Zipher is building the Autonomous Execution Layer for cloud data and AI workloads. Backed by $50M in funding , we dynamically orchestrate clusters, predict bottlenecks, and auto-heal infrastructure in real time — with zero human intervention . Our platform runs in production at global enterprise customers, including Fortune 500 companies , delivering mission-critical resilience and sub-second optimization We are looking for a Senior Backend Engineer to build the systems behind Zipher’s autonomous execution engine. You will own core infrastructure that turns high-volume telemetry and changing cloud conditions into reliable, real-time decisions across production data and AI workloads.
What You’ll Do
* Architect and scale the core backend services that power real-time workload orchestration, optimization, and self-healing
* Build resilient, high-throughput systems for processing distributed state, event streams, and production telemetry at scale
* Design infrastructure that makes autonomous decisions observable, explainable, and safe for enterprise engineering teams
* Partner closely with data, ML, and platform engineers to bring optimization models and control loops into reliable production systems
* Drive architectural decisions, raise the engineering bar, and own services from design through deployment, observability, and incident response
What We Offer
* A chance to build the core execution engine for a new category of autonomous data platform High ownership from day one : real architectural influence, direct exposure to founders, and responsibility for mission-critical systems
* Technical, high-velocity team that values curiosity, speed, and engineering craftsmanship Top-of-market compensation and meaningful equity Ready to build the infrastructure that lets data and AI workloads run autonomously? Hit Apply.
What You’ll Do
* Architect and scale the core backend services that power real-time workload orchestration, optimization, and self-healing
* Build resilient, high-throughput systems for processing distributed state, event streams, and production telemetry at scale
* Design infrastructure that makes autonomous decisions observable, explainable, and safe for enterprise engineering teams
* Partner closely with data, ML, and platform engineers to bring optimization models and control loops into reliable production systems
* Drive architectural decisions, raise the engineering bar, and own services from design through deployment, observability, and incident response
What We Offer
* A chance to build the core execution engine for a new category of autonomous data platform High ownership from day one : real architectural influence, direct exposure to founders, and responsibility for mission-critical systems
* Technical, high-velocity team that values curiosity, speed, and engineering craftsmanship Top-of-market compensation and meaningful equity Ready to build the infrastructure that lets data and AI workloads run autonomously? Hit Apply.
Requirements:
What You’ll Bring 6+ years of backend engineering experience , including ownership of production-grade distributed systems, infrastructure platforms, or core product architecture
* Strong production experience with Python or Go , and a track record of designing robust APIs, services, and asynchronous workflows
* Deep hands-on experience operating cloud-native systems on AWS at scale , including EMR, DynamoDB, Kinesis, Lambda, S3, or API Gateway
* Experience with distributed computing or infrastructure engines , such as Kubernetes, Spark, high-throughput schedulers, streaming platforms, or message brokers
* A high-agency, engineering-first mindset : you enjoy ambiguous, high-leverage problems and take responsibility for reliability, performance, and quality
Nice to Have
* Experience with large-scale compute and data platforms , including Spark, Databricks, Trino, Flink, or Snowflake
* Experience building infrastructure for AI/ML workloads , MLOps/AIOps systems, or production model-serving environments
* Familiarity with cloud cost optimization, FinOps, workload scheduling , or efficiency optimization at scale
* Experience in an elite IDF technology unit (e.g. 8200, Mamram, Matzpen) or another high-performance engineering environment
What You’ll Bring 6+ years of backend engineering experience , including ownership of production-grade distributed systems, infrastructure platforms, or core product architecture
* Strong production experience with Python or Go , and a track record of designing robust APIs, services, and asynchronous workflows
* Deep hands-on experience operating cloud-native systems on AWS at scale , including EMR, DynamoDB, Kinesis, Lambda, S3, or API Gateway
* Experience with distributed computing or infrastructure engines , such as Kubernetes, Spark, high-throughput schedulers, streaming platforms, or message brokers
* A high-agency, engineering-first mindset : you enjoy ambiguous, high-leverage problems and take responsibility for reliability, performance, and quality
Nice to Have
* Experience with large-scale compute and data platforms , including Spark, Databricks, Trino, Flink, or Snowflake
* Experience building infrastructure for AI/ML workloads , MLOps/AIOps systems, or production model-serving environments
* Familiarity with cloud cost optimization, FinOps, workload scheduling , or efficiency optimization at scale
* Experience in an elite IDF technology unit (e.g. 8200, Mamram, Matzpen) or another high-performance engineering environment
This position is open to all candidates.
