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Were looking for a Senior Frontend Engineer to shape how our product empowers security teams - how it feels, performs, and drives action. Youll own key parts of our frontend stack, define how we build across teams, and turn complex security data into clear business insights.

What Youll Do
Champion Development Best Practices: Influence architectural and technical standards across the frontend stack.
Lead Projects: Own and drive the development of key UI components and cross-functional features, working across teams and domains.
Innovate: Bring new ideas to the table -whether its in UX, UI, architecture, usage insights, and more.
Collaborate Cross-Functionally: Partner with Product, Design, Backend, and Data teams to implement experiences that are beautiful, fast, and secure.
Optimize for Performance & Usability: Build responsive, accessible, and production-ready interfaces that scale.

Were looking for a Senior MLOps Engineer to be a core driver in how our product empowers security teams. You will be expected to deeply understand customer needs and translate them directly into product features that deliver real value. You'll own key parts of our frontend stack, drive key architectural decisions, and turn complex security data into clear, actionable business insights.

As we scale our AIDR product and expand deeper into model-driven security intelligence, we are looking for a Senior MLOps Engineer to own the infrastructure, tooling, and operational foundations that power our NLP and LLM training, evaluation, and deployment workflows.

You will architect and operate the systems that enable us to train, fine-tune, deploy, and monitor models at scale making our ML reliable, fast, cost-efficient, and production-ready.

This is a high-visibility, high-impact role where you will partner closely with DevOps, Backend, Data, and Product to establish world-class ML infrastructure from the ground up.

What Youll Do
Build & Scale ML Pipelines
Design, build, and maintain pipelines for training, fine-tuning, evaluating, and deploying NLP and LLM models across GPU and CPU environments.
Establish LLM-Focused CI/CD
Implement automated CI/CD workflows for ML models, including benchmarking, testing, performance gating, and production deployment.
Optimize Runtime & Inference
Select and optimize serving frameworks for low-latency, high-throughput inference, ensuring reliability and scalability.
Own ML Infrastructure
Manage training environments, experiment tracking, model registries, artifact versioning, and distributed training systems.
Operational Excellence
Monitor and optimize production models for performance, cost efficiency, availability, and observability.

As Security Research Team Lead at our company, you will lead the team turning security research and enterprise security data into actionable insights and product capabilities. You will combine people management with hands-on technical leadership, helping customers understand their exposure and get more value from their security tools.
Were looking for a leader with a strong background in cybersecurity research, deep understanding of enterprise security tools, and a data-driven approach to solving problems. You should be equally comfortable mentoring researchers, shaping a research roadmap, and joining customer calls to explain findings and understand real-world challenges.
What You'll Do
Lead and Develop the Team: Manage, mentor, and grow a team of security researchers. Set clear goals, provide technical guidance and feedback, and build a culture of rigor, curiosity, and ownership.
Own the Research Roadmap: Define and prioritize research initiatives in partnership with product and engineering. Balance customer needs, emerging threats, and strategic opportunities, taking projects from initial investigation through production delivery.
Drive Security Tool Research: Lead deep research into enterprise security platforms, including EDR, SIEM, firewalls, IAM, and vulnerability management tools. Assess configurations, policies, coverage, and defensive capabilities to identify gaps and improve security effectiveness.
Engage Directly with Customers: Lead technical customer discussions, explain findings clearly, investigate complex questions, and turn feedback into research and product improvements.
Turn Data into Security Insights: Guide how the team collects, models, correlates, and validates security data. Translate fragmented telemetry and configuration data into reliable assessments, prioritized findings, and actionable recommendations.
Shape Integrations and Product Capabilities: Own the research requirements and security logic behind integrations, security control assessments, and exposure prioritization. Work closely with engineering to ensure research translates into accurate, scalable product features.
Set Research Quality Standards: Establish methods for validating findings, testing assumptions, and measuring accuracy. Ensure conclusions are supported by evidence and recommendations account for customer context and operational constraints.
Guide AI-Powered Research and Workflows: Shape the security knowledge, reasoning logic, and evaluation methods behind our companys AI-powered capabilities, ensuring outputs are accurate, explainable, and useful.
Partner Across our company: Collaborate with product, engineering, data, and customer-facing teams to align priorities, resolve technical challenges, and deliver meaningful customer outcomes.

AI moved attackers faster than human-paced defense cycles can absorb, and pushed exposure data past what any team can triage by hand. Our platform runs AI agents that investigate on their own, verify whether existing controls neutralize the risk, and return a validated case with root cause, owner and remediation. How those agents earn a security team's trust - what they decide alone, what they escalate, what evidence they show - is unsettled across the industry, and what gets built now sets the pattern.
Security teams own thirty tools and still can't say which threats those tools actually stop. our company answers that question. We connect read-only to the stack a company already runs - CrowdStrike, Microsoft, Okta, Qualys, 40+ more - and build a live model of what's exploitable, what's already covered, and what to fix first.
As the Product Manager, you'll own a key domain of the platform end-to-end: vision, strategy, roadmap, specs, delivery, adoption. Direct work with CISOs, detection engineers and SOC teams, and what you decide from those conversations ships. Reports to the VP Product.
Responsibilities:
Set the strategy and roadmap for your domain, and own what it delivers. You decide what gets built, what waits, and what we drop.
Spend real time with customers and prospects. Sit in their environment, watch how their team works, find the problem behind the request.
Write the specs and work with engineering and design through delivery. Stay in it until it ships and people use it.
Build the narrative for what you ship - the value story a CISO repeats to their board, not a feature list. Sales, marketing and CS should be able to sell it from your words.
Bring your product to market with sales and marketing, then track adoption and come back with the next round of decisions.
Watch the market: competitors, new threats, how CTEM and agentic security keep shifting. Turn that into where we go next.

As a Senior Security Researcher, you will bridge our core research initiatives at the intersection of proactive exposure management, agentic workflows, and scalable threat modeling. We are looking for an innovator who translates complex security data into product-driven features, taking full ownership from concept to production.
What You'll Do
Drive Product-Led Research: Translate complex, real-world security challenges into actionable, product-driven research. Take full ownership of research projects end-to-end, from identifying the security gap to collaborating with engineering to ship platform features.
Drive Proactive Exposure Management: Leverage Automated Security Control Assessments (ASCA) alongside vulnerability evaluation and prioritization to holistically assess organizational risk. Deep dive into enterprise security tools (EDR, SIEM, Firewalls, IAM, etc.) to analyze configurations, map defensive capabilities, and continuously evaluate their effectiveness against real-world threats.
Build Security Tool Integrations: Drive the technical research and define the data models required to actually build deep, functional integrations into diverse security platforms, ensuring the accurate extraction of telemetry, policies, and configuration data.
Build AI & Agentic Workflows: Define, design, and implement the logic and knowledge base that feeds our company's AI-powered agents, ensuring they deliver accurate, context-aware security guidance and automated risk assessments.
Map Attack Paths: Define realistic attack flows, identify toxic combinations of misconfigurations, and surface the security gaps that help customers prioritize the risks that actually matter.
Engage with Customers: Work directly with customers to help them understand their exposure, translate your research findings into meaningful posture improvements, and gather feedback to drive product innovation.
Cross-Functional Collaboration: Partner closely with product, engineering, and data teams to embed security insights into everything we build.

We are looking for a Growth Marketing Lead who wants to build, not maintain.
Someone who sees demand generation as more than channels and metrics, and who will build our entire marketing program with AI at its core. This is not about using AI as a side tool. It is about designing how we generate demand, create content, reach buyers, and measure impact around what AI makes possible today.
You will shape how our company shows up, how we break through, and how we convert momentum into revenue.
What You'll Drive
Build an AI-Native Marketing Engine - Design programs, workflows, and team practices where AI is central to how we plan, create, and scale
Create Pipeline That Matters - Build integrated campaigns that generate real pipeline and accelerate deals, not just activity
Bring Big Ideas to Market - Turn bold messaging into campaigns people notice, remember, and act on
Own the Full Funnel - From first impression to closed deal, influence how prospects move and why they convert
Connect Teams and Execution - Work across product marketing, sales, SDRs, and field to keep everything in sync
Turn Insight into Action - Use data and AI to refine, improve, and scale what works, fast.

Required Technical Support Engineer Tier 3
As a Technical Support Engineer on our Tier 3 team, you'll work with some of the most advanced companies leveraging cutting-edge AI-driven systems to enhance business performance. Your role involves deep technical investigation, resolution of complex issues escalated by the Support team, and acting as the main technical liaison with R&D. You'll play a critical role in identifying recurring issues and driving continuous improvement initiatives in collaboration with R&D and Product Management through leveraging customer feedback and data across the Support team.
Youll Own:
Subject Matter Expertise: Serving as a dedicated subject matter expert (SME) for a specific product area and owning it end-to-end.
Escalation Management: Partnering with Tier 2 Support and Customer Success teams to prioritize escalations, communicate updates, and drive end-to-end resolution processes.
Team Enablement: Educating and upskilling Tier 2 teams by sharing insights, documenting learnings, and delivering trainings to bridge knowledge gaps and improve first-line resolution rates.
Support Tooling: Identifying gaps and advocating for, or creating troubleshooting tooling as needed, to better equip Support team members in identifying root causes faster and delivering more holistic resolutions as early as possible.
Youll Solve:
Complex Troubleshooting: Performing root cause analysis, troubleshooting, and resolving issues using a variety of tools, datasets, and cross-functional collaboration.
Recurring Technical Challenges: Aligning closely with R&D teams to communicate recurring technical themes and suggesting improvements.
Customer Obstacles: Reading and understanding code and writing occasional scripts to resolve complex customer issues.
Youll Impact:
Product Quality & Supportability: Collaborating with R&D and Product Management to provide solutions and workarounds, and to implement product features or support tools that ultimately reduce the need for customers to submit tickets.
Support Team Proficiency: Mentoring and enabling support teams to improve technical proficiency and resolution capabilities.