We're looking for a Senior Backend Engineer to own core components of our autonomous execution engine. You'll design and scale distributed services that make real-time infrastructure decisions across multi-cloud environments.
Nice to Have
Experience with large-scale data/compute platforms: Spark, Databricks, Trino, Flink, or Snowflake
Exposure to MLOps / AIOps infrastructure or serving ML models in production
Background in cloud cost optimization, FinOps, or workload efficiency at scale
Prior service as a Software/Backend Engineer in an elite IDF technology unit (8200, Mamram, Ofek, etc.)
What We Offer
Top-of-market compensation + significant equity (above market standard)
Direct ownership over core platform architecture and autonomous infrastructure decisions
Work with founders, engineering leads, and global enterprise customers on mission-critical systems
Small, high-impact team that values ownership, speed, and technical depth over process
Ready to build the future of autonomous cloud infrastructure? Hit Apply.
What You'll Do
Architect and scale high-throughput, low-latency backend engines that execute real-time autonomous infrastructure decisions
Design resilient spot-loss mitigation and self-healing systems ensuring zero downtime across enterprise-grade cloud environments
Expand our ML-driven orchestration core to support complex AI training/inference workloads and distributed data pipelines
Solve complex distributed state challenges across massive scale, event streams, and real-time telemetry
Build explainability and telemetry layers that give enterprise engineering leadership full visibility into autonomous platform actions
What You'll Bring
6+ years of backend engineering experience with focus on distributed systems, infrastructure, or core product architecture
Production mastery of Python or Go as your primary development language
Deep, hands-on production expertise with AWS at scale (EMR, DynamoDB, Kinesis, Lambda, S3, API Gateway)
Proven background in distributed computing or infrastructure engines (Kubernetes, Spark, high-throughput schedulers, or distributed message brokers)
Strong production ownership mindset: debugging complex issues, maintaining high availability, and shipping robust system fixes
