דרושים » מוצר » Hands-On R&D Lead - Agentic Data Infrastructure

We are looking for a Senior Product Manager to join our Agentic Search team, building the search and retrieval infrastructure that powers AI agents and LLM-based applications at scale.
This is a hands-on IC role with real ownership. You will take full end-to-end responsibility over a core product area, from defining strategy through shipping and iterating based on real usage data. You will work within a small PM team reporting to the Director of Product, alongside engineering, design, and go-to-market, shaping how AI agents discover, retrieve, and act on web information in real time.
The product serves both a developer-facing PLG motion and a growing enterprise customer base, so you will need to be equally comfortable digging into API design and search quality as you are running customer discovery calls and informing competitive positioning. We are looking for someone who can operate as a senior strategic partner, not just an executor, and who has the potential to grow into a principal-level PM over time.
Youre welcome to work hybrid from Tel Aviv, Israel

we are looking for a Senior Product Manager.
The hard part is deciding what good enough means. Perfect coverage, perfect freshness, and low cost cannot all be true at once, and the person in this seat is the one who has to make that call for each use case and defend it.
In your first year, we expect you to set a clear quality bar for our search products that the team builds against, have a real influence on where our index goes next, and bring us a point of view on where search infrastructure is heading.
This is a hands-on senior IC role with real ownership, reporting to the Director of Product. You will work day to day with our search engineering and research teams, with the evaluation team, and with customer success, who bring us quality feedback from real accounts every week. Our search engineers are deeply experienced in large-scale retrieval, and the product team is small, so you will argue your case directly with the people building it. That only works if you have built at this scale yourself.
Your responsibilities will include:
Set the quality bar and release criteria for search: what good means per use case, and what a change has to clear before it ships. Our evaluation team owns the measurement, and you work closely with them on what to measure and why.
Own the depth, latency, and cost tradeoffs across our search products, and make them explicit and defensible.
Shape the direction of our index: what it needs to cover, how fresh it needs to be, and what quality bar it has to meet.
Build a point of view on where search infrastructure is going as agents, rather than people, become the main consumer, and turn that into a roadmap.
Know how we compare to the alternatives customers evaluate, and drive the work that closes the gaps that matter.
Work with customer success and directly with customers to understand where our results fall short in real workflows, and turn that into quality priorities.
Partner with the data and vertical product owners on what our corpus needs to contain and how results should be shaped per industry.

We are seeking a Senior Technical Product Manager to join us in Tel Aviv. This is a deeply technical, highly hands-on role at the core of our platform. You will sit side by side with the engineers building it, going into the internals of the systems our customers run on: data modeling, Postgres and MySQL replication, change data capture, sync performance, schema evolution, and the infrastructure that moves data reliably at scale. You will own product areas across the full platform, spanning Ingestion, Reverse ETL, Observability, and Catalog.
Reporting directly to the VP of Product in New York, you will need to be exceptionally effective at managing that relationship remotely: clear written updates, sharp async communication, and the independence to keep moving without daily oversight. At the same time, you will stay close to our customers, through regular calls, acting as their voice in the product even while building alongside the team in Tel Aviv. You will help shape our product culture and how we build for years to come.
What You'll Do
Own Product Areas Across the Platform: Take end-to-end ownership of product areas spanning Ingestion, Reverse ETL, Observability, and Catalog, translating complex technical and data challenges into clear priorities, crisp specifications, and measurable outcomes.
Go Deep on Data Modeling and Infrastructure: Reason fluently about data modeling, schema design, and pipeline internals, including Postgres WAL and logical decoding, MySQL binlog, CDC edge cases, sync performance, and schema evolution, and turn that depth into better product decisions.
Partner with Engineering Side by Side: Work in person, day to day, with our Tel Aviv engineering team to deep dive into problems, unblock delivery, and move fast on high-quality outcomes.
Manage a Remote Reporting Relationship: Keep the VP of Product in New York aligned through clear written specs, proactive updates, and strong async communication, operating with real independence between syncs.
Be the Voice of Customers: Speak regularly with customers to uncover pain points, validate product direction, and ensure what we build resonates with real-world data teams.
Iterate and Prioritize Ruthlessly: Continuously refine the roadmap based on data, user feedback, and results. Make tough tradeoffs and cut scope when needed to ship faster and learn sooner.
Run Tight Feedback Loops: Define and track product metrics, run experiments, and follow through post-launch to confirm outcomes.
Know the Competitive Landscape: Develop a sharp point of view on the data integration and observability market, and use it to inform positioning and prioritization.
Shape Product Culture: Help establish our product rituals and standards, from specs and prioritization frameworks to how we define success and learn from customers.

The ideal candidate is passionate about data and AI, comfortable navigating complex systems, and excited by the opportunity to operationalize AI within a modern enterprise environment. We value curiosity as much as experience: we are looking for someone eager to show what they know, and equally eager to keep learning in a field that moves fast.

Responsibilities
Explore, analyze, and model large volumes of structured and unstructured data in Python, from exploratory analysis and feature engineering through to model validation and communication of results.
Design, train, evaluate, and deploy machine learning models, and monitor their performance, accuracy, and drift in production.
Build and orchestrate Agentic AI solutions - LLM-based agents, RAG pipelines, prompt design, and evaluation frameworks - to automate data quality checks, investigation, and reporting workflows.
Integrate models and agents with internal systems and data sources using MCP servers and clients, and workflow automation platforms such as n8n.
Write efficient and maintainable SQL queries to support analysis, reporting, and data exploration needs.
Collaborate with data engineers to productionise models and agents: reliable data flows, logging, alerting, and performance tuning.
Participate in the development of internal tools and dashboards that make data and AI capabilities accessible across the organization.
Share findings with the team and help evaluate emerging AI tooling as the ecosystem evolves.

As a Fraud Data Scientist, you will be at the front lines of protecting our ecosystem from sophisticated financial fraud and abuse. You will join a high-impact team operating in a data-rich, high-frequency environment where seconds matter.

In this role, you will take ownership of the end-to-end machine learning lifecycle-from uncovering complex fraud patterns to deploying highly scalable, real-time models into production. You will collaborate closely with Engineering, Product, and Risk Operations to build robust defenses that balance strict security with a seamless user experience.

What You Will Be Doing
Model Development & Deployment: Design, train, and deploy advanced machine learning models (e.g., gradient boosting, anomaly detection, graph networks) to detect and mitigate fraud in real-time.

Production Ownership: Take full ownership of putting models into production systems, ensuring low-latency execution and high reliability.

Agentic Workflows: Research, build, and implement Agentic flows and LLM-driven orchestration to automate multi-step fraud decisioning, logic routing, and investigation paths.

Adversarial Analysis: Conduct deep-dive exploratory analysis on massive datasets to identify emerging fraud vectors, loops, and coordinated attacks.

Feature Engineering: Build and optimize real-time streaming and batch features to improve model signal and precision.

Experimentation & Monitoring: Design rigorous shadow-testing and A/B testing frameworks for new models. Set up continuous monitoring pipelines to catch data drift and performance degradation early.

We are looking for an experienced Applied Data Scientist with expertise in building agentic systems and autonomous agents to join one of our R&D. You will be at the core of transforming our supply chain solutions into a fully agentic platform - designing and building agents that autonomously generate analytical pipelines, orchestrate multi-step reasoning, and resolve complex logistics challenges for our customers. You will combine strong machine learning and deep learning expertise with the ability to architect and implement production-grade agentic systems, working closely with engineering, product, and domain experts to push the boundaries of what autonomous AI can do in supply chain.
Responsibilities:
Design and build autonomous agentic systems that generate, configure, and execute analytical pipelines to solve supply chain challenges end-to-end
Architect multi-agent workflows with planning, tool use, memory, and feedback loops - enabling agents to reason, adapt, and improve over time
Develop and integrate ML and deep learning models (e.g., predictive models, anomaly detection, demand forecasting) as core capabilities within agentic pipelines
Research and apply state-of-the-art techniques in agentic AI, LLM orchestration, and multi-agent systems to production use cases
Translate complex logistics and supply chain challenges into agent-based problem formulations, collaborating closely with product and domain experts
Define and implement rigorous evaluation frameworks for agent performance: correctness, reliability, robustness, and edge-case handling
Collaborate with software engineers to productionize agentic solutions - including testing, monitoring, versioning, and iterative improvement
Contribute to team practices: reproducible code, experiment tracking, documentation, and knowledge sharing

Were looking for a Senior Data Scientist to be a core driver in how our product empowers security teams. You will be expected to deeply understand customer needs and translate them directly into product features that deliver real value. You'll own key parts of our frontend stack, drive key architectural decisions, and turn complex security data into clear, actionable business insights.

In this role, you will design, build, and productionize advanced models that help organizations secure AI systems across data, models, and runtime usage. Youll work closely with Product, Engineering, and Security teams to turn complex, real-world security problems into scalable, high-impact AI solutions.

This is a high-impact, hands-on role with true ownership, where your work directly shapes the intelligence powering a category-defining AI Security platform.


What Youll Do:

Own End-to-End Model Development (Research → Production)

Take full ownership of the model lifecycle: problem definition, research, prototyping, training, evaluation, deployment, and ongoing optimization.

Design and build scalable ML / AI solutions to detect, analyze, and mitigate AI-related security risks.

Ensure models are robust, explainable, and production-ready in real-world enterprise environments.

Partner Deeply with Product & Engineering

Collaborate closely with Product Managers to translate customer pain points and security requirements into clear modeling objectives.

Work hands-on with engineering to integrate models into production systems and data pipelines.

Balance research depth with pragmatic execution and business impact.

Build AI Security Intelligence

Develop capabilities across areas such as AI behavior analysis, anomaly detection, model governance, data risk detection, and usage observability.

Work with structured and unstructured data, including logs, prompts, model outputs, and metadata.

Continuously iterate on models based on usage patterns, feedback, and emerging threat vectors.

Lead Research POCs & Innovation

Stay at the forefront of LLMs, applied ML, and AI security techniques and bring new ideas into the product.

We're looking for a Data Scientist to join our team. As a Data Scientist, youll be a key member of our AI team, designing, building, and deploying cutting-edge AI systems that leverage large language models (LLMs), unstructured data, and advanced ML techniques. Youll be instrumental in bringing AI from research to real-world production, delivering high-impact features that drive our security platform.

In this role, you'll have a unique opportunity to solve complex problems, work with large scale data and be part of the core team that shapes the future of AI in the company.


WHAT YOU WILL DO
Design and develop end-to-end AI solutions, from data ingestion and modeling to deployment and observability.
Build and fine-tune LLM-based applications to tackle complex cybersecurity challenges.
Own the full ML lifecycle - from ideation and experimentation to production readiness.
Collaborate with product, engineering, and security teams to turn AI research into user-facing features.
Work with large-scale unstructured data (e.g., logs, threat intel, alerts) to extract meaningful insights.
Evaluate and optimize AI system performance, scalability, and reliability.
Contribute to core architectural decisions related to AI and ML infrastructure.

We are looking for an experienced Applied AI/ML Scientist with expertise in building agentic systems and autonomous agents to join one of our R&D. You will be at the core of transforming our supply chain solutions into a fully agentic platform, designing and building agents that autonomously generate analytical pipelines, orchestrate multi-step reasoning, and resolve complex logistics challenges for our customers. You will combine strong machine learning and deep learning expertise with the ability to architect and implement production-grade agentic systems, working closely with engineering, product, and domain experts to push the boundaries of what autonomous AI can do in supply chain.
Responsibilities:
Design and build autonomous agentic systems that generate, configure, and execute analytical pipelines to solve supply chain challenges end-to-end
Architect multi-agent workflows with planning, tool use, memory, and feedback loops, enabling agents to reason, adapt, and improve over time
Develop and integrate ML and deep learning models (e.g., predictive models, anomaly detection, demand forecasting) as core capabilities within agentic pipelines
Research and apply state-of-the-art techniques in agentic AI, LLM orchestration, and multi-agent systems to production use cases
Translate complex logistics and supply chain challenges into agent-based problem formulations, collaborating closely with product and domain experts
Define and implement rigorous evaluation frameworks for agent performance: correctness, reliability, robustness, and edge-case handling
Collaborate with software engineers to productize agentic solutions - including testing, monitoring, versioning, and iterative improvement
Contribute to team practices: reproducible code, experiment tracking, documentation, and knowledge sharing

Were looking for a Data scientist Expert to join us and spread the power of our company. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems at our company. You will work closely with cross-functional teams to explore, innovate, and implement AI-driven solutions to tackle emerging threats, examine cloud security features, and enhance the companys security posture.
Responsibilities
Lead applied research on AI agents and LLM-driven features in the company platform - from autonomous threat investigation agents to AI-powered security operations workflows.|Cover a range of features - from leveraging LLMs to enhance customer investigation experience to novel usage of AI for cloud security.
Collaborate with engineering teams to design, build, and maintain production pipelines.
Work closely with the Security Research and Product teams to define research goals.
Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments.
Stay abreast of cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions' accuracy, efficiency, and scalability.