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Requirements:
4+ years of hands-on experience in reverse engineering, including both static and dynamic analysis.
2+ years of experience in vulnerability research, exploit development and bypassing OS-level mitigations.
Expert-level knowledge of Windows operating system internals and low-level OS research experience.
Experience in C/C++ development, including Win32 API.
Experience in a scripting language, with a preference for Python.
Ability to work independently and as a part of a team
Ability to work under pressure with strict deadlines, and to prioritize projects
Strong attention to detail.

Requirements:
6-10+ years of experience in Data Engineering, with demonstrated architectural ownership.
Expert-level experience with Snowflake (mandatory), including performance optimization, data modeling, security, and ecosystem components.
Expert proficiency in SQL and strong Python skills for pipeline development and automation.
Experience with modern orchestration tools (Airflow, Dagster, Prefect, or equivalent).
Strong understanding of ELT/ETL patterns, distributed processing, and data lifecycle management.
Familiarity with streaming/event technologies (Kafka, Kinesis, Pub/Sub, etc.).
Experience implementing data quality, observability, and lineage solutions.
Solid understanding of cloud infrastructure (AWS, GCP, or Azure).
Strong background in DataOps practices: CI/CD, testing, version control, automation.
Proven leadership in driving architectural direction and mentoring engineering teams
Nice to Have:
Experience with data governance or metadata management tools.
Hands-on experience with DBT, including modeling, testing, documentation, and advanced features.
Exposure to machine learning pipelines, feature stores, or MLOps.
Experience with Terraform, CloudFormation, or other IaC tools.
Background designing systems for high scale, security, or regulated environments.

Requirements:
In-depth knowledge of some operating system internals is a must - Knowledge of Linux is an advantage
Development experience in C/C++/Rust is a must, 3 years at least
Experience in security research - 3 years at least
Experience in reverse engineering - both static and dynamic, is a must (x86/64 architectures), 3 years at least
Development knowledge in some scripting languages is a must - Experience with Python is an advantage
Ability to work independently and as a part of a team
Strong attention to detail
Ability to take initiative
Preferred Qualifications
Exploitation experience is an advantage (either application-level security or memory corruption)
Familiarity with Kubernetes, containers, and cloud workload security.
Experience leading endpoint security projects across organizational boundaries and teams
Academic experience
Published security research, conference presentations, or CVEs.

Requirements:
Your Impact
Design and implement automated evaluation loops, static analysis, and rigorous quality gates to ensure the ADLC process doesn't just write code, but consistently produces great, production-ready code.
Help the team tackle complex, hard problems to elevate our autonomous development product from "good" to "excellent".
Lead complex initiatives in Context Engineering and Prompt Engineering.
Manage and orchestrate the complex ecosystem of autonomous agents utilized for internal development.
Serve as a leading individual in a very strong team professionally and personally - Were looking for someone who not only delivers his own work but improves that of those around them.
Find space for growth to push the entire team or group forward - New projects, changing processes or improving existing tools.
View prompt engineering as a core engineering discipline-where rewriting agent behavior is a versioned, reviewed, and tested code change.
Act with a debugging temperament; conduct deep-dive analyses of raw agent transcripts to diagnose non-deterministic failures and ascertain root causes instead of merely working around them.
Your Experience
At least 8+ years of experience in software development, architecture, or owning operational systems in production.
Computer Science B.Sc. or equivalent education or equivalent military experience required.
A product builder's mindset: you can extract requirements, talk to stakeholders, and tell the difference between what's important and what's noise.
Experience in building production grade agents. Deep understanding of the agent loop, its states and transitions. You know how to build it correctly, not just use it.
Positive can-do mindset, able to work independently and within a team.
Hands-on experience with LLM APIs, including a practical, highly-skeptical understanding of token costs, caching, context windows, and model failure points.
You know how to build the right context for a task, including memory systems, session storage, and vector databases.
You understand where LLMs fail and how to design around those failure points.
You've used traces or observability tooling to diagnose and improve agent behavior.
A systems-level background that touches reliability, observability, or platform engineering, with a strong preference for writing narrow, deterministic code over building hypothetical abstractions.
Experience in the cybersecurity space - an advantage.

Requirements:
7 - 10 years of experience in Cloud Infrastructure, DevOps, or SRE roles.
Strong hands-on experience with AWS, Azure, and/or GCP, especially in networking (VPC setup, VPNs, routing, firewall configurations).
Expertise in Terraform, Kubernetes, Helm, and scripting languages (Python or Bash).
Proven experience supporting live, production SaaS environments.
Solid understanding of cloud security concepts and practices.
Strong troubleshooting skills in distributed, cloud-based environments.
Excellent communication and collaboration skills.

Requirements:
Bachelor's degree or equivalent military experience.
At least 5 years of experience in Linux system-level programming.
Extensive knowledge of Linux internals, or Linux 'under the hood'.
Very strong system-programming skills in C++.
Strong debugging skills with various tools on different Linux platforms.
Proven experience with multi-threaded application development.
Preferred Qualifications
Linux kernel programming experience.
Experience with containers, Docker, or Kubernetes.
Familiarity with multiple Linux distributions (e.g., RHEL, Ubuntu).
Experience with software security and/or Linux Security modules (e.g., SecureBoot, SELinux, AppArmor).

Requirements:
Your Expereience:
Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent practical experience.
6+ years of Devops engineering experience on mission-critical, enterprise-level systems in a hybrid (both cloud and on-prem) environment.
3+ years of hands-on experience with cloud environments, preferably Google Cloud Platform (GCP).
Expertise in configuration management and Infrastructure-as-Code using frameworks such as Terraform and Ansible.
Strong programming/scripting knowledge in languages like Python, Bash, or Go for infrastructure automation.
Demonstrated experience with CI/CD pipelines (e.g., GitHub, Jenkins, Artifactory) and a strong foundation in Linux/Unix administration.
Preferred Qualifications
Experience with containerization and orchestration technologies, particularly Kubernetes.
Hands-on experience with monitoring and observability tools such as Datadog, Grafana, or Prometheus.
Understanding of networking principles including firewalls, load balancers, and complex network designs.
A curious and positive mindset with a passion for applied learning and challenging existing processes for continuous improvement.

Requirements:
Bachelors, Masters, or PhD in Computer Science, Engineering, Information Systems, or a closely related quantitative discipline.
Typically 15+ years of progressive experience in cloud, security, networking, or large‑scale distributed systems architecture.
Demonstrated experience leading architecture for complex, global, cloud‑native platforms with strong security and reliability requirements.
Experience driving or enabling AI/ML-based capabilities in large-scale platforms is highly desirable.
Knowledge and Skills:
Deep expertise in cloud‑native architecture, distributed systems, and platform‑scale software design.
Strong background in security and networking architectures, ideally including SASE, SSE, Zero Trust, identity, and policy‑driven systems.
Exceptional analytical and problem‑solving skills, with the ability to simplify complex systems and drive clear architectural decisions.
Proven ability to align technology strategy with business outcomes, financial considerations, and customer impact.
Track record of technical innovation, including patents, published designs, or successful large‑scale product deployments.
Outstanding communication skills, capable of influencing and aligning stakeholders at the executive and industry level.
Strong understanding of AI concepts, data pipelines, and automation techniques, with the ability to apply them pragmatically to real-world engineering and product challenges.

Requirements:
Your Experience:
Keeps up with the latest research and stays on top of the fast-moving AI space, with a real passion for whats happening in Generative AI.
Regularly tries out different AI tools and sees how theyre useful in everyday work and life.
Strong understanding of advanced prompting techniques like Chain-of-Thought, ReAct, and few-shot prompting.
Experience working on model quantization or finding ways to optimize inference costs and token usage at scale.
Hands-on experience with Python (FastAPI, Django, or Flask) or Go, with a solid grasp of async programming and microservices.
Experience turning a vague product idea (e.g., "let's add a smart assistant") into clear, concrete technical requirements.
Nice to have:
Hands-on experience using frameworks like LangChain to build more complex LLM flows and agents.
Experience working with vector databases.
Comfortable building and using RESTful and GraphQL APIs, especially when dealing with low-latency streaming (WebSockets, Server-Sent Events).
Enjoys digging into non-deterministic systems - when an LLM fails, comfortable figuring out whether its the prompt, the retrieval, or the data.
Familiar with AI-specific security risks, like prompt injection and data leakage.

Requirements:
Your Experience
6+ years of experience working as a Backend Developer.
3+ years of experience as a team lead.
Security knowledge (preferably code security)
Development experience in JS/TypeScript.
Live production systems with high-scale.
Experience with Kubernetes development.
Experience in the cloud (preferably GCP).
An Advantage:
Experience with GCP or any other cloud provider.
Bachelor's degree or equivalent military experience.

Requirements:
First-level university degree or equivalent experience; advanced university degree preferred.
Up to 5 years of related experience in tax.
Fluent in English.
Knowledge and Skills:
Thorough knowledge of professional accounting and financial reporting systems.
Advanced knowledge of the income tax laws as they relate to corporations.
Excellent communication, leadership, and influence skills.
Strong financial and business acumen.
Strong project management, problem solving, and analytical skills.
Knowledge of tax and accounting software desirable.
Expertise in international tax desirable.

Requirements:
5+ years in product management, with a focus on cybersecurity/technical B2B SaaS products.
Proven track record to deliver features from inception to production.
Strong technical background in security, data and cloud technologies.
Experience working with AI/ML models and incorporating LLM-based features into customer-facing products.
Familiarity with MCP - A Plus.
Ability to successfully collaborate with cross functional teams, including highly technical engineering, research and UX/UI teams, fostering collective success.
Strong analytical and critical thinking abilities, facilitating effective decision-making, prioritization and planning.
Self-learner, curious and adaptable to complex and dynamic environments.
Positive and confident communicator, with excellent written and verbal communication skills in English.
Comfortable engaging with and presenting to diverse stakeholders.
Self-motivated with a proactive approach to problem-solving and task management.

Requirements:
Bachelors degree in Computer Engineering, Electronics, or Electrical Engineering.
Masters or PhD in a relevant domain is highly desirable.
10+ years of experience in product R&D within the computer/system software industry, focusing on kernel and driver development.
Knowledge and Skills:
In-depth working knowledge and Hands-on experience in I/O subsystems, programming, and kernel development.
Expertise in C and C++ programming languages.
Strong understanding of operating system internals and kernel & driver internals, including memory management, threading, and resource scheduling.
Proven expertise in debugging, kernel triaging, and resolving memory and performance-related issues.
Proficient in performance profiling, multithreading, and driver programming.
Strong Knowledge in Linux and virtualization technologies such as VMware, Hyper-v and KVM.
Ability to Design and implement scalable, efficient solutions for complex datapath and kernel challenges.
Strong ability to innovate and bring fresh approaches to technical challenges.
Excellent problem-solving skills with a proactive mindset and sharp analytical abilities.
Exceptional communication skills to effectively present and discuss technical designs, proposals, and solutions with senior management and stakeholders.
Demonstrated technical leadership with a focus on driving innovation.

Requirements:
Bachelor's or master's degree in computer science, engineering, information systems, or closely related quantitative discipline.
Typically, 7-10 years experience.
Knowledge and Skills:
Strong programming skills in Python, Java, Golang, or JavaScript.
Understanding microservice architecture and how they can be built in a containerized, Kubernetes-managed environment is central to all modern cloud-native applications.
Designing and integrating software systems running on multiple platform types into the overall architecture.
Evaluating forms and processes for software systems testing and methodology, including writing and executing test plans, debugging, and testing scripts and tools.
Excellent written and verbal communication skills. Ability to effectively communicate product architectures and design proposals at senior management levels.

Requirements:
2-5+ years of experience as a Data Engineer or similar role.
Hands-on experience with Snowflake (mandatory)-including SQL, modeling, and basic optimization.
Experience with dbt (or similar)-model development, tests, documentation, and version control workflows.
Strong SQL skills for data modeling and analysis.
Proficiency with Python for pipeline development and automation.
Experience working with orchestration tools (Airflow, Dagster, Prefect, or equivalent).
Understanding of ETL/ELT design patterns, data lifecycle, and data modeling best practices.
Familiarity with cloud environments (AWS, GCP, or Azure).
Knowledge of data quality, observability, or monitoring concepts.
Good communication skills and the ability to collaborate with cross-functional teams.
Nice to Have:
Exposure to streaming/event technologies (Kafka, Kinesis, Pub/Sub).
Experience with data governance or cataloging tools.
Basic understanding of ML workflows or MLOps concepts.
Experience with infrastructure-as-code tools (Terraform, CloudFormation).
Familiarity with testing frameworks or data validation tools.