipelines for industrial data, or full-stack awareness (React, TypeScript).
