דרושים » AI » AI Product Lead

Requirements:
2+ years building or owning products where the deliverable is work getting done - workflow automation, ITSM, orchestration, ops tooling, RPA. Something with queues, approvals, handoffs, and a human on the other end who either trusts the system or works around it.
Experience with agentic AI or LLM-based systems - particularly human-in-the-loop design and how agents hold up their end of a conversation with a person
Enough security fluency to make access decisions responsibly, or the appetite to build it fast. You don't need years in the industry, but you'll be making calls about access and permissions and you can't be squeamish about the stakes.
You're comfortable in the details. You'll spec approval flows and escalation logic with engineering and design, define what "resolved" means precisely enough to measure, and write requirements precise enough to build from.
Nice to Have:
Background in IAM, IGA, or PAM - you know what an entitlement, a group, and a joiner-mover-leaver process actually are
Cybersecurity experience more broadly, in any function
Experience working with customer-facing or POC teams, turning field signal into roadmap.

Requirements:
6+ years of product management experience in B2B/B2B2C SaaS.
Proven, hands-on experience shipping AI-powered features in production, ideally LLM-based agents or agentic workflows that take action, not just generate content.
A strong working understanding of the modern AI stack: LLM capabilities and limitations, prompt and context engineering, RAG, tool/function calling, evaluation frameworks, and cost/latency tradeoffs.
Experience designing human-in-the-loop experiences and building user trust in AI-driven decisions.
A data-driven approach: you define success metrics before you build and you measure outcomes after.
Experience working with US-based customers and understanding their businesses, workflows and buyers.
Excellent communication skills and the ability to drive alignment with senior leaders and cross-functional directors.
A builder's mindset: you're comfortable prototyping on your own (with AI tools, no-code, or code) to test ideas quickly.
Big advantage:
Experience in Proptech, vertical SaaS, HRtech or marketplace products.
Experience building platform or data-layer products (integrations, data models, APIs).
Experience leading or mentoring other product managers.
An early-stage or growth-stage startup background.

Requirements:
The Ideal Candidate
Has 3-5 years of product management experience.
Possesses a strong understanding of agentic / LLM products - from UX to the technical LLM engineering stack.
Spent at least 2 years working in the cybersecurity market, ideally in a SOC-adjacent space (SecOps, incident response, threat intelligence, threat hunting).
Extensively worked with automation products and APIs - can look under the hood and understand systems and architecture.
Data-driven, with the ability to ask the right questions.
Superb English speaking and writing skills.

Requirements:
What you'll bring:

5+ years of Product Management experience, with a strong technical background in areas such as Technical Product Ownership, Solution Architecture, or AI/ML.
Hands-on experience with LLMs, agentic workflows, tool calling, APIs, orchestration, and platforms (e.g., Anthropic Claude, OpenAI, Microsoft Copilot).
Ability to navigate the evolving agentic AI ecosystem and evaluate emerging models, frameworks, platforms, protocols, and tools.
Strong technical understanding of AI application architecture, complex systems, and technical trade-offs, with the ability to prototype and experiment independently.
Proven ability to operate effectively in a fast-moving, ambiguous, and rapidly evolving environment.
Proven ability to collaborate effectively across Product, Engineering, AI/ML, Design, and customer-facing teams.
Excellent written, verbal, and presentation skills.
BSc in Computer Science, Engineering, or a related technical field.
Advantages:

Experience working with large enterprise customers and understanding their security, privacy, governance, and compliance requirements.

Requirements:
4+ years in product role in cybersecurity.
Real depth with data. Either discipline: the building side (modeling, pipelines, warehousing, analytics) or the product side (owning a data platform, defining schemas, shaping what a data layer exposes). What matters is that you've worked with data as a system, not as a dashboard.
You turn data into value. You look at a schema and see what it unlocks - which questions become answerable, which decisions become automatable. You're not satisfied with a correct model that nobody can use.
You're comfortable in the details. You're able to understand entity relationships decisions engineers make , sit in integration design reviews, and write requirements precise enough to build from.
Nice to Have:
Background in IAM, IGA, or PAM - you know what an entitlement, a group, and a joiner-mover-leaver process actually are
Product management experience, especially owning a platform or infrastructure component that other teams build on
Experience with agentic AI or LLM-based systems - particularly how context and knowledge get structured for a model to act on reliably
Experience working with customer-facing or POC teams, turning field signal into roadmap.

Requirements:
5+ years of experience as a Product Manager, including leading technical products in SaaS, developer tools, platforms or AI.
A strong technical background: a degree in Computer Science or Engineering, or previous experience as a developer. You understand APIs, data models, backend systems and how modern web apps are built.
Proven experience owning a product end to end, from idea to launch to growing it over time.
Hands-on experience with AI products, LLMs or agent-based systems, and a strong intuition for what makes them work well for users.
Strong analytical skills and a data-driven approach to decisions.
Excellent communication skills, with the ability to align engineering, design and business teams around a clear product vision.
A builder mindset: high ownership, a bias for action, and comfort with the speed and ambiguity of a startup.
Advantages: experience with AI coding tools, developer platforms, PLG products or no-code/low-code tools; hands-on coding experience.

Requirements:
what we're looking for
product
4+ years of product management experience, with a strong preference for hands-on experience building 01 products in ai, automation, b2b saas, or other technically complex environments.
strong product management experience with a proven ability to take ambiguous problems and turn them into working solutions.
excellent product sense and ability to simplify complex workflows.
strong discovery skills and curiosity about how businesses actually operate.
comfortable owning problems rather than receiving predefined requirements.
ai & technical
ai-native: you actively use modern ai tools as part of how you work.
strong understanding of llm-based products, agents, apis, automation, data, and modern ai capabilities and limitations.
able to prototype independently using ai-assisted development tools.
comfortable discussing architecture and technical tradeoffs with engineers without necessarily being an ml engineer.
experience building ai-powered products, agents, automations, or internal tools is a significant advantage.
business
strong business orientation, you naturally think about roi and measurable outcomes.
ability to understand complex business processes quickly.
comfortable working across multiple departments and stakeholder groups.
excellent communication and stakeholder-management skills.
able to operate effectively in environments where the problem and solution are initially unclear.
the mindset we're looking for
you hear: this process takes our team 30 minutes per customer.
and your instinct is not: let's write a prd.
it's:
why does this process exist? which decisions are being made? what data do we have? what could an agent do? what still requires a human? can i prototype this this week? and how would we measure whether it's better?
we're looking for a builder, problem solver, and product thinker who wants to help define how an ai-native company should operate.
we will handle your application and information related to your application in accordance with the applicant privacy policy available here.

Requirements:
What you'll bring
Detection engineering depth: 5+ years in detection engineering or security engineering, with detections you personally wrote, tested, tuned, and maintained in production.
SecOps stack fluency: Hands-on experience with SIEM, SOAR, security data pipelines, or security data lakes, including the query languages and data source configuration work that comes with them.
Content and automation experience: Comfortable building detection content, wiring up data sources, and building automated response workflows - and opinionated about where each one breaks.
Product instinct, not necessarily a product title: You can get from "this is broken" to a clear, buildable spec without being handed a template. Prior Product Manager or Technical Product Manager experience is a strong plus.
Communication that lands both ways: You can hold a deeply technical conversation with a SecOps engineer and a clear one with a security leader. Experience working directly with customers or external security teams is a strong advantage.
Curiosity about AI in the loop: Interested in how AI and ML change detection and monitoring, and willing to reason carefully about what an agent should and shouldn't be trusted to do inside a customer's security environment.
0-to-1 judgment: Comfortable in an early-stage environment with an emerging category, limited existing structure, and a high bar for ownership.

Requirements:
3+ years of product management experience building B2B enterprise software, including substantial experience in data security, DSPM, or security-focused data governance.
A proven track record of delivering products in this domain, with examples of capabilities you owned, customer adoption, and the impact they achieved.
A strong understanding of sensitive-data discovery and classification, data exposure, permissions and access controls, and security or governance policies.
Technical fluency in cloud and enterprise data environments, with the ability to discuss architecture, integrations, and technical tradeoffs confidently with engineering teams.
Strong customer discovery skills and the ability to turn complex, sometimes conflicting needs into a clear product direction.
Experience owning a product area from strategy through launch and iteration, balancing long-term ambition with focused delivery.
Clear communication and the ability to align teams, influence decisions, and explain complex ideas to different audiences.
Curiosity, initiative, and sound judgment when working through ambiguity.
Experience that would be a plus:
Data lineage, catalogs, retention, residency, or compliance and audit workflows.
DLP, database security, identity and permissions, or automated remediation.
Products spanning cloud, SaaS, and on-premises data environments.
Securing data used by AI applications, copilots, or agents.
Working directly with enterprise security leaders, data owners, and governance teams.

Requirements:
6+ years of product management experience in B2B SaaS or platform-oriented environments
Experience working on AI-powered products, preferably including GenAI
Good technical understanding and ability to work closely with engineers on complex systems
Familiarity with concepts such as LLMs, retrieval, or data-driven systems (hands-on experience is a plus)
Strong product thinking, ability to balance user needs, business goals, and technical constraints
Experience working with data, metrics, and experimentation
Ability to work across teams and drive alignment in ambiguous environments
Strong communication skills and ability to clearly articulate product decisions
Strong advantage
Experience building platform products, APIs, or internal tools
Familiarity with AI evaluation, monitoring, or experimentation frameworks
Background in technical roles (engineering, data, etc.)
Experience in domains requiring high trust and reliability (e.g., HR, finance, security)
How to evaluate if this role fits you
You might be a strong fit if:
You enjoy working on systems and platforms, not only end-user features
You are curious about how AI systems work under the hood and want to deepen that understanding
You are comfortable collaborating closely with engineers and learning technical concepts
You like solving problems that impact multiple teams and products
This role can fit candidates coming from different backgrounds, what matters most is your ability to grow into the space, take ownership, and contribute to building a scalable AI platform.