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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.

Requirements:
Requirements & Qualifications:

Leadership Experience: 2+ years of experience leading technical teams (architects, DevOps, or engineering squads), including mentoring, task prioritization, and delivery accountability - ideally in a professional services or consulting environment.

Communication & Presentation: Outstanding verbal and written communication skills in English & Hebrew. Proven ability to conduct discovery calls and articulate sophisticated technical concepts to both engineering teams and non-technical business executives, and to represent the company at a senior level.

Cloud Platform Expertise: 5+ years of proven experience architecting, deploying, and managing complex production workloads on Google Cloud Platform (GCP) and/or Amazon Web Services (AWS), with deep knowledge of their core services (compute, storage, networking, databases).

Core Technical Foundations: Strong foundational knowledge of operating systems (Linux/Windows), virtualization environments, database architectures (SQL/NoSQL), and proficiency in scripting languages (such as Python and Bash) for automation and troubleshooting.

Modernization & Serverless Mastery: Practical experience implementing containerized solutions (Docker, Kubernetes/GKE/EKS) and serverless technologies (Cloud Run, AWS Fargate, ECS, Lambda, Cloud Run Functions).

Hands-On DevOps & IaC: Strong, hands-on background in DevOps practices. Expert-level knowledge of Infrastructure as Code (IaC) tools - specifically Terraform - along with deep experience in CI/CD pipeline construction.

Migration Experience: Proven track record of guiding enterprise migrations (re-hosting, re-platforming, and refactoring), particularly On-Prem to Cloud or cloud-to-cloud migrations (such as AWS to GCP).

Client-Facing Professionalism: A consultative, customer-centric mindset with strong analytical, scoping, and problem-solving abilities, and the maturity to own decisions independently under broad executive guidance.

AI/ML Familiarity: An understanding of the modern AI landscape, with the ability to identify opportunities where Generative AI can drive value for clients.

Education: Bachelor degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).

Preferred Advantages
Multi-Cloud experience: Hands-on architectural and deployment experience with both GCP and AWS.
Prior experience as a Team Leader, Delivery Lead, or Principal Architect in a cloud consulting / MSP / professional services company.
One of the following Professional-level cloud certifications:
- Google Cloud Professional Cloud Architect
- AWS Certified Solutions Architect - Professional
Deep expertise in FinOps methodologies and cloud cost allocation tools.

Requirements:
Deep, hands-on WAF expertise across multiple major providers - you've written, tuned, and operated real rules in production on several of: AWS WAFv2, Cloudflare, F5, Imperva, Akamai, Azure, GCP, Fortinet, ModSecurity/CRS. Not "managed a WAF vendor relationship" - written the rules.
You know the caveats cold. Body-inspection limits and oversize handling, text transformations and normalization order, encoding and unicode evasion, parameter pollution, chunked and multipart edge cases, rule precedence and evaluation order, WCU/capacity economics, and how each provider's expression language quietly differs from the others.
Strong security research background - application security, vulnerability research, or offensive security. You can read an advisory, build the PoC, derive the variants nobody published, and explain exactly which request component carries the exploit primitive.
A real feel for the false-positive tradeoff. You've had to defend a blocking decision to someone whose production traffic you broke, and you know why "block everything suspicious" is not a security posture.
Comfortable in code. Enough Python (or similar) to automate replay, build variant generators, and query exploit and traffic data yourself rather than waiting on someone.
Fast under pressure, systematic afterward. You can get a solid rule out the door when a customer needs one today - and your instinct once it ships is to build the check that catches the whole class, not just the instance you fixed.
Advantage: virtual patching / vulnerability-mitigation experience, or time on a WAF vendor's rules or research team.
Advantage: hands-on with LLMs and agentic tooling - you'll be shaping an AI system's output, and it helps to understand how it fails.

Requirements:
Experience
6 years of B2B marketing experience in technology companies.
3+ years in a senior leadershiprole, reporting to a CEO
Proven hands-on ownership of campaigns, messaging, and pipeline metrics - not just oversight.
Demonstrated ownership of an annual marketing budget.
Track record of contributing materially to pipeline and revenue targets.
Domain and GTM Expertise
4+ years background in SaaS, software infrastructure, developer tools, cloud, open-source, or platform businesses.
Hands-on experience with B2B, PLG, and PLS motions.
Strong preference for candidates with an engineering background or significant experience at a company that sells to developers or technical buyers.
Experience marketing to enterprise buyers, technical decision-makers, and product companies.
Brand and Category Leadership
5+ years leading brand strategy, positioning, and narrative development.
Demonstrated experience in category creation or category leadership, including PR, analyst relations, and executive thought leadership.
Track record of building brand equity that measurably impacts pipeline, deal velocity, or win rates.
Demand Generation
3+ years owning demand generation in B2B environments.
Hands-on experience building and operating multiple demand engines (partners, field marketing, warm demand, organic, paid).
Proven ability to generate predictable, qualified pipeline and reduce dependency on founder-led or opportunistic sales.
Experience managing demand efficiency metrics (SQLs, CAC, payback, pipeline contribution).
Product Marketing
3+ years of product marketing experience in B2B technology companies.
3+ years of experience in PLG and PLS motions
Ownership of messaging, positioning, sales enablement, and proof assets - with ability to produce them directly.
Demonstrated impact on conversion rates, win rates, and pipeline velocity.
Experience translating complex technical products into clear, credible commercial value.
Leadership and Operating Skills
Strong strategic thinking combined with execution discipline and a bias for getting things done hands-on.
Comfortable being the most senior marketer in a growth-stage environment.
Native-level English required.
Experience working in a multicultural environment.

Requirements:
Strong technical background - degree or equivalent experience in Algorithms, Data Science, Machine Learning, Computer Science, or AI research - a must
experience in Algorithms, Data Science, Machine Learning or AI research
Sharp technical skills and the ability to engage substantively with researchers on model architectures, training, evaluation, and pipelines
Strong product mindset - relentlessly focused on the "why," with customers and business value at the center of every decision
Strong drive to learn, grow, and develop - autodidact mindset is essential
Product management experience is not required; technical depth, curiosity, customer obsession, and judgment matter more
Passion for the field of visual Generative AI - a big advantage
Strong visual creative skills and a sharp eye for visual quality - a big advantage
Proactive, independent, and motivated problem solver
Excellent communication and interpersonal abilities - comfortable translating complex AI concepts
Excellent organizational skills, attention to detail, and the ability to prioritize effectively
Comfort in a fast-paced, dynamic environment; adept at multitasking and meeting deadlines
Adaptability and flexibility
A team player with self-motivation and independence