Senior System Software Engineer - Signing Platform

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8835820

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30/09/2026

Senior DevOps Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

our company's platform runs inside the security stacks of enterprise customers, processing live detection and telemetry data from SIEM, EDR, and SOAR systems at real scale. Until now, infrastructure has been built and carried by the founding engineering team alongside everything else. You will be the first dedicated owner of it. That means designing our company's cloud foundation across GCP and AWS, building the deployment, scaling, and observability layers from the ground up, and setting the standards the rest of engineering builds on. It also means holding a bar that most startups can defer and our company cannot: we sell to security teams who audit their vendors seriously, so how we run our own infrastructure is part of how we win. This is a hands-on senior role with real architectural authority, and as engineering grows you become the person others learn cloud and infrastructure from.
What you'll be doing
Multi-cloud architecture: Own the design and implementation of our company's multi-cloud architecture across GCP and AWS, including the cross-cloud standards, boundaries, and tradeoffs that keep two providers from becoming twice the complexity.
Infrastructure as code: Build and maintain the entire environment in Terraform, so infrastructure is reviewable, reproducible, and scales without a person in the loop.
Deployment pipelines from scratch: Create the CI/CD foundation that lets a small team ship quickly and safely, with the testing, gating, and rollback paths that make fast releases boring rather than risky.
Kubernetes at data scale: Run and scale the Kubernetes and containerized workloads behind our company's security data processing, where volume, latency, and cost pressure all show up at once.
Security of our own stack: Own identity, access, secrets, network boundaries, and infrastructure hardening to a standard that holds up under customer security review.
Reliability and visibility: Build the logging, monitoring, and alerting layer that tells us something is wrong before a customer does, and make on-call sustainable as the system grows.
Technical direction: Partner directly with the founding engineering team on architectural decisions, and raise the infrastructure and cloud fluency of every engineer who joins after you.

Requirements:
Senior infrastructure depth: 7+ years as a DevOps or Site Reliability Engineer, with production systems you built and carried, not only inherited.
Multi-cloud experience: Hands-on work with core services across both GCP (GCE, GKE, Cloud Storage, VPC) and AWS (EC2, EKS, S3, RDS), and clear judgment on when running in two clouds is worth the cost.
Kubernetes and containers: Strong production experience with Docker and Kubernetes, including scaling, resource management, and debugging clusters under real load.
Infrastructure as code: Proven Terraform experience (or Pulumi) in complex, multi-provider environments, with a preference for codified over manual.
Pipelines and scripting: Built CI/CD from zero with GitHub Actions, GitLab CI, or Jenkins, backed by strong Python or Bash.
Security instincts: A DevSecOps mindset and real exposure to security best practices. Background in a cybersecurity or otherwise security-sensitive environment is a strong advantage.
0-to-1 ownership: Comfortable being the first and only person in a domain, making decisions without an existing playbook, and staying close to the work while setting direction for others.

This position is open to all candidates.

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8837817

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24/09/2026

Senior Devops Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

is looking for a DevOps engineer to own our infrastructure end to end.
You would be our only one. There is no platform team to join and no one to hand you a ticket queue. There is plenty of work, and most of it is on this page. You will set the technical direction as we grow, report to the Head of Engineering, and work directly with every engineer on the team.
We run on AWS and Kubernetes and deploy through GitOps. Our use of AI in engineering is growing quickly, and the infrastructure behind it has not caught up yet. Building that is a real part of this job.
What Youll Do:
Own all of our infrastructure. Kubernetes, AWS, and the core services around them. The foundation was built properly and the team has kept it running between other priorities. You are not inheriting a mess. What it has not had is a full-time owner. Reliability, cost, security posture, and the roadmap all become yours.
Own CI/CD. Every services build and deploy pipeline, and the self-hosted runner infrastructure underneath. We ship fast and we are working on shipping faster. One of our engineers is automating more of it right now, and you will take that over and push it further. The interesting problem is adding the safety a growing company needs without turning deploys into something people dread.
Help us shape the infrastructure behind our AI development. Our engineers use coding agents every day and that use keeps growing. We do not have a clear path for the infrastructure behind it yet, and you will help us find one. One direction we are exploring is moving agents off laptops and into the cloud, with a sandbox environment per engineer so an agent keeps working after the laptop is closed. Deciding whether that is the right answer, and building what we choose, is part of this job.
Scale how we deploy to customers. Some customers need us to run inside their own environment. We already do this, but each deployment takes too much hands-on work. You will make it repeatable, faster, and secure, and give our engineers the tooling to support customers directly.
Own our observability. Metrics, logs, alerting, and dashboards. Decide what is worth waking someone for, and keep the cost of watching under control.
Own infrastructure security and support our compliance work. Hardening, IAM, secrets, and vulnerability management. You will help us keep our SOC 2 compliance, which customers require before they will work with us, and help answer their security reviews. We sell to security teams, so they ask hard questions.
Keep our data recoverable. Backups, restore testing, and a disaster recovery plan for RDS Postgres and ClickHouse that we have actually rehearsed.
Partner with engineers on solutions, not tickets. You are the person developers come to when they need infrastructure to do something new.

דרישות:
6+ years in DevOps, infrastructure, or platform engineering.
Real production Kubernetes experience, preferably EKS.
Deep AWS knowledge. VPC, IAM, and networking, at a level where you can explain the trade-offs behind your design.
Infrastructure as code. Terraform or Terragrunt.
Ownership of CI/CD pipelines, GitHub Actions preferred.
Hands-on work with AI coding agents such as Claude Code or Codex, as part of your daily workflow.
A security-first mindset. You think about blast radius and least privilege by default, not after review.
Clear communication. You will work with every engineer here, and sometimes with our customers. You can explain a technical trade-off to someone who does not share your background.
Accountability. You will be the only person who owns Tokens infrastructure, and that is what you want.
Nice to Have
GCP or Azure alongside AWS.
GitOps with ArgoCD, and writing Helm charts.
Python, or another language you use to build real internal tooling. Our services are Python.
ClickHouse, or another column store used for high volume log and event data.
RDS Postgres in production. Tuning, upgrades, and failover.
Experience building המשרה מיועדת לנשים ולגברים כאחד.

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8832847

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חברת השמה / כח אדם

4 ימים

DevOps Engineer- Avon

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We're looking for a DevOps / Platform Engineer to own our infrastructure end to end- both sides of it.
Side one is our multi-tenant SaaS on AWS: you build it, you run it, you keep it fast, secure, and up. Side two is the part that makes this role unusual - our enterprise customers deploy Avon AI inside their cloud (and sometimes fully air-gapped, on-prem environments). You'll own that too: packaging the platform, running the installation with the customer's infrastructure and security teams, and being the person on the call when their environment doesn't look like anyone's reference architecture.
This is a customer-facing engineering role. You'll be in rooms with enterprise IT, security, and platform teams- walking them through our architecture, answering security review questions, and unblocking deployments. If you want a pure behind-the-scenes infra job, this isn't it. If you like owning infrastructure and being the trusted technical voice in front of a customer, read on.
You'll be our first dedicated DevOps hire, which means you inherit real systems in production and a lot of room to shape how they evolve.
Key Responsibilities
EKS, networking, data stores, CI/CD, cost, and uptime. Build and evolve it with Infrastructure as Code.
Maintain and improve our Helm charts and container distribution so Avon AI installs cleanly in a customer's Kubernetes cluster.
Plan and execute installations in customers' private clouds and on-prem/air-gapped environments, working hands-on with their infrastructure teams from kickoff through go-live.
Support security reviews and architecture discussions, and translate enterprise IT constraints back into our roadmap.
IAM, network segmentation, secrets management, WAF, and the controls enterprise customers audit us on.
Metrics, logs, tracing, and alerting for our SaaS, and self-contained monitoring for customers who won't ship telemetry outside their network.
CI/CD pipelines, ephemeral PR sandboxes, release automation, and local development so engineers ship quickly and safely.
For our SaaS tenants and for deployed customer installations, including on-call ownership of what you build.

Requirements:
4+ years as a DevOps Engineer, Platform Engineer.
Strong hands-on AWS- EKS, EC2, VPC, IAM, S3, Lambda, CloudFormation/CDK, WAF.
Deep Kubernetes knowledge- cluster architecture, networking, and real production debugging. Helm authoring is a must, not a nice-to-have: our charts are the product our customers install.
Infrastructure as Code- Terraform, CloudFormation, or equivalent, with a real automation mindset.
CI/CD ownership- GitHub Actions (preferred), Jenkins, or similar, including release and artifact pipelines.
Docker and container packaging- multi-service images, registries, and distribution to environments you don't control.
Strong scripting and automation- Python and Bash.
Monitoring and observability- Prometheus, Grafana, OpenTelemetry, DataDog, Coralogix, CloudWatch, or similar.
Excellent English, written and spoken, and genuine customer-facing skills - you can lead a technical call with an enterprise customer's infra and security team, explain an architecture clearly, and stay calm when a deployment is blocked.
Proven track record running highly available, production-grade, service-oriented systems.

This position is open to all candidates.

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8853233

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30/09/2026

Senior AI Systems Engineer, Agents

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

our company's product is built around an AI agent that security analysts and detection engineers work with directly. It investigates coverage questions against live enterprise security data, authors and tests detection logic, and tunes noisy alerting.
That agent is already in production with enterprise design partners. Now we need to make it dependable and scalable enough for GA.
You will own that evolution: the agent architecture, its evaluation and quality system, and the production engineering around it. This is a hands-on senior IC role with real architectural authority - you set the technical direction and you write the code.
The agent operates inside customer security environments, where a wrong action can become a customer incident. Correctness, isolation, observability, and evaluation are not polish. They are the product.
What you'll be doing
Agent architecture: Design the evolution from today's production single-agent system to a multi-agent one: orchestration, task decomposition, runtime and framework choices, and a migration path that does not break what design partners already rely on.
Agent capability: Own the prompts, context, skills, and tool design that make the agent genuinely good at detection engineering across multiple security platforms, not just plausible-sounding.
Evaluation platform: Build the harnesses, judges, and golden datasets that turn "the agent feels better" into a number, plus the CI gates that keep regressions from shipping.
Reliability and safety: Keep long-running agentic sessions healthy in production, and build the isolation and guardrails required of an agent working inside enterprise security environments.
Production debugging: Work real failures from production traces, and turn each one into an eval case that can never regress silently.
Technical direction: Make the calls on architecture, sequencing, and quality bar and be accountable for the outcome, including raising how AI-natively the whole team builds.
Cross-team partnership: Partner with product and customer-facing teams on what the agent should do, and with platform teams on the data and integrations it depends on.

Requirements:
Senior engineering depth: You have 6+ years of experience building and operating production software, with strong backend and distributed-systems fundamentals and experience designing APIs and services.
Shipped agents, not demos: You have taken an LLM agent system with tool use, multi-turn interaction, and planning to real users, and you can talk concretely about how it failed and what you did about it.
Architectural judgment: Informed opinions on single-agent vs. multi-agent design, orchestration patterns, and the current framework and SDK landscape, with the pragmatism to pick the boring option when boring wins.
Eval discipline: You have built or owned evaluation for an LLM system, including golden datasets, LLM-as-judge with calibration, and regression gates in CI, and you can quote the metrics you moved.
Tool design instincts: You know when a deterministic tool beats a model call, how to design tool contracts an LLM will not misuse, and how to keep cost and latency under control.
Distributed systems fluency: Streaming, stateful services, and the operational instincts to keep long-running agent sessions alive in production.
Ownership in ambiguity: You can lead an area as a hands-on IC in an early-stage environment with little existing structure. Security domain experience such as SIEM platforms, SOC workflows, detection engineering, or security query languages, and experience with modern agent SDKs and protocols such as MCP, are strong advantages.

This position is open to all candidates.

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8837820

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30/09/2026

Senior DevOps Engineer, AIOps

חברה חסויה

Location: Tel Aviv-Yafo and Ra'anana

Job Type: Full Time

As a Senior DevOps Engineer, youll help turn agentic AI capabilities for diagnosing and troubleshooting network and GPU infrastructure into secure, scalable, production-ready services. This role stands out through its end-to-end ownership across cloud and customer-managed environments, close partnership with software and AI engineers, and direct influence on the reliability of NVIDIAs AI infrastructure.

What You'll Be Doing:
Own the DevOps, infrastructure, security, release, and reliability lifecycle - from development environments and CI/CD through deployment, production readiness, and sustained operations.
Build and operate Kubernetes environments and Helm-based deployments for a Python, FastAPI, Node.js, and React microservices platform across SaaS and on-premises footprints.
Engineer GitLab CI/CD pipelines with automated testing, container builds, vulnerability scanning, and versioned image and Helm chart publication through JFrog Artifactory.
Automate infrastructure provisioning, configuration, upgrades, and routine operational workflows to accelerate delivery and improve engineering productivity.
Operate PostgreSQL, Temporal workflow services, and S3-compatible object storage with disciplined capacity planning, backups, recovery testing, and safe migrations.
Strengthen release reliability through deployment validation, reduced-downtime strategies, persistent-state protection, and recovery plans for active workflows.
Deliver actionable observability and security using OpenTelemetry, Datadog/Grafana, Langfuse, secrets management, identity integration, TLS, Kubernetes RBAC, network policies, and container hardening.
Partner with software and AI engineers to troubleshoot distributed systems, investigate incidents, define reliability targets, and improve platform performance, resource efficiency, and customer outcomes.

Requirements:
What We Need to See:
Bachelors degree in Computer Science, Software Engineering, or a related field, or equivalent experience.
5+ years of experience in DevOps, site reliability engineering, or platform engineering supporting distributed applications and microservices.
Strong hands-on experience with Kubernetes, Docker, and Helm, including networking, storage, workload scheduling, scaling, and troubleshooting.
Strong Linux administration skills and proficiency in Python and Bash for automation, plus experience with infrastructure as code and configuration tooling such as Terraform and Ansible.
Experience building and maintaining CI/CD pipelines, including runners, container registries, artifact management, automated quality gates, and secure release practices.
Practical experience operating PostgreSQL or comparable relational databases, including SQL, migrations, backup and restore, and performance troubleshooting.
Strong networking and observability fundamentals across TCP/IP, DNS, HTTP, TLS, load balancing, ingress, metrics, logs, traces, dashboards, and actionable alerting.
Sound understanding of secure infrastructure operations and incident response, with demonstrated ownership, cross-functional collaboration, and prioritization in an evolving environment.

Ways To Stand Out From the Crowd:
Experience operating AI applications, agent platforms, or LLM services, including monitoring latency, failures, token usage, and cost.
Familiarity with Temporal, LangGraph, Model Context Protocol (MCP), Langfuse, ClickHouse, Redis/Valkey, or S3-compatible storage.
Deep experience with OpenTelemetry instrumentation and collectors, Datadog APM, or Prometheus/Grafana.
Experience with self-hosted Kubernetes, OpenShift, Kubernetes operators, CloudNativePG, or GPU clusters and AI data centers.
Experience building reproducible AMD64 and ARM64 container images, optimizing BuildKit pipelines, and securing the software supply chain.

This position is open to all candidates.

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28/09/2026

Senior Software Engineer, BlueField platform

חברה חסויה

Location: Tel Aviv-Yafo and Yokne`am

Job Type: Full Time

We are looking for a Senior Software Engineer to provide broad technical leadership for BlueField ARM processor platform boot, from early firmware through Linux login. Do you enjoy looking beyond the problem in front of you and asking how technology, tools, and engineering methods should evolve for the next generation of products? This is an opportunity to have an impact well beyond individual features! We value technical depth, curiosity, and practical innovation, and we want this role to help raise the technical capabilities of the entire organization. This senior individual-contributor position spans firmware, kernel, architecture, and product teams. You will help drive current product development while also shaping future technical direction, introducing new tools and methods, and improving how our teams develop, debug, validate, and understand complex systems.

What you'll be doing:

Own the technical strategy and roadmap for BlueField platform boot integration, from early firmware through Linux login.

Set the technical direction for platform boot integration in partnership with the architecture team, experienced domain experts, product teams, and firmware partners.

Lead the most complex cross-layer technical issues and drive technical decisions with architecture and domain experts on reliability, security, performance, recovery, and platform readiness.

Define the operating model for boot integration: interface contracts, qualification criteria, release decisions, technical risk management, and escalation paths across organizations.

Identify and assess emerging technologies, development methods, and tools. Drive adoption where they improve product capability, quality, engineering efficiency, or time to debug.

Requirements:
What we need to see:

Bachelor's degree or equivalent experience in Computer Science, Computer Engineering, Electrical Engineering, or a related field, with 12+ years in embedded, firmware, or Linux system software.

Deep knowledge of ARM platform boot, including firmware, ATF, UEFI, bootloaders, Linux kernel bring-up, device tree, platform initialization, and userspace handoff.

A record of leading difficult cross-organizational projects from definition through delivery, including decisions with material product or schedule impact.

Experience influencing architecture and product direction through technical judgment, without relying on direct management authority.

Strong C skills and practical experience with Linux development, debugging, and hardware/software integration.

Ways to stand out from the crowd:

Hands-on experience with ATF, UEFI/EDK II, Linux kernel, or complex ARM SoC/server boot flows.

Experience with secure boot, measured boot, provisioning, firmware update, or recovery flows.

Experience building automated test, simulation/emulation, observability, or failure-triage infrastructure.

Experience introducing tools or engineering practices that significantly improved team efficiency or technical capability.

Knowledge of PCIe, I2C/I3C, SPI, SMBus, BMC interactions, reset and power sequencing, and server-platform interfaces.

This position is open to all candidates.

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8835684

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30/09/2026

Senior AI Engineer and Agentic Platforms - Network Architecture

חברה חסויה

Location: Tel Aviv-Yafo and Yokne`am

Job Type: Full Time

We are at the forefront of the AI revolution, delivering brand new accelerated compute platforms for global impact. Our Network Architecture group is seeking a talented and motivated Sr. Software Engineer to build the agentic workflows that our architects use in their daily work. The software at the center of this role is our hardware network simulation environment - you will design multi-step agent workflows over it, engineer the context that grounds them in our own specifications and source code, and optimize their runtime performance. If you are passionate about building the practical infrastructure that brings intelligent agents to life, we want to hear from you.

What you'll be doing:
Build agentic workflows - loops, graphs, and multi-step pipelines - that carry real hardware network simulation and analysis work end to end.
Engineer the context these workflows run on, turning our simulation models, specifications, design documents, and source code into context that makes agents accurate in our domain.
Work closely with network architects to understand their workflows and translate them into agent workflows they use daily.
Optimize the runtime performance of our simulation tooling on these platforms, including execution time, compute cost, and end-to-end latency.
Define evaluation and regression testing for agent workflows, so that changes to a prompt, a graph, or a context source are measurable.
Build observability across agent runs: what the agent did, where it failed, and why.
Champion guidelines for secure and reliable agent workflows, including data handling, access control, and interaction boundaries.
Serve as a key technical resource for solving sophisticated integration issues between agents and internal tooling.

Requirements:
What we need to see:
B.Sc. or above in Computer Science, Computer Engineering, or a related field, or equivalent experience.
5+ years of hands-on experience in software engineering, with demonstrated ownership of production systems from design through deployment.
Expert-level programming skills in C++, with strong Python skills alongside it.
Strong understanding of the full stack, including hardware: memory, I/O, networking, accelerators, and where real performance bottlenecks occur.
Current, practical knowledge of how to build systems around AI models: agent loops, tool interfaces, context retrieval and management, and common failure modes.
Understanding of inference serving, including request lifecycle, batching, caching, and the tradeoffs between throughput, latency, and cost.

Ways to stand out from the crowd:
Experience writing hardware simulation software - network, system, or architectural simulators, models, or testbenches.
Networking experience - protocols, fabrics, switching, or RDMA - and experience working alongside silicon, systems, or architecture teams.
Hands-on experience with inference serving engines such as vLLM, TensorRT-LLM, or Triton Inference Server, including low-level internals such as KV cache, batching and scheduling, and quantization, and related performance work such as profiling and GPU programming.
Hands-on experience building or fine-tuning LLMs or other generative models.
Agent workflows, tooling, or context pipelines adopted by other engineering teams.

This position is open to all candidates.

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8837912

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08/09/2026

Senior DevOps Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Platform and infrastructure (K8s + IaC)
Architect and operate our Kubernetes platform on AWS - scaling, networking, cost, and reliability
Own infrastructure as code (Terraform) so environments are reproducible, auditable, and fast to evolve
Build the foundations that let the team provision and scale services without friction

AI agent platform - managing and scaling agents at volume
Operate and scale the orchestration layer (Temporal) that runs dozens of agents in parallel
Tune the platform for the unusual load profile of agent workloads - bursty, long-running, data-heavy, latency-sensitive
Give engineers the primitives to deploy, version, observe, and roll back agents safely under enterprise SLAs

CI/CD and developer experience
Own build and deploy pipelines end-to-end - fast, safe, boring releases
Invest in DX as a first-class product: the team treats developer experience as leverage, and you set the bar
Reduce the time from merged to in production and from idea to running experiment

Observability and reliability
Build monitoring, alerting, and tracing that make production legible - for services and for agents
Own incident response and the reliability practices that keep enterprise customers SLAs intact
Turn incidents into systemic fixes, not repeated firefighting

Security and compliance
Own secrets management, hardening, and the day-to-day security posture of the platform
Support our compliance commitments (we are Mastercard-certified, operating in fintech - the bar is high)
Build security into the pipeline so it is the default, not a gate

Requirements:
Strong DevOps/platform/SRE experience at a company with a real engineering culture (FAANG, unicorn, or a well-established startup with high standards)
Deep Kubernetes and AWS - you have architected, scaled, and debugged production clusters, not just deployed to them
Infrastructure as code in your bones - Terraform or equivalent, with strong opinions on reproducibility and auditability
CI/CD ownership - you have built pipelines that engineers trust and rarely think about
Production observability and incident response at meaningful scale
Comfort with and curiosity about AI/LLM workloads. We are an AI-native company; you should be using AI in how you work, and excited to operate the infrastructure agents run on

This position is open to all candidates.

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8814945

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חברת השמה / כח אדם

27/09/2026

Senior/Principal SRE Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We're hiring a Senior/Principal Site Reliability Engineer to own production reliability for Cortex Agentix Endpoint Security (following an acquisition of KOI Start Up) as it scales. You'll define and operate our SLOs and error budgets, lead high-severity incident response, and ensure our Kubernetes and AWS infrastructure stays stable under growth. You'll also build and supervise the AI agents that handle routine alert triage and monitor tuning, focusing your own time on the reliability engineering that requires human judgment. This role is a strong fit for someone who treats reliability as an engineering discipline and enjoys ownership, incident command, and applying AI to operational work.
Your Impact:
Own reliability as an engineering discipline - define SLIs, set SLOs, and run error-budget-based decision-making so "how reliable are we" becomes a number that governs how fast we ship.
Own production incidents end-to-end - lead response, mitigation, and resolution for high-severity incidents, and drive blameless postmortems that feed real fixes back into the system.
Own the reliability and capacity of production infrastructure as we scale - forecasting headroom, validating scaling behavior under load, and keeping latency and error rates within SLO.
Run and evolve Kubernetes environments so releases and infra changes are safe by default across hundreds of tenant apps.
Own, build, and supervise our SRE AI agents that triage alerts, review monitors, resolves and summarize incidents. Set and expand the trust ladder that governs what the agents do autonomously, what needs approval, and what stays human. This is a core part of the role.

Requirements:
Your Experience:
5+ years operating production cloud infrastructure, with a strong reliability focus (SRE, or DevOps/platform engineering with reliability ownership).
Deep hands-on experience with Kubernetes, Helm, ArgoCD, Terraform, and CI/CD.
Experience defining and operating SLIs, SLOs, and error budgets - or a clear grasp of the discipline and the drive to establish it from scratch.
Strong observability and alerting experience in Datadog or comparable platforms, including raising signal-to-noise in production.
Proven incident-response instincts - comfortable owning high-severity incidents and a genuine believer in blameless postmortems.
Proven ability to own platform and reliability projects end-to-end, from design through production operation and ongoing improvement.
Strong troubleshooting across distributed systems, Kubernetes, CI/CD, and live incidents.
Collaborative mindset - comfortable working across engineering, security, product, and leadership.
Comfort in a fast-paced, high-ownership environment where priorities shift but production quality doesn't.
Genuine interest in applying AI, automation, and intelligent workflows to operational work - and in building and supervising agents, not just using them.
Ownership-driven - You take responsibility for the reliability of the systems you build and operate, from SLO definition through incident command and continuous improvement.
Reliability as engineering - You treat reliability as a software problem to be solved with code, measurement, and automation - not an ops queue to be worked by hand.
Collaboration - You work effectively across engineering, security, product, and leadership to align on reliability priorities and drive shared outcomes.
Innovation balanced with pragmatism - You actively explore new approaches, particularly AI-assisted operations and agent supervision, while weighing them against reliability, maintainability, and operational simplicity.
Security mindset - You design and build with least privilege, auditability, and production safety as foundational principles rather than afterthoughts.
Clear communication - You articulate reliability, risk, cost, and security tradeoffs precisely to both technical and non-technical stakeholders.

This position is open to all candidates.

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8834235

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08/09/2026

Senior Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are looking for a Senior Data Engineer to build and scale the data foundation behind platform and products. You will own complex data end-to-end - from ingestion and transformation through modeling, quality, observability, and production delivery.
This is a hands-on senior IC role for a strong builder who can solve difficult data problems independently, set a high technical bar, and collaborate closely with engineering, DS, and product. You will turn large, fragmented datasets into reliable, reusable capabilities that power every product.
Responsibilities
Build and own scalable data pipelines- Design, implement, and operate robust pipelines for high-volume structured and unstructured data, with validation, monitoring, lineage, and recovery built in.
Scale the platform for growth- A key near-term initiative is re-architecting the system to support a significantly larger customer base. You will own performance and cost-efficiency across pipelines and services, keeping reliability and operating costs under control as the platform scales.
Build across the stack- This is not a pipelines-only role. You will also write backend services and some frontend, including the internal backoffice the team runs on. We hire builders, not narrow specialists.
Own the core data tables- Own schema design and evolution, data contracts, and the modeling standards the team follows - naming, shared dimensions, normalization, documentation. Be accountable when a table is wrong, late, or drifting.
Level up the teams data work- Pair with and advise software engineers and data scientists on Spark, SQL, and modeling, and help turn notebook-grade code into production-grade pipelines.
Partner cross-functionally- Translate product, client, compliance, and business requirements into clear technical designs and dependable production systems.

Requirements:
Spark at scale- You have tuned real Spark jobs for performance and cost - skew, shuffle, partitioning, memory, spill - run pipelines over TB-scale or billions of rows in production, and can reason about the physical execution plan, not just write DataFrame code.
5+ years of professional experience building and owning production systems.
Strong Python and SQL, with maintainable, tested production code.
Strong software engineering fundamentals across the stack. You can own backend services and pick up frontend when the work needs it - not a pipelines-only specialist.
AI-first way of working- You build with AI in your day-to-day development, using it to move faster and raise the quality of what you ship.
Deep experience designing and operating ETL/ELT pipelines, data models, and distributed data-processing systems.
Comfortable advising and pairing with other engineers and data scientists on data work.
Strong AWS experience: S3, Glue, EMR, Athena, and related compute and orchestration services.
Experience with modern data lakehouse or warehouse architectures. Apache Iceberg is a strong advantage.
Experience with workflow orchestration (Airflow or similar), CI/CD, Docker, Git, and infrastructure as code such as AWS CDK and CloudFormation.
Strong understanding of data quality, schema evolution, lineage, observability, privacy, security, and access controls. Experience with regulated or sensitive data, such as healthcare / PHI, is an advantage.
High comfort in a fast-moving environment with incomplete requirements, high ownership, and a strong sense of urgency.

This position is open to all candidates.

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8814966

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