Zipher

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 Data Analyst to own the intelligence layer on top of Zipher's autonomous execution engine. You will turn enterprise-scale telemetry from production data and AI workloads into the metrics, models, and answers that engineering, product, and executives run on. What You'll Do Own end-to-end analytics for core product areas: cost optimization, SLA, failure rates, and workload efficiency Define and instrument the product KPIs and dashboards used daily by engineering, product, and the executive team Build and maintain production-grade data pipelines and models on enterprise-scale telemetry — Databricks/Spark, logs, metrics, and traces Partner closely with backend and ML engineers to translate complex multi-cloud performance data into actionable platform intelligence Run deep-dive analyses and experiments that validate features, quantify impact, and uncover new optimization opportunities 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 data engine behind autonomous AI workloads? Hit Apply. What You'll Bring Experience in an elite IDF technology/intelligence unit (e.g. 8200, Mamram, Matzpen) 3–6+ years in Data Analytics, Product Analytics, or Analytics Engineering, including ownership of analysis that drove real product decisions Advanced, production-level SQL and strong Python (pandas, numpy; scikit-learn is a plus) Proven experience with large-scale datasets, scalable data models, and end-to-end data products running in production Strong applied statistics and exploratory analysis, plus the technical storytelling to make findings land with non-technical stakeholders A high-agency, engineering-first mindset: you enjoy ambiguous, high-leverage problems and take responsibility for the correctness and quality of what you ship Nice to Have Experience with Databricks, Snowflake, Spark, AWS Athena/Glue, dbt, or Airflow/Prefect Background in cloud infrastructure metrics, compute engines, or MLOps/AIOps telemetry B.Sc. in Computer Science, Industrial Engineering, Statistics, or Mathematics, or equivalent

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. Autonomous execution is a new category, and we are the ones defining it — already running in production inside Fortune 500 environments, where being wrong is not an option. The team is deliberately talent-dense; every hire changes what we are able to build next. We are looking for a Full Stack Engineer to build our enterprise web application and control plane alongside our senior engineers. You will build the services, APIs, and interfaces that let engineering leaders monitor, understand, and control autonomous data workloads in real time. This is a backend-heavy role. It is best suited for candidates whose primary expertise and passion lie in backend development. What You'll Do Ship features end to end across the control plane: services, APIs, and the interfaces built on top of them Build scalable, low-latency APIs over live telemetry from production data and AI workloads Build high-performance, real-time visual interfaces and explainability tools for monitoring an autonomous data platform Partner closely with backend, AI, and distributed systems engineers to ship complex, mission-critical platform features Own quality for what you ship: testing, CI/CD, observability, and the operational bar for a product enterprise customers depend on What We Offer A chance to build the core execution engine for a new category of autonomous data platform — a product already running inside Fortune 500 environments Real ownership from day one: you own what you ship end to end, and you grow into owning whole domains of the control plane Engineering problems that are genuinely hard: real-time telemetry at enterprise scale, low-latency APIs, and interfaces that make autonomous decisions readable A talent-dense team: direct access to the founders and to the engineers who designed the platform, and a bar that pulls you up Top-of-market compensation and meaningful equity Ready to build the control plane for an autonomous data platform? Hit Apply. What You'll Bring 4+ years of full stack engineering experience building production-grade web applications, with the weight of it on the backend Strong production experience with Python (FastAPI) on the backend and React with TypeScript on the frontend 2+ years of hands-on production experience with AWS — Lambda, ECS, Fargate, DynamoDB, ECR, S3, API Gateway, or EventBridge Experience from startup engineering teams, building cyber, AI, or data-intensive products where scale and latency are the hard part BSc in Computer Science, Electrical Engineering, or a related engineering discipline A high-agency, maker mindset: strong product intuition, engineering craftsmanship, and full ownership of what you ship Nice to Have Experience as a developer in an elite IDF technology unit (e.g. 8200, Mamram, Ofek, Matzpen) or another high-performance engineering environment Experience designing real-time, event-driven, or high-throughput cloud architectures Depth in modern frontend: TypeScript, state management, and component or micro-frontend architectures Background in observability and telemetry dashboards, developer-facing platforms, or large-scale data platforms

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. Autonomous execution is a new category, and we are the ones defining it — already running in production inside Fortune 500 environments, where being wrong is not an option. The team is deliberately talent-dense; every hire changes what we are able to build next. We are looking for a Senior Full Stack Engineer to own Zipher's entire product surface — the control plane that turns autonomous decisions into something engineering leaders can see, trust, and act on. You will own it end to end: the services and APIs behind it, and the real-time interfaces built on top of them. This is a backend-heavy role. It is best suited for candidates whose primary expertise and passion lie in backend development. What You'll Do Own the product surface end to end: architecture, services, APIs, and the real-time interfaces built on top of them. Set the technical direction of the control plane — stack, data contracts, and the patterns every engineer after you builds on. Build high-throughput services that turn live telemetry from production data and AI workloads into decisions, and the explainability layer that makes those decisions readable. Work directly with the founders on what gets built next, and lead the technical moves that follow — from what enterprise customers need to the architecture that answers it. Drive quality end to end: testing, CI/CD, observability, and the operational bar for a product Fortune 500 engineering teams run in production. What We Offer A product that is already winning: a new category of autonomous data platform, in production inside Fortune 500 environments. A domain of your own: you lead it end to end — the architecture, the stack, and the patterns every engineer after you builds on. A seat on the core team: you are one of the engineers deciding what the platform becomes, not one implementing someone else's decisions. Engineering problems that are genuinely hard: real-time telemetry at enterprise scale, distributed decisions, and an explainability layer teams trust in production. Engineers worth learning from: a deliberately talent-dense team, direct work with the founders, and a bar that pulls everyone up. Room to grow and to lead: your ownership widens as the platform does, and the people who lead moves here keep leading them. Top-of-market compensation and a meaningful equity package. Ready to own the control plane for an autonomous data platform? Hit Apply. What You'll Bring 7+ years of full stack engineering experience, with most of it on the backend — production services, APIs, and data-intensive systems. Strong production mastery of Python (FastAPI) and TypeScript/React, plus 2+ years of hands-on production experience with AWS — Lambda, ECS, Fargate, DynamoDB, ECR, S3, API Gateway, or EventBridge. Experience from leading startup engineering teams, building cyber, AI, or data-intensive products where scale, latency, and correctness are the hard part. A track record of taking systems from architecture to production at scale, and owning them once they are there. BSc in Computer Science, Electrical Engineering, or a related engineering discipline. A high-agency, maker mindset: strong product intuition, engineering craftsmanship, and full ownership of what you ship. Nice to Have Experience as a developer in an elite IDF technology unit (e.g. 8200, Mamram, Ofek, Matzpen) or another high-performance engineering environment. Experience designing real-time, event-driven, or high-throughput cloud architectures. Depth in modern frontend: TypeScript, state management, and component architectures for data-dense interfaces. Background in observability and telemetry products, developer-facing platforms, or large-scale data platforms such as Spark, Databricks, or Snowflake.

Zipher is building the Autonomous Execution Layer for cloud data and AI, a new category we are defining: $50M raised and live in Fortune 500 environments. We are hiring a Solution Engineer (FDE), Forward Deployed Engineer, to join a deliberately talent-dense team. As our Solution Engineer (FDE), you will work embedded with the engineering teams of the world's largest data and AI organizations, write the code that connects Zipher to their live workloads, and own every deployment until it runs and delivers in production. Our Solution Engineers work the way Forward Deployed Engineers do: as software engineers first. Whether your title today is Solutions Engineer, Forward Deployed Engineer, Solutions Architect, or tech lead, you grew up as a developer, and you spend your days in code. What You'll Do Own Zipher's technical win with its enterprise customers Deploy Zipher into the customer's production: build the integrations, connectors, and deployment code that plug the engine into Databricks, Spark, Kubernetes, and AWS Write production code in the field: debug live pipelines, ship fixes and extensions, and turn every one-off into a reusable building block Own each deployment end to end, through to the measured impact on cost, performance, and reliability Bring the field back into the product, with core engineering and the founders What We Offer A product that is already winning: in production inside Fortune 500 environments An engineering seat in the field: as an FDE, you write the code and own the deployment architecture, and what you build shapes what we ship next Engineers worth learning from: a deliberately talent-dense team and direct work with the founders Room to grow and to lead: your ownership widens as the platform does Top-of-market compensation and a meaningful equity package The teams running the world's largest data and AI workloads are about to stop tuning them by hand. Come be the engineer who puts it in production - Hit Apply. What You'll Bring 5+ years writing production code as a software engineer: backend, full stack, or data Strong production coding in Python or another backend language, and hands-on depth in cloud and data platforms: AWS, Databricks, Spark, Kubernetes, or adjacent Solutions built directly with B2B or B2E customers, deployed into their production systems in real time Strong customer-facing abilities and a customer-oriented mindset: you earn the trust of senior engineers in their own environment A high-agency engineering mindset: as comfortable in a customer's codebase as in your own Nice to Have BSc in Computer Science, Electrical Engineering, or a related engineering discipline A developer seat in an elite IDF technology unit (8200, Mamram, Ofek, Matzpen) or another high-performance engineering environment Databricks, Apache Spark, Snowflake, Airflow, dbt, or cloud-native data platforms Background in platform engineering, SRE, or data engineering