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Requirements:
What We're Looking For:
3+ years of software engineering experience with backend systems.
Strong proficiency in Python, TypeScript/Node.js, or Go.
Experience with JSON-RPC, WebSockets, and real-time communication protocols.
Knowledge of RESTful API design and implementation.
Familiarity with database systems (SQL and NoSQL).
Understanding of authentication protocols (OAuth, JWT, API keys).
Experience with Model Context Protocol development or similar AI integration protocols.
Understanding of AI model context management and data retrieval patterns.
Knowledge of tool calling and function execution in AI systems.
Familiarity with prompt engineering and context optimization.
Military tech background (e.g., 8200, Mamram)- an advantage.
English proficiency- required.

Nice to Have:
Experience working with large language models and AI applications.
Background in distributed systems and microservices architecture.
Knowledge of streaming data processing and real-time analytics.
Experience with AI development frameworks (LangChain, LlamaIndex, etc.).
Contributions to open-source MCP projects or similar protocols.
Understanding of enterprise security and compliance requirements (SOC2, GDPR, HIPAA).

Requirements:
5+ years of product management experience, with ownership of complex, cross-functional product areas.
Proven experience building products in marketplaces, e-commerce, supply-chain-adjacent, or operationally complex domains.
Strong product instincts combined with analytical rigor and comfort working with data.
Demonstrated experience (or strong intuition) for applying generative AI to real-world product problems.
Excellent communication skills in Hebrew and English, with the ability to influence and align diverse stakeholders.
Comfortable operating as a senior IC: setting direction independently, going deep into details, and owning outcomes.
Technical fluency and strong collaboration skills with engineering and data teams.

Requirements:
5+ years of product management experience, with a meaningful portion in developer tools, API platforms, or search and retrieval infrastructure.
Track record of shipping products in fast-moving markets, working closely with engineering and design from concept through launch and iteration.
Strong understanding of LLMs, AI agents, and how search and retrieval systems fit into agentic workflows. Hands-on technical background is a strong plus.
Degree in computer science, engineering, or a related field, with the ability to engage deeply with technical architecture and tradeoffs.
Comfortable operating in ambiguity: you can context-switch between strategic thinking and tactical execution without losing the thread.
Proven ability to influence cross-functional stakeholders and drive alignment without formal authority.
Excellent written and verbal communication: you can explain technical concepts clearly to both engineers and business stakeholders.

Requirements:
~1+ year experience with Generative AI / LLMs
5+ years experience with Backend engineering
Experience shipping GenAI features to production
Strong hands on, production grade backend/software engineering skills (Python preferred)
Experience with major AI providers (OpenAI, Anthropic, Google)
Prompt engineering and LLM behavior knowledge
Understanding Agents / multi-step workflows
Experience with AI frameworks (LangChain, LangGraph, etc.)
Familiarity with embeddings / vector databases
Excellent problem-solving skills with demonstrated success in fast-paced environments.
Bonus:
MLOps / model deployment experience
Evaluation, monitoring, and guardrails
Fine-tuning or model customization
RAG systems (Retrieval-Augmented Generation)
Building retrieval pipelines and grounding LLM outputs

Requirements:
5+ years of backend development experience, ideally building scalable and distributed systems.
Deep expertise in Python and modern cloud-native architectures.
Proven experience with AI-enhanced systems - integrating or working with LLMs, RAG, or machine learning pipelines.
Understanding of data-intensive architectures, including streaming, caching, and dataflow optimization.
Strong collaboration and communication skills, with the ability to translate AI concepts into production-grade systems.
Advantage: Familiarity with vector databases, prompt engineering, and evaluation frameworks for AI models.
Advantage: Background in cybersecurity, runtime analysis, or agentic AI design patterns.

Requirements:
2+ years of ML engineering or applied ML research
Deep familiarity with HuggingFace transformers
Experience running inference servers (vLLM, TGI, or Triton)
Python and CUDA fundamentals
Understanding of quantization (AWQ, GPTQ, GGUF)
Bonus: GRPO/RLHF/DPO training, GPU workloads on Kubernetes

Requirements:
8+ years of product management experience
Proven track record of building 0-to-1 products - from idea to launch to scale
Deep B2C background - you understand consumer behavior, retention, and what it takes to earn a user's habit
Experience working in or alongside high-performing teams where the bar was high and the pace was real
AI-driven, passionate about leveraging AI tools and technologies to build smarter, more efficient user experiences.

Requirements:
Minimum of 8 years of experience designing and developing scalable, distributed backend systems in one or more modern programming languages (Python is a plus).
Deep expertise in Python concurrency and execution models (WSGI, ASGI, asyncio, multiprocessing, threading, GIL).
Proven track record building production-ready asynchronous Python applications serving high-volume traffic.
Strong experience with Pydantic and FastAPI in production environments.
Expertise in designing and implementing RESTful APIs and gRPC services with strong emphasis on versioning strategies and backward/forward compatibility.
Demonstrated ability to solve complex performance, scalability, and workload distribution challenges.
Proficiency with relational and non-relational database solutions (PostgreSQL, Redis, DynamoDB, MongoDB), including query optimization and data modeling.
Experience with event-driven architectures and message queuing systems (Kafka, RabbitMQ, AWS SQS).
Hands-on experience with Docker, understanding of CI/CD pipelines and methodologies, and working in Kubernetes/AWS-based deployments.
Strong proficiency with AWS cloud services and cloud-native architectures.
Understanding of observability practices (distributed tracing, metrics, logging) and experience with monitoring tools.

Requirements:
At least 5 years of experience working within research teams, with a focus on at least one of the following: web data extraction, reverse engineering, or browser technologies.
Strong analytical and problem-solving skills, with keen attention to detail and a passion for pushing the boundaries of whats possible in web data gathering.
Strong JavaScript skills with hands-on reverse-engineering experience in web contexts.
Advantages:
Hands-on experience with dynamic instrumentation and reverse engineering tools such as Frida, IDA Pro, Ghidra, or Radare2 / Cutter.
Experience with browser automation frameworks (Puppeteer, Playwright, CDP) and/or anti-scraping / bot-detection mechanisms.
Familiarity with web-focused IDEs and debugging environments (e.g., Chrome DevTools Protocol, Charles Proxy, Fiddler, Burp Suite, VS Code, WebStorm).
Prior work with Chromium or Firefox source code.

Requirements:
3-5 years of experience in a performance creative, creative strategy, or ad-creative role within digital advertising.
Strong understanding of global digital media buying, ad platforms (TikTok, FB, Instagram, YouTube, LinkedIn), landing page performance, and content marketing.
Demonstrated success in using data and testing frameworks to drive creative decisions.
Familiarity with user acquisition funnel strategies, especially for in-house growth teams.
Experience working with or implementing generative AI tools in creative workflows.
Ability to manage multiple, complex tasks simultaneously in a global, high-pressure environment.
Excellent presentation and communication skills for sharing insights with internal stakeholders and clients.
Fluent in English - verbal and written communication.

Requirements:
We're not looking for a process operator. We're looking for a commercial product leader who happens to love fintech - operating at the exceeding-the-standard bar from day one:
Ownership & agency. You own outcomes end to end - including the decision to continue, scale, reshape, or stop. You set the decision framework (problem, success, assumptions, tradeoffs, kill-signals) before work starts and keep the team honest against it. You don't wait for someone to tell you how the work will be judged.
Operates in ambiguity. When the problem isn't defined, you make assumptions explicit, pressure-test them fast, and move. A fast, imperfect call beats waiting for perfect analysis - and you know the blast radius.
Judgment & taste. You bring a clear point of view, synthesize inputs into a defensible recommendation, and don't default to the average of what stakeholders said. You can name weak logic and a solution that isn't good enough yet - including in others' work.
Commercial instincts. You think in pricing, margin, take-rate, unit economics, and vendor cost. You can read a P&L and a contract and tell us what's hiding in it.
Show, don't tell. You'd rather put a model, prototype, or one-pager in front of the team than run another meeting.
AI-driven velocity. You build tools, prompts, and workflows that embed your thinking so the team moves without waiting on you. The bottleneck isn't you - that's the point.
Customer obsessed. You're in our members' businesses regularly. You can tell a real pattern from a loud opinion.
High ownership, low ego. You see a fire, you put it out, even if it's not "yours."
Experience:
8+ years of product management experience
Deep domain in payments, fintech, or B2B financial products - you've shipped against Stripe / Adyen / Square / Plaid / a BaaS platform / lending infra.
Track record of building 0-to-1 and scaling live products to find PMF.
Comfortable as the named executive counterpart to vendor and partner leadership.
US ↔ international expansion (UK/EU/AU) in payments.
Experience with regulatory and fraud challenges.