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לפני 2 שעות
Location: Tel Aviv-Yafo
Job Type: Full Time
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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30/07/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior AI Software Engineer to build the agents that sit on top of our search platform: systems that take a user's intent, break it into steps, gather and verify information from the web, and return answers an agent can act on. You will work across applied research and engineering, designing how agents plan, call tools, retrieve, and reason so they accomplish open-ended tasks reliably and at scale.

This is a high-ownership role at the intersection of agent systems, retrieval, and product. You will turn frontier-model capabilities into dependable, production-grade agent behavior, and you will own that behavior end to end, from the prompts and tools to the evaluation that proves it works.

In this position, your responsibility will be to

Design and build AI agents that plan, retrieve, and reason over real-world information to complete open-ended tasks

Build the tool interfaces and context engineering that let frontier models use our search and other tools effectively

Mine and analyze usage data to build agents that learn and improve continually from how they are used

Turn new model capabilities into reliable product features, and own them from prototype to production

Define the evaluations, metrics, and guardrails that prove an agent is accurate, grounded, and safe

Improve agent quality across reasoning, planning, tool use, and grounding against real user tasks

Build the backend and infrastructure that run agents reliably under high volume

Collaborate with the search, ML, and product teams to make agent and platform capabilities reinforce each other
Requirements:
You may be a good fit if you:

6+ years of software engineering experience, with a track record of shipping complex systems to production

Strong understanding of LLMs and transformer architecture, and how model behavior shapes what agents can do

Able to mine and analyze data to build agents that learn and improve continually

Hands-on experience building agentic systems: tool calling, planning, multi-step or long-running task execution

Experience with agentic frameworks (e.g. LangChain, DeepAgents) and tracing tools (e.g. LangSmith)

Strong grasp of context engineering and tool interfaces for frontier LLMs

Comfortable defining the metrics and evaluations that prove a system works, and iterating on them

Strong product judgment; you turn vague needs into reliable systems and ship without waiting for perfect specs

Thrive in a small, fast-moving team and take ownership end to end
This position is open to all candidates.
 
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7 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across the platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how evolves from AI-enhanced internal tools to customer-facing AI products.
Requirements:
Core Engineering: Significant software engineering experience (typically 4+ years) with strong Python skills and solid backend engineering fundamentals.
Production Experience: Experience building and operating production systems in cloud environments.
Real-World GenAI Experience: Practical experience bringing LLM-based systems into production, including handling latency, cost control, and failure modes. Familiarity with additional agentic frameworks (e.g., LangChain, MetaGPT) and evaluation frameworks.
Builder Mentality: Strong ownership and the ability to operate independently while collaborating closely across teams, with the motivation to grow into technical leadership as the group expands.
(Advantage) Data & RAG: Experience enabling LLMs to consume structured or operational data (configurations, logs, metrics) and experience with retrieval systems (RAG) or vector databases.
This position is open to all candidates.
 
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02/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
we are looking for a Senior Software Engineer to help build the core of our AI security platform and AI Control Plane.
You will build systems that help enterprises understand, monitor, and control how AI agents and LLM-based applications operate across their organization. We expect engineers to work in an AI-native way: leveraging and orchestrating AI agents to accelerate design, implementation, testing, debugging, and iteration, while owning the quality of the final result.
This role requires strong ownership, system design judgment, and the ability to turn complex AI-security problems into reliable production systems.
What you will do
Leverage and orchestrate AI agents and LLMs to design, build, test, debug, and ship core platform capabilities.
Build systems for monitoring, governing, and controlling AI agents, LLM applications, tool usage, prompts, context, policies, and runtime behavior.
Turn ambiguous AI-security problems into simple, scalable, production-grade systems.
Own technical decisions from design through production, working closely with Product, Security, and Engineering.
Requirements:
5+ years of backend software engineering experience in production environments.
Strong system design skills and backend fundamentals: APIs, data modeling, scalability, performance, and reliability.
Proven ability to own complex systems end to end, operate independently, and create clarity in ambiguous situations.
Strong interest in AI, LLMs, agents, and the security challenges around their adoption.
Clear communication and strong cross-functional collaboration skills.
Nice to Have
Experience building production systems with LLMs, AI agents, or agent orchestration.
Experience in cybersecurity, cloud security, or enterprise security products.
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
We are hiring an AI Researcher to join the research team building the next generation of AI-native security systems. You will work alongside security and threat researchers to build large-scale AI agents that reason over software, code, endpoint activity, and security signals to detect malicious behavior, uncover vulnerabilities, assess risk, and make autonomous security decisions in real-world production environments. We are entering the Mythos era - where attackers operate at machine speed using autonomous systems and AI-generated software, and defenders must evolve the same way. We use state-of-the-art frontier models, including access to Mythos, to build reliable AI-native security systems at global scale. You will help design the evaluations, harnesses, and reliability infrastructure that make autonomous agents dependable under real customer load, while collaborating with leading AI organizations including Anthropic on initiatives such as Glasswing. This is an opportunity to work at the frontier of AI, autonomous systems, and cybersecurity while helping define how the next generation of security systems will operate.
Key Responsibilities
Build AI agents and autonomous security systems that reason over software, code, endpoint activity, MCPs, and security signals to detect malicious behavior, uncover vulnerabilities, and assess risk at production scale.
Develop systems, tooling, and infrastructure that enable agents to autonomously investigate threats, hunt for malware in massive datasets, and operate reliably in complex security environments.
Design and run experiments to evaluate frontier-model and agent capabilities in realistic adversarial scenarios, including benchmark creation, large-scale datasets, automated evaluations, and human-in-the-loop review systems.
Build the evaluation harnesses, observability systems, and reliability infrastructure required to make autonomous agents accurate, scalable, and dependable under real customer load.
Engineer for scale and performance across large distributed AI systems, including inference optimization, orchestration, batching, caching, cost controls, and graceful degradation under high demand.
Continuously evaluate emerging models, agent architectures, prompting techniques, and research directions to ensure our systems remain at the frontier of AI-native cybersecurity.
Rapidly prototype and test new approaches across reasoning, autonomy, evaluations, and security workflows as the AI landscape evolves.
Partner closely with threat and security researchers to extract domain expertise, translate analyst reasoning into AI workflows, and enable new forms of automation and autonomous investigation.
Collaborate with leading AI and security researchers to shape the future of AI-native cybersecurity as the industry transitions into the Mythos era.
Senior candidates will help define research direction, shape technical strategy, identify high-leverage problems, and influence how autonomous AI systems are deployed across the organization.
Requirements:
Strong experience building and operating AI agents or autonomous systems in production environments.
Hands-on experience with LLMs, agent frameworks, tool use, reasoning systems, retrieval, evaluations, or multi-agent orchestration.
Proven ability to rapidly design experiments, iterate on ideas, and turn research into reliable production systems.
Deep familiarity with the rapidly evolving AI ecosystem; enthusiasm for continuously experimenting with new models, techniques, architectures, and research directions.
Strong intuition for identifying which new AI capabilities are production-ready versus hype, and ability to quickly translate frontier advances into practical systems.
Strong engineering skills, especially in Python and modern AI infrastructure.
Proven ability to own problems end-to-end, from research and prototyping through deployment, scaling, and reliability.
This position is open to all candidates.
 
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02/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
As an AI Engineer at our company, you will own the intelligent decision-making pipelines that turn complex workspace telemetry into autonomous security actions. You will design, build, and deploy the autonomous reasoning workflows and advanced data classification systems that drive our company's preventive operating model. Your focus will be on creating resilient, production-grade AI systems capable of deep policy comprehension, real-time prevention at the point of adoption, and autonomous remediation of existing risks.
This is a ground-floor opportunity to shape the AI strategy of a fast-growing cybersecurity company alongside a lean, elite team of builders.
WHAT YOULL DO
End-to-End Ownership: Own our AI capabilities entirely from initial research, architectural design, and prototyping, through to production deployment, optimization, and continuous monitoring.
Design & Build Agentic Workflows: Architect multi-step AI agents capable of autonomously investigating workspace risks, interpreting complex enterprise policies, and taking precise remediation actions.
Integrate Multi-Faceted ML: Bring innovation and creative thinking to our core engine. Implement diverse ML models across our entire research and product pipeline-utilizing clustering, text extraction, document analysis, and tabular data classification.
Ship Production-Grade AI: Build high-throughput, resilient, and fault-tolerant production code. You will ensure our AI pipelines and agentic workflows are highly predictable, deeply observable, and built to scale under enterprise-grade loads.
Implement Guardrails & Evaluation: Build continuous evaluation frameworks to benchmark agent accuracy, mitigate hallucinations, and enforce strict data security/privacy guardrails.
Requirements:
Agentic Expertise: Deep experience with LLMs and the modern agentic stack (LangGraph, AutoGPT patterns, tool-calling, and orchestration). You understand how to guide an LLM through complex, multi-step tasks.
The "Full-Stack" DS Mindset: You are a coder first. You are comfortable digging into a large codebase, understanding backend services, and writing production-grade code. You don't wait for someone else to "fix the API."
Product-Driven Research: You are obsessed with impact. You choose the right tool for the job-whether its a simple heuristic or a complex fine-tuned model-based on what provides the most value to the user.
Data & System Fluency: Strong experience with Python and SQL. You understand how to interface with Postgres and ClickHouse to build the data-rich contexts our agents require.
Engineering Rigor: You care about version control, testing, and CI/CD. You treat your prompts and model configurations with the same engineering discipline as code.
The company Mindset: You take ownership, act with accountability, collaborate openly, and focus on delivering meaningful impact. You thrive in fast-moving environments, embrace ambiguity, and enjoy solving hard problems together.
Education: Bachelors or Masters degree in CS, Math, Statistics, or equivalent practical experience in a high-growth AI environment.
Communication: Full professional fluency in both Hebrew and English.
This position is open to all candidates.
 
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03/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior AI Engineer to design and build the intelligence layer .

You will own the agentic workflows, LLM integrations, and reasoning pipelines that allow our AI agents to autonomously analyze markets, make decisions, and drive eCom growth at scale.

What you'll do
Design & Build Agentic Workflows: Architect multi-agent pipelines - including planning, memory, tool use, and decision loops - that power autonomous media buying and growth operations.
Own LLM Integration: Select, prompt-engineer, fine-tune, and evaluate LLMs to produce reliable, high-quality outputs across diverse business tasks.
Build RAG Systems: Develop retrieval-augmented generation pipelines with vector search and context management to ground agent reasoning in real business data.
Drive Evaluation & Reliability: Define evals, build testing frameworks, and continuously improve agent output quality, consistency, and safety in production.
Collaborate Across the Stack: Work closely with backend engineers to integrate AI capabilities into core product APIs, ensuring low-latency, production-grade deployment.
Requirements:
Requirements
8+ years of engineering experience, with at least 2 years focused on LLM-based systems, agents, or applied ML in production.
Agentic Systems Expertise: Hands-on experience building multi-agent architectures, tool-calling workflows, and orchestration frameworks (e.g. LangGraph, CrewAI, ADK, or custom).
Prompt Engineering & Evals: You treat prompts as code - versioned, tested, and measured. You know how to systematically debug and improve LLM behavior.
AI-Native Development: You actively use agentic coding tools (Claude Code, Cursor, etc.) to accelerate your own workflow.
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes.
As a Senior Staff Software Engineer in the Detection Platform group, you will be tasked with being the technical authority responsible for defining and evolving the architecture of the cloud-native systems that power our AI SIEM detection, hunting, and response capabilities, including large-scale real-time detection engines, stateful detection engines, anomaly detections, ML pipelines, agentic SOC and threat-hunting capabilities. You will lead the design and execution of backend systems that process billions of events and several petabytes of data daily and serve tens of thousands of security specialists at enterprise and government customers worldwide. Your technical leadership will bridge long-term architectural strategy and high-velocity product delivery, and you will drive cross-team initiatives that shape how detection and response are built and operated across the group.
Requirements:
10+ years of software engineering experience with deep production-level mastery of Go and/or Java (Python a plus), and a strong track record of building and operating high-scale distributed backend services.
A track record of being a recognized subject-matter expert others seek out to review and elevate their designs, with a passion for building high-scale distributed systems.
Platform thinking: proven experience building and evolving platforms, not just features, with a focus on API design (gRPC, REST), service boundaries, multi-tenancy, and shared infrastructure in a high-scale SaaS environment.
Strong background in distributed data processing and microservices, building high-quality, scalable data products that handle millions of events per second.
Deep experience with AWS and/or GCP, Kubernetes, Docker, Postgres, Redis, Kafka, Cassandra, and ClickHouse.
Hands-on experience leveraging AI in the development process (e.g. AI coding assistants and agentic dev tools such as Claude Code, Cursor, or Copilot) and a desire to reshape how a team builds software to better utilize AI.
Experience embedding AI into production services, building agentic and LLM-powered capabilities. Familiarity with modern techniques such as agentic frameworks and orchestration, retrieval-augmented generation (RAG), the Model Context Protocol (MCP), vector databases, prompt engineering, and evaluation and guardrail frameworks for reliable AI systems is a strong advantage.
The ability to turn vaguely specified, complex requirements into efficient, future-proof end-to-end designs, and to drive multi-team initiatives and influence the engineering roadmap.
Strategic communication: able to articulate complex technical trade-offs to both technical and non-technical stakeholders, including Product Management, Directors, and VPs.
Ability to swiftly delve into new products, and to collaborate effectively with local and remote teams across time zones.
Customer focus: you care about delivering value and want to hear directly from customers on how to evolve your systems.
Previous experience developing security-related products is a strong advantage.
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
As a Senior or Principal Software Engineer in Cortex Cloud, you will contribute to the development and scaling of cloud-native security solutions for enterprise organizations. This role involves working within an established team to evolve a high-traffic product, with a focus on refining architecture, optimizing the technology stack, and maintaining engineering standards.
Your responsibilities include writing reliable code, influencing product direction, and designing distributed systems. You will be expected to make technical decisions that impact the long-term stability and performance of cloud workload protection services.
AI Integration & Engineering Workflow
A core component of our development process is the use of AI. Rather than basic code completion, we integrate AI assistants as functional components of our workflow. Our team utilizes a multi-agent AI system (IDEX/ProDex) that assists across the development lifecycle: from planning and architecture to code analysis and security reviews.
In this role, you will:
Work with AI Tools:Utilize platforms such asGemini, Claude, and Cursorfor tasks beyond code generation, including root-cause analysis, system design reviews, and architectural assessment.
Develop AI-Augmented Workflows:Help refine how AI is integrated into the SDLC, including the orchestration of agents and the development of internal tools that extend AI capabilities across our codebase.
Maintain Quality Standards:While AI assists in increasing velocity, you are responsible for the technical output. This includes critical review of all generated code and ensuring that AI-assisted work aligns with our architectural requirements and security benchmarks.
Interact with Specialized Agents:Coordinate with AI agents (Product, Architecture, Security) that operate on shared context to assist in managing complex engineering tasks.
We are looking for engineers who are interested in leveraging AI as a technical tool to manage complexity and who want to contribute to the practical application of human-AI collaboration in a cloud environment.
Requirements:
Your Experience
Backend Engineering: 5+ years of experience building and maintaining production-grade distributed systems.
Languages: Proficiency in Go (Golang) is a strong advantage. We are open to engineers with deep expertise in other backend languages (Java, Python, Rust, C#, or Node.js) who are willing to transition to a Go-primary stack and have a focus on clean, well-tested code.
Fundamentals: Strong grasp of system design, data structures, and algorithms in high-scale cloud environments.
Standards: Experience with CI/CD, comprehensive testing (unit, integration, E2E), and rigorous code reviews.
Cloud: Proficiency in AWS, GCP, or Azure, including cloud-native services.
Reliability: Experience with observability (monitoring, logging, tracing) and system profiling.
Education: B.Sc. or M.Sc. in Computer Science, Software Engineering, or equivalent technical/military experience.
Advantages
Advanced Go: Deep experience with concurrency and memory management patterns.
Distributed SaaS: Background in managing multi-tenant, cloud-based SaaS at scale.
Cybersecurity: Familiarity with threat detection or cloud security infrastructure.
AI Systems: Interest in agentic workflows or prompt engineering in production.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
As a Senior or Principal Software Engineer in Cortex Cloud, you will contribute to the development and scaling of cloud-native security solutions for enterprise organizations. This role involves working within an established team to evolve a high-traffic product, with a focus on refining architecture, optimizing the technology stack, and maintaining engineering standards.
Your responsibilities include writing reliable code, influencing product direction, and designing distributed systems. You will be expected to make technical decisions that impact the long-term stability and performance of cloud workload protection services.
AI Integration & Engineering Workflow
A core component of our development process is the use of AI. Rather than basic code completion, we integrate AI assistants as functional components of our workflow. Our team utilizes a multi-agent AI system (IDEX/ProDex) that assists across the development lifecycle: from planning and architecture to code analysis and security reviews.
In this role, you will:
Work with AI Tools:Utilize platforms such asGemini, Claude, and Cursorfor tasks beyond code generation, including root-cause analysis, system design reviews, and architectural assessment.
Develop AI-Augmented Workflows:Help refine how AI is integrated into the SDLC, including the orchestration of agents and the development of internal tools that extend AI capabilities across our codebase.
Maintain Quality Standards:While AI assists in increasing velocity, you are responsible for the technical output. This includes critical review of all generated code and ensuring that AI-assisted work aligns with our architectural requirements and security benchmarks.
Interact with Specialized Agents:Coordinate with AI agents (Product, Architecture, Security) that operate on shared context to assist in managing complex engineering tasks.
We are looking for engineers who are interested in leveraging AI as a technical tool to manage complexity and who want to contribute to the practical application of human-AI collaboration in a cloud environment.
Requirements:
Your Experience
Backend Engineering: 5+ years of experience building and maintaining production-grade distributed systems.
Languages: Proficiency in Go (Golang) is a strong advantage. We are open to engineers with deep expertise in other backend languages (Java, Python, Rust, C#, or Node.js) who are willing to transition to a Go-primary stack and have a focus on clean, well-tested code.
Fundamentals: Strong grasp of system design, data structures, and algorithms in high-scale cloud environments.
Standards: Experience with CI/CD, comprehensive testing (unit, integration, E2E), and rigorous code reviews.
Cloud: Proficiency in AWS, GCP, or Azure, including cloud-native services.
Reliability: Experience with observability (monitoring, logging, tracing) and system profiling.
Education: B.Sc. or M.Sc. in Computer Science, Software Engineering, or equivalent technical/military experience.
Advantages
Advanced Go: Deep experience with concurrency and memory management patterns.
Distributed SaaS: Background in managing multi-tenant, cloud-based SaaS at scale.
Cybersecurity: Familiarity with threat detection or cloud security infrastructure.
AI Systems: Interest in agentic workflows or prompt engineering in production.
This position is open to all candidates.
 
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8779570
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תודה על שיתוף הפעולה
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03/08/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
We're looking for a Senior Data Engineer to help build next-generation data platform - the lakehouse foundation that will power data processing across the entire product. This is not a "write pipelines on top of someone else's platform" role, and it's not a pure infrastructure role either. It's both, deliberately.

You'll own the platform end to end: the infrastructure it runs on (Spark on Kubernetes, Apache Iceberg, AWS Glue, Airflow), the frameworks and tooling that let dozens of other engineers build on it without reinventing the wheel, and the design of the data pipelines themselves. Everything you build becomes leverage for the teams around you - your abstractions, base images, CI/CD flows, and operational patterns are what make the platform usable at scale.

You'll also own one of the hardest ongoing trade-offs in a high-scale data platform: balancing cost and performance. Compute sizing, storage layout, partitioning and compaction strategy, job scheduling - every decision has a price tag and a latency profile, and you'll be the one making those calls with data.

This role is ideal for an engineer who is equally comfortable debugging a Spark executor OOM on Kubernetes at 10am, designing a clean Python framework API at noon, and modeling the cost impact of a table layout change in the afternoon.



What You'll Do

Platform & Infrastructure

- Design, deploy, and operate our Spark-on-Kubernetes compute platform, including autoscaling, resource tuning, and multi-tenancy considerations.

- Own the lakehouse storage layer built on Apache Iceberg and AWS Glue catalog - table design, partitioning, compaction, schema evolution, and retention.

- Build and operate orchestration on Airflow: DAG standards, deployment flows, environment promotion, and reliability.

- Own production operations of the platform: monitoring, alerting, incident response, and continuous hardening.

Frameworks & Developer Enablement

- Build the code frameworks, libraries, and templates that other engineers use to write pipelines - so that spinning up a new production-grade Spark job is measured in hours, not weeks.

- Define and enforce standards for pipeline structure, testing, observability, and deployment across teams.

- Own CI/CD for data workloads: image builds, artifact promotion, and GitOps-based delivery.

- Act as a technical partner to product and research teams building on the platform - your customers are other engineers.

Data Pipelines & Architecture

- Design and build scalable batch and streaming pipelines processing complex, high-volume datasets from diverse sources.

- Lead large-scale backfills and migration initiatives, ensuring data consistency and integrity across evolving storage and compute platforms.

- Design event-driven data flows over large-scale queue systems (Kafka) for reliable, efficient data movement.

Cost & Performance

- Continuously balance cost against performance: right-size compute, tune queries and jobs, optimize storage layout and file sizes, and choose the correct engine for each workload.

- Build cost visibility and attribution into the platform so trade-offs are made with data, not guesswork.
דרישות:
- 5+ years of experience in software engineering, with meaningful time spent building and operating large-scale data platforms.

- Strong hands-on experience with distributed processing engines (Spark strongly preferred), including performance tuning and debugging in production.

- Practical experience deploying and operating workloads in Kubernetes-based environments - you're not afraid of infra work; you enjoy it.

- Experience building shared frameworks, libraries, or internal tooling used by other engineers, with the product mindset that comes with it (clean APIs, docs, versioning, backward compatibility).

- Strong proficiency in SQL and data modeling: complex analytical queries, query tuning, partitioning strategies.

- Solid software engineerin המשרה מיועדת לנשים ולגברים כאחד.
 
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עדכון קורות החיים לפני שליחה
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8766023
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