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At our company, we move fast. Were an ultra-collaborative company with brilliant people who care deeply about the details. Together, were solving interesting and complex puzzles to keep the worlds data safe.
We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.
Responsibilities
Design and Build ML Infrastructure: Develop and maintain scalable, production-ready infrastructure for both traditional ML (anomaly detection, user behavior analytics) and LLMs across enterprise environments.
Optimize Model Performance: Analyze and optimize LLM and ML performance using techniques like knowledge distillation, quantization, and efficient data structures to boost efficiency and lower resource costs.
Deploy and Integrate: Collaborate heavily with software and data engineers to integrate models into production pipelines, cloud-native environments, and on-premises workflows.
Drive MLOps & Tooling: Manage the complete model lifecycle (monitoring, retraining, deployment) and actively build custom tools from scratch to improve the team's ML workflows.
Elevate Engineering Standards: Perform rigorous code reviews, ensure robust Python production standards, and provide technical guidance to data scientists and junior engineers.
Cross-Functional Partnership: Partner with cybersecurity researchers and product teams to translate research insights and threat analysis features into highly performant production code.
Open-Source Engagement: Actively engage with the open-source community by contributing code and expertise to relevant ML/LLM projects.

At our company, we move fast. Were an ultra-collaborative company with brilliant people who care deeply about the details. Together, were solving interesting and complex puzzles to keep the worlds data safe.
We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.
Responsibilities:
Own and operate the company authentication platform and internal IdP (token issuance, rotation, validation).
Build and maintain the NuGet packages for token validation and service-to-service communication used across all services.
Manage API gateway policies (routing, auth, rate limits, mTLS, observability).
Define and enforce RBAC across services (roles, permissions, policy evaluation, audits).
Continuously improve reliability, performance, and developer experience through automation, documentation, and support.

we are looking for a Senior Talent Acquisition Partner.
On your day to day:
As a Talent Acquisition Partner, you will be responsible for E2E recruitment for a variety of positions, including finding, attracting, interviewing and hiring top talent. You will partner with managers of all levels, including C-level, and have a complete ownership of the recruitment pipeline, funnel and process.

At our company, we move fast. Were an ultra-collaborative company with brilliant people who care deeply about the details. Together, were solving interesting and complex puzzles to keep the worlds data safe.
We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.
Responsibilities:
Define the product roadmap needs into detailed requirements, work with R&D teams and manage the entire development process from concept to launch.
Serve as an in-house subject matter expert of our company platform and become the go-to person in your domain.
Work closely with engineering teams to ensure high-quality deliverables.
Manage strategic relationships with new and existing partners.

Required Sustain Mechanical Engineer
- Full technical ownership of assigned product lines across their lifecycle, serving as the senior engineering authority for sustaining activities
- Lead mechanical design changes in multidisciplinary products to improve quality, reliability, manufacturability, serviceability, and customer experience
- Drive cost-reduction initiatives (VAVE / Cost Down) through redesign of mechanical and electromechanical assemblies, materials, and manufacturing processes
- Lead root cause analysis (RCA) and implement corrective and preventive actions (CAPA) for field failures and production issues
- Provide ongoing engineering support to manufacturing and suppliers, including design optimization, tooling development, and first article inspections (FAI).

The Product is where we dream big and at the same time question how things have been done for decades in a highly competitive landscape. Everything - under the hood and all the way to the shiny exterior - must adhere to the highest standards. Theres simply no other way about it. Its the mentality that got us to where we are today and will continue to lead the way for anything we do.
On your day to day:
As a PM, you'll stay laser-focused on users, uncovering deep insights through qualitative discovery and user interviews to solve real problems. You'll empower engineers and designers as equals, fostering a self-managing team that collaborates effectively and drives meaningful impact

Were looking for a strategic and experienced product leader to drive our data classification and privacy portfolio-one of the most foundational parts of our platform and a critical area of investment and innovation. This role is responsible for building advanced, scalable solutions that help our customers identify, categorize, and govern sensitive data across SaaS, IaaS, and on-prem environments.
You will lead a talented team of product managers and work closely with engineering, design, marketing, and sales to ensure our classification and privacy products continue to set the industry standard. Youll work in a hybrid model, and help shape the future of the company platform.
Responsibilities
Lead the strategy, vision, and execution for our companys classification and privacy products portfolio
Manage and grow a team of experienced product managers across multiple product lines
Define and own the roadmap for sensitive data discovery, classification, labeling, and privacy-aware controls across cloud and on-premises environments
Deeply understand customer use cases for compliance (e.g., GDPR, CCPA, HIPAA), data governance, insider threat protection, and data loss prevention
Drive innovations in content-aware and context-aware classification, including AI-driven techniques such as ML, NLP, and LLM-based models to accurately identify and categorize sensitive data
Evaluate and incorporate emerging technologies (e.g., generative AI and large language models) to enhance classification accuracy, scalability, and real-time data understanding
Work hands-on with UX designers, engineering, and research teams to design thoughtful, scalable solutions
Partner with internal stakeholders including Customer Success, Sales Engineering, and Professional Services to understand deployment challenges and inform roadmap priorities
Engage regularly with customers and prospects to gather feedback and validate product direction
Collaborate with marketing and sales teams to position, launch, and drive adoption of new features and products
Track and analyze product usage, customer feedback, and market trends to iterate on product strategy
Serve as a subject matter expert and thought leader both inside and outside the organization on data classification and privacy topics.

we are looking for a Senior Product Designer.
On your day-to-day, you will-
Take Product design ownership overall platform areas (Dashboard, Studio, Editor, and mobile app)
Collaborate closely with the product, engineering, and design teams in order to define, design, and deliver intuitive UI/UX solutions.
Create wireframes, storyboards, user flows, process flows, high-end designs and prototypes to effectively communicate interaction and design ideas.
Working with usability testing and data analysis in order to reach Intelligent UX solutions.

We are looking for a brilliant and highly motivated Full Stack Engineer who is passionate about technology and eager to make an impact. In this role, you will work on our web applications, contributing to both backend services and frontend applications to ensure seamless performance and scalability. You will be responsible for designing and implementing new APIs, optimizing existing systems, and building high-quality, maintainable solutions that enhance the overall user experience.
What will your day to day look like:
Full-Stack Development: Build and deploy frontend and backend code that supports growth initiatives, ensuring scalability and performance.
Rapid Prototyping: Quickly turn ideas into MVPs for testing and validation, using an agile and iterative approach.
Data-Driven Decision Making: Work closely with analytics tools to gather insights, track KPIs, and make informed decisions that fuel growth.
Collaborate with Cross-Functional Teams: Partner with marketing, product, design, and data teams to identify opportunities and run experiments.
Contribute to the Growth Strategy: Bring your technical expertise and creativity to brainstorm and prioritize growth opportunities that align with business goals.

We are looking for a Knowledge & AI Enablement Manager with proven experience in Knowledge Management and AI driven systems to design, build, and own the complete Knowledge Lifecycle for Technical Support.
This role defines how operational knowledge is created, governed, maintained, and embedded into daily Support workflows, while ensuring it is AI ready and serves as a trusted, high quality input for AI models across the organization.
Key Responsibilities:
Knowledge Lifecycle Ownership:
Own and build the end-to-end Knowledge Lifecycle for Support, from case-driven knowledge creation through continuous improvement and reuse
Define how knowledge is captured from cases, incidents, and escalations and transformed into structured, reusable, high-impact assets
Establish governance models for knowledge quality, validation, ownership, versioning, and ongoing maintenance
Design and operationalize workflows that embed knowledge creation, review, and updates into daily Support activitie
Define and implement a RACI model for knowledge creation, review, approval, and maintenance
Knowledge and AI Readiness:
Own KM platform configuration, Search and analytics tooling, taxonomy, publishing workflows, and integration with case management and AI retrieval pipelines
Define and enforce standards that ensure Support knowledge is structured, tagged, and maintained to be fully consumable by AI systems such as LLMs, RAG pipelines, semantic search, automation, and recommendation engines
Partner closely with Data, AI, and Engineering teams to align knowledge models, structure, and lifecycle with AI consumption requirements and future AI roadmaps
Act as the primary owner of the Support knowledge layer that feeds AI, ensuring consistency, reliability, and scalability
Measurement, Feedback, and Adoption
Define, track, and continuously improve KPIs including knowledge coverage, freshness, reuse, case deflection, and measurable AI performance impact
Establish feedback loops that surface insights from AI usage and knowledge gaps back to Support Engineers, driving better case handling and higher quality knowledge creation
Lead change management initiatives to drive adoption, accountability, and consistent knowledge behaviors across global Support teams.