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1 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're looking for a Senior AI Product Manager to take ownership of core areas of our B2B platform - the point where powerful AI capabilities become real products that customers rely on. We've already built the foundation: rich data, agentic infrastructure, and deep domain intelligence. Now we need someone who can take what's working with one customer and make it work everywhere - productizing capabilities, scaling them across our customer base, and raising the quality bar as they grow.

This is a hands-on builder role. You'll work in close, direct partnership with both customers and R&D - running discovery, analyzing the data, and prototyping ideas yourself, then teaming up with R&D to bring them to life at scale.

This is a fast-moving area, and we'll shape the exact scope together, based on where you can create the most leverage for the business. We're looking for true startup reflexes: the ability to shift focus as priorities shift, zero in on what matters most this quarter, and make clear, deliberate trade-offs.

If you thrive in a fast-paced startup environment and want to build AI products that make complex insights accessible and actionable for a real-world, >$1B industry, this role is for you.

What You'll Do

Own core areas end to end - strategy, discovery, execution, and measurement. Define what success looks like in numbers, and stay accountable to it well beyond launch.
Productize and scale what works. Turn capabilities proven with one customer into products that work seamlessly across your entire customer base.
Lead discovery yourself. Run customer and prospect conversations to uncover what people will actually pay for, and bring back a scoped, evidenced bet.
Prototype your ideas. Go from concept to working prototype using coding agents and AI tooling, with a design bar high enough to serve as a real proposal.
Own quality. Define what "good" means for our agents, build the evals to measure it, and raise the bar on reliability, cost, and trust as the system evolves.
Partner deeply with R&D. Engage on technical trade-offs - accuracy, latency, cost, build vs. buy - and earn the team's respect through substance.
Drive it to market. Team up with design, sales, marketing, and customer success to package, position, and launch it, then feed adoption data back into the roadmap.
Requirements:
4+ years in product, ideally with a mixed background: product plus engineering, or product plus data or analytics. We weigh evidence of what you have built above the number itself.
AI-native practice. You work fluently with agentic systems and know current best practice: tool and context design, retrieval, orchestration, guardrails, failure modes. You have built and run evals, and you can say where your agents broke and what you did about it.
Hands-on data fluency. You independently query and interrogate data to size an opportunity, validate a hypothesis, or judge whether an agent's output is any good. SQL and Python or equivalent, used in real work.
Builder instinct with design judgment. Idea to prototype to product, with coding agents as part of your daily craft. Strong UX orientation for complex data products, and the ability to produce a credible design proposal yourself.
Customer and commercial range. Comfortable leading discovery calls and working directly with sales and marketing. Excellent communication, with the ability to simplify complexity for customers and executives alike.
Startup temperament. Proven experience in startups, ideally at scale-up stage. You resolve ambiguity yourself rather than escalating it, and you make trade-offs explicitly.
Nice to have

Experience with data-intensive, API or infrastructure-adjacent products where part of the customer is internal.
Data acquisition experience: sourcing, licensing, partnerships, and the quality and legal questions that come with them.
Enterprise B2B, especially selling into large CPG, retail or foodservice organizations.
This position is open to all candidates.
 
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10/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Required Product Manager - AI Platform
About the role:
We've taken a platform-first, builder mindset from day one, developing the modular building blocks we call pillars. Our users are exceptional engineers who continuously build creative and unexpected solutions with our platform. Being a PM here means embracing that creative tension while staying relentlessly focused on where the platform needs to go next.
As a PM, you'll own a pillar end-to-end alongside your team of engineers and designers. You'll build and evolve it as a standalone value stream and as a connected part of the broader platform. PMs are full picture owners: they shape the story of their pillar from market positioning to technical enablement, defining success not just by what gets shipped, but by the measurable impact it delivers.
What you'll do:
Define what to build and why. Go deep with customers, analyze usage data, and research the competitive landscape. Bring that view to your team, build a sharp perspective on what's worth building next, and communicate the reasoning to engineering, leadership, and the market.
Shape experiences engineers choose to use. Our developer experience spans the entire ecosystem across the UI, API, CLI, and daily chat and coding interfaces. Work closely with design and engineering to make each surface deliberate, from the first wireframe through launch.
Drive cross-functional impact. PMs don't hand off and wait. You work across engineering, design, marketing, sales, and CS throughout the full product cycle, accountable for picking the right problem, the solution built, and whether the launch lands.
Build for agents and developers. We are the context and action layer for both. Shape your domain so agents can act on it reliably and developers can navigate it intuitively. Understand the tradeoffs in how data, APIs, and interfaces serve both. Separate the signal from the hype, and use that view to sharpen your roadmap.
Measure what matters. Define success metrics before you ship. Track adoption, analyze what's landing, and iterate until the outcome is real.
Requirements:
4+ years in product management across at least two companies or roles, with a track record of shipping products that developers or technical users rely on.
Shipped an AI-powered product.You know what it takes to get an AI product or feature into production at a quality bar that users trust.
Technically grounded. You've experimented with APIs, MCP, CLI, and similar surfaces. You can think like the engineer you're building for and hold your own in technical conversations.
Obsessed with experience. You care deeply about how something feels to use, not just what it does. Whether it's a UI, API, chat, or CLI interface, you've worked closely with designers and engineers to make each surface right, and pushed back when something wasn't good enough.
Analytical. You work with both qualitative and quantitative data to drive decisions. You define success metrics before you ship and use them to decide what to do next.
Hands-on with AI. AI tools are part of your daily workflow. You have a real thesis on where AI for developers is heading, and you can articulate why.
Strong communicator. You explain product decisions clearly, inspire the team around a direction, and can tell the story of what you're building to customers and executives alike.
Collaborative by default. You share credit, ask for input, and make the people around you better. You've pulled a team forward on something hard, not just contributed to it.
This position is open to all candidates.
 
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19/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are a fast-paced, technology-driven team where everyone's contribution impacts product success.

We are looking for a hands-on, business-minded AI Engineer to join our Data & AI Team.

This role is for someone who has already built and shipped real AI products in a company environment. You will work as an integral part of the Data & AI Team, partnering directly with business stakeholders to identify high-impact opportunities, translate business needs into technical solutions, and build AI products that automate internal processes and create immediate value.

The ideal candidate is a builder. You should be comfortable working with LLMs, AI agents, automation workflows, APIs, data pipelines, data warehouses, and internal company systems. You should also be comfortable taking ownership, asking sharp business questions, and moving ideas from concept to production.

Our Data Team has already built internal AI products at our company. Now we are looking for someone who can help take us to the next level.

What Were Looking For
The right person has built with AI in a real company environment and knows how to turn business needs into practical internal products. They should be comfortable working with stakeholders, understanding how teams operate, and identifying where AI can create meaningful value.

Because this role sits inside the Data & AI Team, they also need to be strong with data. That means working confidently with company data, data warehouses, pipelines, APIs, and the technical building blocks that make AI products reliable and useful.

This role is for someone hands-on, curious, and hungry to build. Someone who can combine AI, data, and business context to help our company move faster, automate smarter, and turn ideas into measurable business wins.

What Youll Do
Build end-to-end internal AI products, automations, agents, and workflows that solve real business problems across our company.
Work directly with business stakeholders to understand pain points, define requirements, and turn ideas into scalable AI-driven solutions.
Design, prototype, test, deploy, and maintain production AI products using LLMs, AI agents, APIs, automation frameworks, and internal company data.
Work hands-on with data tools and infrastructure, including Snowflake, ETLs, data pipelines, APIs, AI tools, and internal servers.
Identify high-impact manual processes and turn them into automated AI-driven business wins.
Evaluate new AI tools, frameworks, and agentic workflows, and apply them where they can improve productivity, decision-making, or business operations.
Help shape internal AI development best practices around reliability, usability, security, documentation, maintainability, and production readiness.
דרישות:
2-5 years of hands-on experience in AI Engineering, Data Engineering, Software Engineering, Data Science, Analytics Engineering, or a similar technical role.
Proven experience building and deploying AI-powered products, workflows, agents, automations, or business solutions in a real company environment.
Strong hands-on experience with LLMs, AI agents, prompt engineering, RAG, workflow automation, APIs, or AI development frameworks.
Ability to code and build practical solutions using Python, SQL, JavaScript/TypeScript, or similar languages.
Strong data experience, including ETLs, data pipelines, APIs, databases, data warehouses, and Snowflake.
Experience working in a SaaS or B2B technology company.
Strong business acumen, ownership, and communication skills, with the ability to work independently with stakeholders and drive projects from idea to production.
Degree in Engineering, Computer Science, Mathematics, Statistics, Physics, or a related quantitative field - advantage
Advantages
Experience with agent frameworks, RAG systems, vector databases, orchestration tools, Snowflake, Airflow, Rivery, Gitlab, Claude, OpenAI, or similar tools.
Experience working in a cybersecurity or data company.#ENGLISH המשרה מיועדת לנשים ולגברים כאחד.
 
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לפני 2 שעות
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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04/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Own the intelligence layer - the AI research pipeline that classifies and risk-scores every tool we find. Discovery tells us what software an organization runs; the AI does the hard part: figuring out what each tool actually is, what it can do, how it handles data, and how risky it is. You'll own that research and enrichment system end to end - the LLM-backed agents, the prompts and context that drive them, the evals that keep them honest, and the cost and latency of running them at scale.

This is an engineering role, not a research one. You'll ship production TypeScript, and you'll be measured on the accuracy, cost, and reliability of the intelligence the product depends on.

What you'll work on

The multi-agent researcher system: LLM-backed agents that research each tool across topics like platform, data policy, AI models, and agentic capabilities, and return structured, evidence-backed classifications.

Evals and quality: design eval sets, measure classification accuracy and hallucination, and turn prompt changes into regression-tested, reviewable diffs instead of guesswork.

Grounding and trust: cite evidence, resolve contradictions between AI output and validated data, and drive down hallucination on the fields that matter.

Model routing and cost/latency: choose and route across providers, tune concurrency and caching, and keep the pipeline fast and affordable as volume grows.

Structured outputs, tool/function calling, and the schemas and validation that make model output safe to persist.

Deep observability into the pipeline - spans, traces, and metrics for every model call.
Requirements:
3+ years of software engineering with hands-on, in-production LLM experience - you've shipped an AI-powered system that real users depend on, not just notebooks or demos.

Strong prompt and context engineering: you treat prompts as artifacts you version, test, and improve.

An eval-driven instinct: you reach for a measurement before you reach for a bigger model, and you know how to detect and reduce hallucination.

Fluency with structured outputs, function/tool calling, and multi-agent orchestration.

Solid engineering fundamentals - you build the pipeline around the model, not just call the API.

Judgment about cost, latency, and provider trade-offs at scale.
This position is open to all candidates.
 
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18/08/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for an experienced and strategic Product Manager to lead a core domain within our companys Cloud Firewall portfolio. This role is central to shaping how enterprises secure cloud environments at scale across hybrid and multi-cloud infrastructures.
our companys cloud security solutions protect some of the worlds largest organizations, and our Cloud Firewall capabilities are a critical part of helping customers enforce consistent, scalable, and intelligent network security in dynamic cloud environments.
As the Product Manager for a core Cloud Firewall capability, you will own the product vision, strategy, and execution end to end - from deeply understanding customer needs, market trends, and cloud platform evolution, through defining roadmap priorities and driving delivery, to ensuring strong adoption and long-term customer value.
You will work closely with engineering, architecture, UX, research, sales, marketing, and customer-facing teams in a highly cross-functional environment. This role requires a strong product leader with proven success in Agile product development, the ability to lead complex cross-functional programs, and a demonstrated record of influencing strategy and execution across engineering, business, and customer-facing teams.
This is an opportunity to influence a strategic cloud security domain and build high-impact products that solve real customer problems in one of the most important areas of cybersecurity.
Key Responsibilities
Define and own the product strategy, vision, and roadmap for our companys Cloud Firewall capabilities, aligned with company objectives, customer needs, and market opportunities.
Lead product discovery by analyzing customer pain points, industry trends, competitor offerings, and emerging cloud security requirements across AWS, Azure, GCP, and hybrid environments.
Work closely with engineering leadership and development teams to translate strategy into execution through clear priorities, well-defined requirements, and pragmatic tradeoff decisions.
Drive product development in a proven Agile environment, including backlog management, feature prioritization, user story definition, sprint planning support, and ongoing collaboration with R&D throughout the delivery lifecycle.
Requirements:
Bachelors degree in Computer Science, Engineering, Business, or a related field. MBA or advanced degree is an advantage.
5+ years of product management experience in cybersecurity, cloud security, network security, or closely related domains.
Strong technical understanding of cloud networking, firewall technologies, network security controls, and cloud security architectures in AWS, Azure, and GCP environments.
Proven track record of owning and delivering complex products in Agile / Scrum development environments leading to business success, with hands-on experience working closely with engineering teams throughout iterative release cycles.
Proven leadership experience, with the ability to lead cross-functional initiatives, influence senior stakeholders, and drive alignment across organizations without direct authority.
Track record of creating real & measurable impact on the products and services you are responsible for.
Demonstrated ability to manage complex projects from concept to launch, balancing strategic thinking with execution discipline.
Strong analytical and problem-solving capabilities, with a structured and data-driven approach to prioritization and decision-making.
Excellent communication and presentation skills, with the ability to engage effectively with executives, customers, engineering teams, and go-to-market stakeholders.
Self-motivated, proactive, and comfortable operating in a fast-paced, dynamic environment.
Experience with enterprise-scale products and large, sophisticated customer environments is a strong advantage.
Background in cloud firewall, FWaaS, CNAPP, cloud network security, or adjacent cloud security domains is highly preferred.
This position is open to all candidates.
 
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10/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Required AI Data Engineer
About the role:
We're building the intelligence layer that lets everyone ask hard questions of our data and get trustworthy answers - in plain language, in seconds. As AI Data Engineer, you own the semantic and AI-native surface of our Snowflake platform: the governed semantic layer that defines "what a metric means," the Cortex Agents that let business users query it conversationally, and the infrastructure that keeps all of it fast, reliable, and ready to scale.
This is a builder-owner role. You'll ship the semantic models, wire up the agents, and set the standard for how analysts across the company work with data. You'll also lead the Data Analyst guild - the connective tissue that keeps our hub-and-spoke analytics model coherent as it grows.
If you're excited by the space where data engineering, LLM tooling, and analytics governance meet, this role sits right in the middle of it.
What youll Own:
Snowflake semantic layer - Own the semantic layer end-to-end as the single source of truth for metrics; design semantic models, enforce naming standards, and ensure consistent metric definitions across dashboards and AI agents.
Cortex Agents - Design and deploy conversational AI agents using Cortex Analyst and Cortex Search; tune for accuracy and safety, expose through multiple surfaces (Snowflake Intelligence, Streamlit, MCP), and build evaluation harnesses to maintain quality at scale.
Data craft (Analytics guild) - Co-lead the technical track of the Analytics guild; set SQL and modeling standards, run technical enablement and code reviews, and serve as the technical authority for analysts.
Scaling data infrastructure - Improve performance, reliability, cost efficiency, and governance across the dbt/Airflow/Airbyte/Snowflake stack as data volume and query load grow; optimize warehouse sizing, medallion layers, and ingestion pipelines.
What you'll do day to day:
Model and maintain semantic views that power both dashboards and AI agents, keeping definitions versioned, tested, and certified.
Build, evaluate, and iterate on Cortex Agents - including retrieval quality, guardrails, and observability.
Extend and optimize dbt models, Airflow DAGs, and Airbyte connectors across bronze/silver/gold layers.
Partner with GTM, Finance, CS, and Product stakeholders to translate business questions into governed, reusable data assets.
Run the Data Analyst guild: standards, reviews, enablement, and tooling.
Own data quality, lineage, and cost monitoring across the Snowflake platform.
Expose data and agents through Streamlit apps, BI tools (Omni), and MCP servers for internal AI workflows.
Requirements:
5+ years of experience in data engineering roles in B2B SaaS companies
Strong SQL and hands-on data engineering experience building production pipelines (dbt strongly preferred; orchestration with Airflow or similar).
Deep, practical Snowflake experience - warehouse management, performance tuning, cost control, and data modeling.
Experience building or maintaining a semantic / metrics layer, and a strong point of view on metric governance.
Hands-on work with LLM-powered data applications - RAG, text-to-SQL, agent orchestration, or similar. Snowflake Cortex (Analyst, Search, Agents) is a big plus.
A builder mindset paired with the judgment to set standards others follow.
Nice to have:
Experience leading a guild, chapter, or community of practice - or otherwise driving standards without direct authority.
Familiarity with reverse-ETL, streaming ingestion (Airbyte or similar), and BI tooling on a semantic layer (Omni, ThoughtSpot).
Exposure to GTM / RevOps data (CRM, product usage, call intelligence) and the ambiguity that comes with it.
Experience with MCP, Streamlit, or embedding AI into internal tooling.
This position is open to all candidates.
 
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1 ימים
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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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
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8804088
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
6 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for a talented AI-native Software Engineer to join our innovative R&D team!
we help its customers acquire better users and spend less doing it - and our core team owns the engine behind it. We turn raw customer data into ad-network conversions, end-to-end: through large-scale ML and data pipelines, event-driven delivery services on AWS, and the UI that ties it together. There's no narrow lane here - you own problems wherever they live in the stack.
We're an AI-native team: we treat AI and agentic tooling as a first-class part of how we build, and it's how a small team credibly owns this much surface area. We're looking for a high-ownership generalist who works this way (or is hungry to), and who thrives in a correctness-critical domain where a bug means real customer ad-spend going the wrong way.
Responsibilities:
Turn raw customer data into ad-network conversions end to end, building across the whole stack: ML and data pipelines, delivery services, and the customer-facing UI.
Take features from idea to production largely on your own, designing, shipping, monitoring, and iterating, using AI and agentic tooling as a force multiplier, and owning your systems in production where mistakes translate directly into customer spend.
Collaborate closely with the team lead, product, and data scientists to take models and ideas from prototype to reliable, scaled-up production.
Requirements:
3+ years of hands-on experience building production cloud systems end to end: architecture, development, testing, and cloud-native work in production.
Strong Python (our primary language), and solid software engineering foundations: software design principles, concurrency, data structures, and cost/performance trade-offs.
An AI-native, can-do generalist: you use (or are eager to adopt) AI and agentic tooling as a core part of how you ship, you're comfortable across the whole stack and unafraid of unfamiliar territory, and you take strong ownership of systems end to end on a small team.
A team player with excellent communication skills, strong independent-learning ability, and curiosity to explore new fields and constantly improve.
Advantage:
SQL and modern data warehouses (Snowflake, BigQuery or Databricks equivalent).
Experience with ad-network, martech, attribution, or measurement ecosystems (Google Ads, Meta, MMPs, conversion APIs).
Experience with modern cloud and orchestration tooling: Temporal, Airflow, Docker, Kubernetes, ArgoCD, Terraform, and AWS.
Background in analytics, data science, or product: you think like an analyst or PM about what makes a signal correct and valuable, not just whether the code runs. We value this highly.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8797628
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דיווח על תוכן לא הולם או מפלה
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v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
11/08/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
As an AI Product Owner & AI Process and Agentic Designer, you will own the process of transforming complex workflows into scalable AI solutions, bridging the gap between business stakeholders and AI Engineers. You will lead business process analysis, identify agentic process opportunities, validate business value, and define solution designs that enable successful AI implementation across the organization.

Responsibilities

Business Process Analysis & Discovery
Partner with business stakeholders to map, document, and analyze existing workflows, identifying inefficiencies, bottlenecks, and manual processes ripe for automation.
Conduct discovery sessions and workshops to deeply understand business needs, pain points, and success criteria across departments.
Agentic Opportunity Identification
Evaluate workflows to pinpoint where agentic and AI-driven approaches can deliver the most value, distinguishing tasks suited to automation, augmentation, or full agentic orchestration.
Maintain a prioritized pipeline of AI/agentic opportunities, assessing each for feasibility, complexity, and impact.
Business Value Validation
Define and quantify the expected business value of proposed solutions (e.g., cost savings, time reduction, quality improvement, revenue impact) and build the business case for investment.
Establish success metrics and KPIs, and track realized value post-implementation to ensure outcomes match projections.
Solution Design & Definition
Translate business requirements into clear solution designs, including agentic process flows, decision logic, data inputs/outputs, integration points, and human-in-the-loop checkpoints.
Define guardrails, escalation paths, and fallback behaviors to ensure solutions operate safely and reliably.
Stakeholder & Engineering Bridging
Serve as the primary liaison between business stakeholders and AI engineers, translating business intent into technical requirements and engineering constraints back into business terms.
Own the product backlog, prioritize features, and clearly communicate scope, trade-offs, and timelines to all parties.
Implementation Enablement & Iteration
Guide solutions through the full lifecycle from concept to deployment, supporting testing, validation, and change management.
Gather feedback, monitor performance, and drive continuous refinement of deployed AI and agentic solutions.
Scalability & Standardization
Identify reusable patterns, components, and best practices to scale successful solutions across the organization.
Contribute to governance frameworks, documentation standards, and design principles for AI/agentic product development.
Requirements:
5+ years in product management, technical/process consulting, or operations roles -with hands-on experience decomposing real workflows from scratch, not just documenting them.
AI and automation literacy - understands what agentic AI can and cannot do, can read enough code to challenge an AI engineer's assumptions, and has worked on at least one AI or automation project.
Strong data fluency-comfortable pulling and analyzing activity data using SQL, Excel, and basic Python or notebook tools.
Executive communication - writes and presents to senior business stakeholders, including charter leads at the VP level and above.
Able to own analysis deliverables independently - this is not a junior coordinator role.
Process-design or operations background in a domain with real workflow complexity (financial services, operations, customer success, claims, etc.).
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8777799
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דיווח על תוכן לא הולם או מפלה
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סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
5 ימים
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
We're looking for an AI Tech Lead to own that standard across three surfaces:
The platform - Today each agent flow is close to a bespoke implementation. You'll turn our hard-won patterns into shared components, conventions, and infrastructure so the next agent is a week of work rather than a quarter - with evaluation, observability, and cost control built in rather than bolted on.
Enablement - Miggo's advantage compounds only if the whole company is AI-fluent, not just R&D. You'll raise that fluency everywhere - engineering, research, product, GTM - through tooling, patterns, and teaching.
The voice - You'll publish the methodology: how we benchmark agentic security output, how we model residual risk, what we learned failing. This is a category-defining position and we want it argued in public.
This is a hands-on lead role with no direct reports. Your authority comes from the quality of what you build and how clearly you explain i
Requirements:
You've shipped agentic systems to production - real orchestration, tool use, structured outputs, and the failure modes that only appear at scale. Not "I've called an LLM API."
You've built the evaluation discipline, not just consumed it: trajectory tests, golden datasets, regression gates, offline replay. "It seems better" is not a metric, and you have opinions about what is.
Deep backend and distributed-systems engineering. Strong Python, and comfort with workflow orchestration (Temporal or equivalent), streaming, and cloud-native infrastructure. Agent platforms are systems problems wearing an AI hat.
Fluency across the modern agent stack - LangChain/LangGraph-style frameworks, multi-provider routing, structured output contracts, prompt and context engineering - with the judgment to know which parts are load-bearing and which are fashion.
Security literacy. Enough to reason about whether an agent's security output can be trusted, and to argue with researchers on the merits. You don't need to be a vulnerability researcher.
Influence without authority. You'll change how three teams work with no one reporting to you. Show us where you've done that.
Advantage: experience with AI/LLM security - red-teaming agents, prompt injection, or agentic attack patterns.
Advantage: background in cybersecurity, detection engineering, or WAF/mitigation systems.
Advantage: you've driven AI adoption across a whole company, not only an engineering org.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8800157
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