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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior AI Ops Engineer to join our AIOps team and help build the AI-powered platforms, agents, and workflows that enable engineering teams across our company.
This is a hands-on role for someone who can take AI solutions from idea to production, build the infrastructure around them, and create the observability needed to understand and improve how they behave in the real world.
Job responsibilities
Build and operate production-grade AI agents, AI-enabled tools, and workflows that empower developers and operational teams.
Design agentic systems using frameworks such as LangGraph, LangChain, and Supervisor, including RAG, MCP integrations, tool calling, and guardrails.
Build and evolve an AI SDLC harness that helps teams plan, implement, validate, govern, and safely deliver AI-assisted software changes.
Lead AI observability with Langfuse and OpenTelemetry, including tracing, evaluations, quality measurement, and cost analysis.
Build automated evaluation frameworks, including LLM-as-a-judge, to improve the reliability and quality of AI systems.
Design and maintain the infrastructure, CI/CD pipelines, GitOps workflows, and security controls that support AI services.
Develop internal developer tooling and automation that removes friction across the engineering organization.
Partner with engineering and product teams to turn real operational challenges into scalable AI-powered solutions.
Requirements:
Requirements are often considered a measure of how equipped you are to do the job, but sometimes they arent the only factor. If you dont have all the skills, wed still like to hear from you. This could be the perfect fit for you and us.
5+ years of experience in DevOps, Platform Engineering, SRE, or similar infrastructure-focused roles
Strong coding experience in Python, Go is an advantage
Hands-on experience building or operating production LLM applications and agentic workflows
Experience with LangGraph, LangChain, Supervisor, or similar frameworks
Experience building AI SDLC platforms or harnesses that support the full lifecycle of AI-assisted software delivery
Experience with AI observability and evaluation, preferably Langfuse, OpenTelemetry, and LLM-as-a-judge approaches
Experience with AWS, Kubernetes, Helm, and GitOps CI/CD tools such as GitHub Actions and ArgoCD
Experience building internal developer platforms, DevEx tooling, or engineering automation
Strong ownership, problem-solving skills, and ability to lead cross-team initiatives
Nice to have
Experience with RAG, knowledge bases, MCP, tool calling, and AI guardrails
Experience with Terraform/OpenTofu, Crossplane, and the wider Argo ecosystem
Experience with Datadog, Prometheus, service mesh technologies, or large-scale distributed systems.
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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Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a proactive and skilled Software Infrastructure Developer with a strong Agentic AI focus to join our team. In this role, you will design and build the infrastructure, tooling, and AI-powered automation that keep our engineering systems reliable, scalable, and intelligent.

You will be responsible for embedding GenAI and agentic capabilities into our internal developer platforms and CI/CD workflows - creating frameworks, libraries, and multi-agent systems that accelerate automation, improve system stability, and unlock new levels of engineering productivity. This is a hands-on role for someone who thrives at the intersection of infrastructure engineering and applied AI.

The ideal candidate brings deep technical expertise in Python (FastAPI) and/or TypeScript, Kubernetes, CI/CD (Jenkins, GitHub Actions), containerization, and cloud infrastructure - combined with hands-on experience building LLM-powered applications, agents, MCP servers, and RAG pipelines.

What you'll be doing:
AI Platform Development: Design and build internal AI platforms, reusable SDKs, libraries, tools, and MCP servers for agentic applications.
Agentic Workflow Development: Develop single- and multi-agent workflows covering planning, tool selection, delegation, state and memory management, execution, retries, fallbacks, error recovery, and human-in-the-loop approval.
AI-Powered Infrastructure & CI/CD: Integrate AI capabilities into Kubernetes infrastructure and Jenkins/GitHub Actions pipelines to improve development, testing, deployment, and operational workflows.
AI Observability & Evaluation: Implement agent tracing, prompt and tool-call logging, latency and error monitoring, token and cost tracking, regression testing, and failure analysis.
AI Security & Governance: Apply guardrails, access controls, auditability, and governance practices to ensure agents operate safely and reliably.
End-to-End Platform Ownership: Own AI platform capabilities from architecture through production and build reusable solutions that accelerate adoption across engineering teams.
Cross-Functional Collaboration: Collaborate with engineering and business teams to identify high-impact AI opportunities and translate them into scalable technical solutions.
AI Research & Innovation: Evaluate emerging AI frameworks, models, and cloud technologies and promote their adoption where they provide measurable value.
Requirements:
Core Engineering
Minimum of 5 years of hands-on development experience with Python and/or TypeScript.
Experience building asynchronous backend services and APIs using FastAPI or an equivalent modern framework.
Strong software-engineering, analytical, troubleshooting, and cross-functional collaboration skills.
Ability to build reliable, reusable internal platforms that improve developer productivity and accelerate technology adoption.

Infrastructure & DevOps
Strong experience with Kubernetes and Helm, including deployment, networking, resource management, autoscaling, troubleshooting, chart development, templating, versioning, and release management.
Strong experience with Docker, Jenkins, GitHub Actions, and AWS and/or Azure.
Familiarity with Infrastructure as Code, GitOps, and Git-based collaborative workflows.

AI & GenAI
AI Experience - Mandatory: Minimum of 2 years of hands-on production experience building LLM-powered applications, AI agents, multi-agent systems, or internal AI platforms.
Hands-on experience with LangChain, LangGraph, Claude Agent SDK, and OpenAI and/or Anthropic APIs.
Strong understanding of agent architecture, including planning, tool selection, delegation, state and memory management, retries, fallbacks, error recovery, and human-in-the-loop workflows.
Experience with prompt and context engineering, tool/function calling, and structured outputs.
Experience building and integrating MCP servers and clients, including tool schemas, permissions, reliable execution, and error handling.
This position is open to all candidates.
 
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30/09/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for an AI Builder to serve as the technical backbone of Nomas internal AI function. Youll build the LLM-powered agents, automation pipelines, integrations, and infrastructure that teams across the company rely on every day.

This is a rare opportunity to build a new function from the ground up within a company where the work can have an immediate and meaningful impact. Youll create systems such as tools that help Sales track competitive deals in real time, pipelines that automatically turn customer calls into Salesforce updates, and agents that identify competitor activity and deliver actionable insights directly to Slack.

This is a highly hands-on role with true end-to-end ownership-from translating business needs into focused technical solutions to deploying, monitoring, and continuously improving production systems.

What Youll Do:

Build AI-Powered Agents and Automations
Design and build LLM-powered agents, automation pipelines, and backend services used across the organization.
Develop complex integrations that bring together data from multiple internal and external systems.
Build custom MCP servers and other infrastructure required to support scalable internal AI workflows.
Turn fuzzy business needs into practical, focused, and maintainable technical solutions.

Own the Internal AI Infrastructure
Harden and maintain Nomas existing MCP Gateway ecosystem.
Improve reliability, error handling, authentication, secrets management, and versioning.
Implement secure, vault-based credential management and strong security practices across production automations.
Build infrastructure that enables agents and workflows to operate reliably at scale.

Drive Production Readiness and Reliability
Own the deployment, monitoring, maintenance, and reliability of agents and automations in production.
Build evaluation frameworks, test sets, and monitoring processes to measure accuracy, precision, recall, hallucination rates, and overall agent performance.
Identify regressions and continuously improve the quality and stability of production workflows.
Troubleshoot failures across integrations, mod
דרישות:
What You Bring:
3-5 years of software engineering or hands-on development experience.
Strong Python skills and experience writing clean, maintainable, production-grade code.
Hands-on experience working with LLM APIs such as Anthropic Claude, OpenAI, or similar.
Experience building integrations using REST APIs, webhooks, and asynchronous pipelines.
Experience with automation platforms such as n8n, Make, Zapier, or similar.
Hands-on experience with MCP and building or integrating MCP servers.
Experience evaluating LLM or agent performance in production, including building evaluation harnesses or test sets to identify regressions.
Understanding of secrets management, credential handling, and security best practices for production automations.
Ability to work independently and own projects end-to-end.
Strong problem-solving skills and the ability to turn ambiguous requirements into practical technical solutions.

Who You Are:
Genuinely excited about AI and actively following developments in the space.
Adaptable by default-you learn quickly, pivot when needed, and dont become overly attached to a specific tool or approach.
You ship quickly, gather feedback, and iterate.
You care about the end user and business impact, not only the technology.
Comfortable working in a fast-moving startup environment without an established playbook.
Highly accountable, hands-on, and motivated by building something from the ground up.

Nice to Haves:
Background in cybersecurity or enterprise B2B SaaS.
Experience with agent frameworks such as LangChain, LangGraph, CrewAI, or equivalent.
Experience building internal developer platforms or company-wide automation infrastructure.
Familiarity with Salesforce, Slack, and other common enterprise systems.
Experience driving internal adoption of AI tools and המשרה מיועדת לנשים ולגברים כאחד.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Required GTM AI Engineer
About the role:
Our Revenue Operations team has already begun experimenting with AI agents and automation across the go-to-market lifecycle. Weve seen enough to know there is a much bigger opportunity.
Now were looking for an AI builder to take that from experimentation to a real capability across the Go To Market teams.
Youll identify high-value opportunities, build and deploy AI-powered workflows and agents, create the foundations that allow them to operate safely in production, and help define how AI becomes part of the everyday operating model for our GTM organization.
This is a hands-on builder role with broad ownership. Youll work across Sales, Solutions, Customer Success, Marketing and RevOps, combining engineering ability with a strong understanding of how commercial organizations actually work.
What you'll do:
Build AI into the GTM lifecycle- Design and ship agents, automations and AI-powered workflows across areas such as prospecting and enrichment, lead management, account planning, deal support, approvals, pipeline management, forecasting, call intelligence and expansion.
Turn prototypes into production systems- Take promising internal experiments and build them into reliable services that can be used across the organization. Youll work with our engineering and DevOps teams to make sure what we build is secure, maintainable and scalable.
Design for trust and appropriate autonomy- Define where AI can act independently, where people should remain in the loop, and how those boundaries are enforced. Youll build the evaluation, monitoring, permissions and audibility needed for agents that interact with real commercial systems and data.
Build on strong data foundations- Agents are only as useful as the systems and data they can rely on. Youll work across our CRM, GTM tools and data warehouse to improve how information is connected, structured and made available to AI-powered workflows.
Measure real business impact- We care less about the number of agents shipped than what they change. Youll measure impact through outcomes such as faster cycle times, better data quality, higher productivity, improved conversion or time returned to teams - and communicate that impact clearly to the business.
Make the whole organization more capable- You wont be the only person building with AI. Part of your role is creating the patterns, tooling and standards that allow others to build safely and effectively - while making it easy for the wider organization to discover, trust and use what has been created.
דרישות:
3-7 years of relevant experience, in roles such as GTM Engineer, AI GTM Engineer, RevOps Engineer, Business Applications Engineer, a Solutions/Sales Engineer with a strong technical background, an AI-forward Salesforce Developer, or a Forward Deployed Engineer.
Strong engineering ability. You can take an idea from prototype to working production system, integrate with APIs and existing applications, and make pragmatic technical decisions along the way.
Hands-on experience building with LLMs and agents. Youve built systems involving tool use, structured workflows, context management, retrieval, agent frameworks or similar approaches, and understand how to evaluate whether they are actually working reliably.
Production mindset. Youre comfortable deploying and operating cloud-based services and working with concepts such as authentication, permissions, CI/CD, secrets, monitoring and observability.
Integration experience. Youre comfortable working with REST APIs, webhooks, OAuth, Slack applications, SQL and data warehouses.
Good judgment about AI autonomy. You understand the difference between generating an answer and taking an action, and know how to design systems appropriately when AI interacts with important business processes.
Commercial curiosity. You naturally look for high-leverage problems. You can understand a workflow, determine whether it is worth automating#E המשרה מיועדת לנשים ולגברים כאחד.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a talented and motivated Software Engineer with hands-on experience building and operating multi-agent AI systems in production to join our company Automation Platform (DAP) team.
The team develops automation tools, orchestration capabilities, and intelligent platforms that simplify the deployment, management, troubleshooting, and optimization of large-scale network and AI infrastructure environments.
You will work on the design and development of AI-powered systems that bridge networking, automation, observability, and distributed infrastructure - running on Kubernetes at scale. Our stack includes LangGraph, Langfuse, RAG pipelines, MCP, and agent-to-agent (A2A) communication patterns.
This role combines strong software engineering with practical AI application development, with a sharp focus on production hardening, tracing, evaluation, and safety of agentic systems - not model training or research prototypes.
Requirements:
5+ years of hands-on software engineering experience building production-grade backend services, APIs, or AI-powered systems.
Proven production experience with multi-agent AI systems: deployment, tracing, guardrails, hardening, and incident management.
Hands-on experience with agentic frameworks such as LangGraph, CrewAI, Google ADK, AutoGen, or equivalent.
Experience building and running evaluation pipelines for agentic solutions - including trajectory tracing, ground truth validation, and harshness/quality scoring.
Strong Python proficiency: comfortable building scalable backend services using gRPC and REST APIs.
Solid understanding of distributed systems: fault tolerance, consistency models, service communication, and operational challenges at scale.
Hands-on Kubernetes experience: deploying and operating containerized services, managing workloads, config, and scaling in production clusters.
Practical experience with embeddings, vector databases, and semantic retrieval systems in production.
Practical experience with RAG pipelines, LLM API integration, structured outputs, and tool calling in production environments including building and serving MCP servers at scale.
Working knowledge of SQL and/or NoSQL databases, schema design, and query optimization.
Strong debugging skills across application logic, APIs, data, and AI agent behavior.
Strong communication skills and a bias toward ownership and delivery.
Nice to Have
Familiarity with Langfuse/Arize Pheonix.
Familarity with A2A & A2UI protocols.
Experience with network automation, orchestration, or configuration management (Ansible, Terraform, NETCONF, gNMI, or similar).
This position is open to all candidates.
 
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31/08/2026
חברה חסויה
Location: Tel Aviv-Yafo and Netanya
Job Type: Full Time
We're seeking a hands-on AI Solutions Specialist to lead the development and implementation of enterprise-wide AI applications. In this pivotal role, you'll evaluate and deliver cutting-edge AI solutions to employees and teams across the organization. You'll spearhead AI solution projects from initial concept and gathering requirements through execution and widespread adoption, serving as the central point of contact between business, IT, and data teams. You'll also be at the forefront of the latest AI technologies.

As an AI Solutions Specialist you will
Partner directly with cross-functional and non-R&D teams to understand workflows, pain points, decision-making processes, manual tasks, and operational bottlenecks - diagnosing where GenAI and AI Agents can provide real, measurable value.
Translate ambiguous business problems into clear AI use cases, MVP definitions, solution designs, success metrics, and rollout plans.
Lead the lifecycle of GenAI-driven applications and Agents, transitioning rapidly from initial concept and technical feasibility to full enterprise-grade production rollouts.
Build and configure AI-powered solutions, including agentic workflows, workflow automations, RAG-based tools, decision-support tools, and integrations with internal systems.
Conduct technical audits of emerging AI technologies, leading "Build vs. Buy" analyses to ensure global scalability, security, and measurable value to the organization.
Run training and enablement sessions for both technical and non-technical teams, fostering a culture of AI literacy and ensuring the organization can leverage new tools effectively.
Build and evolve the Enterprise AI technology stack, continuously scouting and integrating next-generation platforms, LLM orchestration tools, and agentic frameworks.
Serve as the primary technical liaison between IS, IT, Legal, and Data teams to ensure AI solutions are securely integrated and compliant with enterprise standards.
Be a product owner of enterprise AI platforms, driving continuous solution adoption, impact measurement, and performance optimization across the organization.
דרישות:
5+ years in a technical role such as software engineering, solutions engineering, automation engineering, AI engineering, business application implementation, or a similar hands-on role, including 1+ years delivering AI, GenAI, agentic, or automation solutions for business or operational users.
A clear builder track record: you have shipped tools, automations, workflows, internal products, or prototypes that people actually used.
Deep, hands-on understanding of the LLM lifecycle, including Prompt Engineering, Retrieval-Augmented Generation (RAG), fine-tuning strategies, AI agents, tool use, human-in-the-loop workflows, evaluations, and responsible AI patterns.
Proven experience in implementing Enterprise GenAI platforms (e.g., Gemini Enterprise, Claude Chat).
Hands-on experience developing agentic workflows on top of agentic framework tools like Google ADK, AgentCore, and low-code platforms (Workato)
Proven experience developing GTM-related projects, mainly around sales and marketing.
Proven knowledge of GTM best practices and technology.
Proven project management skills and a demonstrated product management mindset, including the ability to define MVPs, prioritize, separate nice-to-have ideas from high-value use cases, and measure outcomes.
Strong discovery skills with non-technical stakeholders: you can map how work happens today and redesign it around AI, automation, and human accountability.
Excellent communication skills: able to explain technical tradeoffs to business stakeholders and business context to technical teams, and to run training and enablement sessions.
Strong ownership and execution, with creative, out-of-the-box thinking: comfortable moving from ambiguous problems to working solutions, with a focus on business impact and the ability to run and react fast.
Full-stack Web development experienc המשרה מיועדת לנשים ולגברים כאחד.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
Your Career:
The Cortex Content team powers Palo Alto Networks security operations platforms (XSIAM/XSOAR) by building the essential integrations, data connectors, and intelligence layers that protect our customers.
We are looking for a Senior Software Engineer who is passionate about AI and automation to help scale our content ecosystem. In this role, your focus will be leveraging AI to accelerate the delivery, quality, and quantity of our security integrations and content infrastructure. You will design and develop intelligent tools and workflows that enable engineering peers and Technical Program Managers (TPMs) to scale their output, collaborating with them as they test, adopt, and integrate these solutions into our development lifecycle.
Your Impact:
Scale Content Delivery: Design and implement AI-driven systems that empower the team to significantly increase both the quantity and the rigorous quality of our security integrations.
Develop Cross-Functional Tooling: Build internal developer tools and agentic workflows that enable other engineers and TPMs to streamline content creation, validation, and management.
Optimize Workflows: Create reliable CI/CD pipelines incorporating AI agents to automate code generation and testing processes.
Support Team Adoption: Collaborate with engineering peers and cross-functional partners as they test and integrate your tools into their daily workflows, using their feedback to drive continuous improvements.
Contribute to AI Integration: Help lead the practical integration of LLMs and automation frameworks into our day-to-day engineering processes.
Requirements:
Your Experience:
Experience: 3+ years of professional software engineering experience delivering clean, maintainable code in a production environment.
Proven AI/Automation Impact: Demonstrated experience in at least one of the following areas:
Supported or led an AI transformation/adoption effort within an engineering team.
Developed and deployed a major AI-powered feature or internal productivity tool.
Built CI/CD workflows or developer tooling that utilizes autonomous AI agents.
Collaborative Mindset: Experience building tooling meant for other technical stakeholders (engineers/TPMs) and incorporating user feedback into future iterations.
Core Engineering Skills: Solid understanding of software design, API development, and data workflows.
Nice to Have:
Python Proficiency: Strong experience with Python and its associated libraries or AI frameworks (e.g., FastAPI, LangChain, or similar orchestration tools).
Security Knowledge: Familiarity with SIEM, API integrations, or general cybersecurity operations.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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8834205
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מודים לך שלקחת חלק בשיפור התוכן שלנו :)
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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הגשת מועמדותהגש מועמדות
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עדכון קורות החיים לפני שליחה
8812767
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מודים לך שלקחת חלק בשיפור התוכן שלנו :)
30/09/2026
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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הגשת מועמדותהגש מועמדות
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עדכון קורות החיים לפני שליחה
8837820
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דיווח על תוכן לא הולם או מפלה
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
27/09/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior Software Engineer who is passionate about AI and automation to help scale our content ecosystem. In this role, your focus will be leveraging AI to accelerate the delivery, quality, and quantity of our security integrations and content infrastructure. You will design and develop intelligent tools and workflows that enable engineering peers and Technical Program Managers (TPMs) to scale their output, collaborating with them as they test, adopt, and integrate these solutions into our development lifecycle.
Your Impact:
Scale Content Delivery: Design and implement AI-driven systems that empower the team to significantly increase both the quantity and the rigorous quality of our security integrations.
Develop Cross-Functional Tooling: Build internal developer tools and agentic workflows that enable other engineers and TPMs to streamline content creation, validation, and management.
Optimize Workflows: Create reliable CI/CD pipelines incorporating AI agents to automate code generation and testing processes.
Support Team Adoption: Collaborate with engineering peers and cross-functional partners as they test and integrate your tools into their daily workflows, using their feedback to drive continuous improvements.
Contribute to AI Integration: Help lead the practical integration of LLMs and automation frameworks into our day-to-day engineering processes.
Requirements:
Your Experience:
Experience: 3+ years of professional software engineering experience delivering clean, maintainable code in a production environment.
Proven AI/Automation Impact: Demonstrated experience in at least one of the following areas:
Supported or led an AI transformation/adoption effort within an engineering team.
Developed and deployed a major AI-powered feature or internal productivity tool.
Built CI/CD workflows or developer tooling that utilizes autonomous AI agents.
Collaborative Mindset: Experience building tooling meant for other technical stakeholders (engineers/TPMs) and incorporating user feedback into future iterations.
Core Engineering Skills: Solid understanding of software design, API development, and data workflows.
Nice to Have:
Python Proficiency: Strong experience with Python and its associated libraries or AI frameworks (e.g., FastAPI, LangChain, or similar orchestration tools).
Security Knowledge: Familiarity with SIEM, API integrations, or general cybersecurity operations.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8834258
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