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30/08/2026
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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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior AI Engineer to design and build production-grade, LLM-powered systems. You'll work at the intersection of software engineering and applied AI - shipping agents, RAG pipelines, and tool-using systems that solve real problems at scale. This is a hands-on, high-ownership role for someone who thrives at the frontier of what's possible with modern LLMs and isn't afraid to write the glue, the infrastructure, and the prompts that make it all work.
This is a **cross-functional, company-wide role**. You won't be embedded in a single product team - instead, you'll partner with every department to identify high-leverage opportunities and build AI-powered tools and workflows that boost productivity and efficiency across the entire organization.
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
What You'll Do:
- Design, build, and operate LLM-powered applications, agents, and workflows end-to-end - from prototype to production.
- Architect retrieval, context engineering, and tool-use strategies that make models reliable, accurate, and cost-efficient.
- Integrate LLMs with internal services, third-party APIs, and data stores to automate complex business and engineering workflows.
- Build, evaluate, and continuously improve evaluation harnesses for non-deterministic systems.
- Collaborate closely with product, research, and platform teams to translate ambiguous problems into shipped capabilities.
- Stay ahead of the rapidly evolving LLM ecosystem (models, frameworks, agentic patterns) and bring the best ideas into our stack.
Requirements:
Engineering Foundations:
- Strong Python skills- you write clean, idiomatic, well-tested code and understand the language deeply.
- Hands-on experience using coding agents(Cursor, Claude Code, GitHub Copilot, or similar) to build complex software systems. You know how to delegate effectively to AI assistants and review their output critically.
- Experience with multiple database paradigms- both SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis, DynamoDB, or similar). You can choose the right tool for the job.
- Experience designing and integrating with third-party APIs- REST and gRPC. Comfortable building robust clients, handling auth, retries, rate limits, and schema evolution.
- Production experience with Docker and Kubernetes- containerizing services, writing manifests, and debugging deployments.
- Strong Linux fundamentals- confident in bash and the terminal; you can navigate, script, and troubleshoot a server without reaching for a GUI.
- Experience building cloud-native tools on AWS, GCP, or Azure (compute, storage, queues, serverless, IAM).
AI / LLM Expertise:
- Solid understanding of what an LLM is and how it works- tokenization, attention, context windows, sampling, and the practical implications of each for system design.
Strong grasp of modern patterns for integrating LLMs into real workflows, including RAG, MCP (Model Context Protocol), vector databases, agents, tool use, and context engineering- with hands-on experience building with several of them.
- Production experience implementing LLM-powered systems end-to-end, using relevant tools and frameworks (e.g. LangChain, LlamaIndex, LangGraph, Haystack, Pydantic AI, vector stores like Pinecone/Weaviate/pgvector, observability tools like LangSmith or Langfuse).
- Solid foundation in core ML concepts; embeddings, evaluation, overfitting, generalization, and how classical ML relates to and differs from modern LLM-based approaches.
Nice to Have:
- Experience fine-tuning or distilling open-source models.
- Contributions to open-source AI/ML projects.
- Experience with streaming, real-time systems, or low-latency inference.
- Familiarity with prompt evaluation frameworks and LLM-as-judge methodologies.
This position is open to all candidates.
 
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08/09/2026
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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23/08/2026
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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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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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Required Senior Platform Engineer
About The Role:
As a Senior Platform Engineer, you will build the shared backend platform and AI enablement layer that every product team builds on top of, and you will be a key design partner across R&D - helping teams shape architectures for new AI-powered features, backend services, and agentic systems.
This is a force-multiplier role: instead of shipping one product feature, you raise the velocity and quality of every team. You will make key architectural decisions about how AI is integrated, how services communicate, and how engineers measure and improve what they ship - and you will coach and review designs across the org so we move fast without compromising on quality.
What You'll Do:
Lead and partner on architecture and design across R&D - running design reviews, shaping technical proposals, and helping teams choose the right patterns for AI, backend, and data-driven systems
Design and build core backend platform services and SDKs (auth, eventing, feature flags, configuration, data access) that product teams compose into AI-powered features
Build the AI enablement layer: shared LLM gateways, prompt and agent frameworks, evaluation and tracing tooling, model routing, guardrails, and cost/latency controls - so every team can adopt LLMs and agents safely and consistently
Define and own platform processes that improve engineering velocity and quality: service templates, paved-road patterns, code review standards, release workflows, and golden-path documentation
Build the observability and quality story for AI features end-to-end: structured logging, metrics, distributed tracing, LLM-call instrumentation, prompt/response evaluations, and regression detection
Research, prototype, and lead the selective adoption of new AI tooling, agent frameworks, and backend technologies into the platform.
Requirements:
4+ years of experience in backend / software engineering, with proven experience designing and developing high-performance, distributed systems
Strong proficiency in Python and Node.js
Proven experience working in cloud environments (AWS preferred; GCP/Azure acceptable)
Hands-on experience with microservices, containerized environments (Kubernetes), and CI/CD pipelines (GitHub Actions)
Experience with message queuing and streaming systems such as Kafka and/or SQS
Strong understanding of SQL and NoSQL databases, large-scale data flows, and data-driven systems
Experience in developing and deploying LLM agents to production (via Langgraph, Langchain, etc.)
Strong collaboration and communication skills, both Hebrew & English.
This position is open to all candidates.
 
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07/09/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior II Software Engineer to join the CX Platform team, the foundational engineering team powering our entire Customer Experience group. This is a high-impact, hands-on role at the intersection of backend engineering, AI infrastructure, and customer-facing product.

You'll work across the full platform stack (backend services, data pipelines, security, cost, and scale) with a meaningful and growing focus on AI infrastructure. We own the agentic platform for the entire Product Offering group: from building the LLM infrastructure and agentic workflows to ensuring they're reliable, observable, and safe in production.

What you'll be doing:
Own AI infrastructure for the Product Offering group. Design, build, and evolve the shared AI platform (agentic workflows, LLM integrations, observability, and guardrails) that CX product teams build on.
Ship agentic features end to end. Lead development of AI-driven capabilities using LangChain, LangFuse, and AWS Bedrock, from architecture through production deployment and monitoring.
Drive platform architecture. Set the technical direction for the CX backend (services, data pipelines, API patterns) with an eye for scalability, reliability, and developer experience.
Own core data foundations. Design resilient data-access patterns across Snowflake, Elasticsearch, Kafka, Redis, and MySQL; keep pipelines fast, fresh, and reliable.
Mentor and elevate. Help engineers across the CX group grow in backend craft, AI engineering, and system design thinking.
Collaborate cross-functionally. Work with product, design, and customer-facing teams to turn ambiguous problems into well-scoped, high-quality solutions.
Requirements:
What you'll need:
6+ years of backend engineering experience with strong expertise in Node.js and TypeScript.
Hands-on experience building or integrating LLM-powered features or agentic workflows into a production product (not just internal tooling).
Experience with distributed systems and event-driven architectures, and comfort with stores like Kafka, Redis, Elasticsearch, MySQL, and Snowflake.
Strong familiarity with cloud-native environments. AWS experience is a significant advantage.
Deep systems thinking: you design for scale, resilience, and maintainability from the start.
Experience building customer-facing products alongside product managers and designers.
Excellent communication: you can align engineers, product, and non-technical stakeholders around a technical decision.
Proven ability to own and drive complex initiatives with minimal oversight.

Itd be really cool if you also have:
Experience with LangChain, LangGraph, LangFuse, or similar orchestration and observability tooling.
Hands-on experience with AWS Bedrock or other LLM provider APIs.
Experience designing or running AI evaluation frameworks (evals, LLM-as-judge, regression suites).
Familiarity with MCP (Model Context Protocol) or building tools for coding agents.
Experience with React, Next.js, or micro-frontend architectures.
Knowledge of Python for AI/data workflows.
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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08/09/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for an AI Engineer to build the systems that drive this: AI agents that investigate vulnerabilities, generate and validate code fixes, and continuously refine their performance. In this role, youll work at the intersection of AI engineering, security automation, and rigorous evaluation to translate cutting-edge models into dependable production tools.

Responsibilities

Build and evolve production AI agent pipelines for CVE research, patch generation, validation, container image remediation, and end-to-end merge requests.

Design the agent capabilities behind those workflows: prompts, tools, model selection, context, guardrails, and integrations.

Build the feedback loops that make our systems better: tracing production runs, creating datasets, defining evals and scorers, and using results to guide iteration.

Analyze real-world performance to answer the questions that matter: Did this change improve patch success, quality, latency, or cost Can we prove it?

Operate what you build in production across Kubernetes, Argo Workflows, AWS, and GitOps.

Partner closely with Product and engineering to focus on the customer problems with the highest security impact-and ship quickly.
Requirements:
Hands-on experience building with LLMs, agentic architectures, and AI workflows-such as LangGraph, Claude Agent SDK, OpenAI Agents SDK, or equivalent.

Strong experience using coding agents such as **Claude Code, Codex, or Cursor** as part of your day-to-day engineering workflow.

A solid grasp of the mechanics of data science and applied AI: evaluation design, experimental rigor, noisy metrics, statistical reasoning, feedback loops, and evidence-based decision-making.

The judgment to distinguish an impressive demo from a system that reliably works in production.

Strong software engineering skills and an experiment-driven mindset: form a hypothesis, build, measure, learn, and iterate.

Comfort working independently in a fast-moving environment with high ownership and little unnecessary process.

Clear communication and good product instincts.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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8814930
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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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הגשת מועמדותהגש מועמדות
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מודים לך שלקחת חלק בשיפור התוכן שלנו :)
26/08/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
As a Senior Full Stack Engineer, youll take the lead on building close management - a brand-new product were creating from scratch that will reshape how finance teams close their books and become a core engine of our companys growth and scale. Youll also work across our other core product domains, agent workflows and data & network. That spans the intelligent agents that do the work for finance teams, the products that help businesses close their books faster and with more control, and the data and network layer that connects it all together. Youll move fluidly between front-end and back-end, owning features end-to-end across whichever of these domains needs you most.
Key Responsibilities
Own features end-to-end - Take ideas from early concept through production across agent workflows, close management, and data & network. You wont just write code - youll ship real systems, iterate quickly, and see the impact of your work in production.
Build best-in-class UX and UI - Design state-of-the-art user experiences and interface flows for our new applications. Front-end craft is central to this role, not an afterthought to back-end work.
Work across the full stack - Move comfortably between front-end interfaces and back-end services, APIs, and data pipelines.
Build across agent workflows, close management, and data & network - Develop the intelligent agents that automate work for finance teams, our brand-new close-management product - built from scratch - that powers a faster and more controlled close, and the data and network infrastructure that connects it all together.
Think beyond the task - Take initiative, understand the broader system and business context, and help drive both product and technical decisions. This is not a ticket-driven role.
Leverage AI-accelerated development practices - Use modern AI coding tools to improve development velocity, code quality, and testing efficiency while building robust, secure, and scalable infrastructure.
Design for scale - Build products and services that are reliable, maintainable, and architected to scale with the platform.
Requirements:
Genuine full-stack experience - Hands-on, professional experience across both front-end and back-end development. Hands-on experience with React on the front end (our standard stack), and equal comfort on either side of the stack.
7+ years of professional software engineering experience, spanning both front-end and back-end work
Proven experience owning real-time, mission-critical systems where low latency, correctness, and high availability are non-negotiable
BSc in Computer Science or equivalent hands-on experience
A builders mindset, with a track record of taking complex products from idea to production and scaling them
Comfortable working across the stack - from user-facing interfaces and APIs to data pipelines and infrastructure
A modern engineering mindset, with strong instincts for using automation and AI tools to increase impact and velocity
A high bar for quality and a willingness to challenge yourself and the team
Clear communication skills and the ability to collaborate effectively in small, senior teams.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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8797677
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