דרושים » הנדסה » AI Research Engineer, Security

We're hiring a Senior Security Researcher to be the security authority behind our AI agents, and the person who decides what "good" means. As our agents take on more of the security workflow, the hardest question stops being "can we build it?" and becomes "is the agent actually right?" Answering that takes someone who understands how vulnerabilities are found, exploited, and remediated at a deep level, and who can turn that judgment into rigorous, repeatable benchmarks the whole team builds against. You'll own those benchmarks. You'll encode your security expertise directly into the agents - the guidelines, heuristics, and domain knowledge they reason with, and guide how they improve over time. You'll help us understand the real complexity behind the features we want to build, and break them into deliverable pieces. And you'll do it with a genuine appetite for experimental AI - comfortable getting your hands dirty with frontier models and agent tooling, not intimidated by it.
What you'll do:
Own our benchmarks and evaluations. Define what "correct" and "high quality" mean for AI agents that detect, prioritize, and remediate security issues. Build and maintain the benchmark datasets, scoring methods, and ground truth that the team measures itself against - and keep raising the bar.
Guide how our agents get better. Dig into where agents fail - false positives and negatives, bad or unsafe fixes, missed exploitability, wrong prioritization - and translate that into concrete improvements to prompts, tools, data, and agent design alongside engineers.
Be the security ground truth. Bring deep, hands-on AppSec judgment to bear on agent outputs: threat-model the edge cases, label the hard examples, and think adversarially about where an autonomous security agent could be confidently wrong.
Scope and decompose new features. Assess the security complexity and feasibility of new capabilities we want to build, explain the risks and trade-offs clearly, and help break ambiguous, research-heavy problems into small, shippable deliverables.
Be our early adopter of experimental AI. Stay on the frontier of models, agent techniques, and tooling. Test what's new, figure out what's real, and bring the useful parts back into the team.

We're looking for a Security Researcher to join our team at the intersection of security research, AI, and product. This isn't a traditional research role - you'll be deeply embedded in how the platform is built, working side by side with R&D, Product, and AI teams to make sure security expertise is baked into every layer of what we ship. You'll own detection and analytics research across cloud, identity, endpoint, and beyond, while actively shaping how AI capabilities are applied to solve real security problems at scale.





WHAT YOU WILL DO

Research and develop sophisticated detections and behavioral analytics across multiple security landscapes - cloud, identity, endpoint, network, and application - with a focus on coverage that scales across customer environments.
Work closely with R&D, Product, and AI teams as the security authority - reviewing features, shaping designs, and ensuring security logic is sound, practical, and impactful.
Apply an AI-native approach to detection and analytics challenges - leveraging LLMs, ML signals, and AI-assisted workflows to do things that rule-based approaches can't.
Identify gaps in detection coverage and analytical capabilities, and drive those findings directly into the product roadmap.
Analyze real-world attacker techniques and translate them into detection logic, hunting content, and analytical frameworks that ship as part of the platform.
Evaluate detection quality rigorously - measuring fidelity, coverage, and performance against real attacker behavior and production telemetry.
Stay sharp on the evolving threat landscape and rapidly incorporate new techniques, campaigns, and attacker tooling into our detection library.
Contribute to external research output - blog posts, talks, open-source tooling - that reflects our depth and point of view in the security community.

We're looking for a Senior Applied AI Scientist to sit at the frontier of AI security - turning emerging threats into the detection models that protect how AI is used inside the world's largest organizations. You'll be part of the AI Security Research department, working hand-in-hand with security researchers to translate threat intelligence into trainable signals that catch malicious behavior and security risks across the AI-powered workflows of Fortune 500 companies.
You'll bring deep technical versatility - reaching for classical ML, deep learning, or agentic based approaches based on what the problem demands, and the evaluation rigor to know when a model is truly ready for the real world. If you want to define what AI security engineering looks like, not just practice it, this role is for you.
What Youll Do:
Build, train, and ship detection models end-to-end, from raw data to production
Choose the right method for each problem - traditional ML, deep learning, fine-tuned LLMs, agents or heuristics - based on theoretical insights turned into practical results.
Partner with security researchers to turn security research outputs and domain expertise into detection capabilities
Own evaluation: design benchmarks, build labeled datasets, and define production standards
Monitor models in production across all paradigms - ML, deep learning, LLM-based, and agentic systems to track degradation and ensure reliability
Iterate fast, with a tight feedback loop between model performance and product outcomes

As a Security Researcher , you will play a key role in shaping the future of modern runtime and AI security. You will investigate how real-world attacks unfold across applications and cloud environments, and turn those insights into innovative, production-grade security capabilities.

This role is ideal for a deeply technical researcher who is driven to understand attacks at their core - not just identify surface-level indicators. You will research exploitation chains, runtime behavior, attacker techniques, and emerging AI attack patterns, then apply that knowledge to build protections that are precise, resilient, scalable, and grounded in how attacks actually work.

Specifically, you will:

Research real-world attack techniques targeting modern applications, cloud-native environments, and AI-driven systems.
Design, develop, validate, and deploy detection algorithms based on technical research, large-scale runtime telemetry, threat intelligence, and exploit PoCs.
Shape the strategy for detection data collection by defining the required telemetry, collection points, and data quality standards needed to support effective protection.
Drive research efforts end-to-end, from initial exploration and technical investigation to production-grade protection capabilities for active threats.
Work closely with engineering and product teams to turn research into practical security capabilities.

As an AI Security Researcher , you will play a key role in shaping the future of modern runtime AI security. You will investigate how real-world attacks unfold across AI-enabled applications, agents, tools, executed in cloud environments, and turn those insights into innovative, production-grade security capabilities across our AI Security Posture Management (AI-SPM) and AI Detection & Response (AI-DR) products.

This role is ideal for a deeply technical researcher who is driven to understand AI attacks at their core - not just identify suspicious prompts or surface-level indicators. You will research how prompt injection, tool misuse, agent drift, model abuse, and other emerging AI attack techniques translate into real runtime behavior and security impact. You will then apply that knowledge to build protections that are precise, resilient, scalable, and grounded in how attacks actually work in production.

Specifically, you will:

Research real-world attacks targeting models, agents, MCP/tooling ecosystems, RAG applications, and AI-enabled production systems.
Drive research end-to-end - explore, design, develop, validate, and deploy detection logic and protections based on runtime telemetry, exploit PoCs, technical analysis, and threat intelligence.
Shape AI-SPM capabilities by identifying what telemetry, signals, and modeling are required to continuously discover AI components, classify AI behavior, map risk, and detect unsafe or anomalous usage in production.
Shape AI-DR capabilities by researching how to detect AI-driven attacks, prove runtime impact, establish causality, and distinguish failed attempts from real compromise.
Work closely with engineering and product teams to turn deep technical research into practical security capabilities that deliver clear customer value.

we are looking for a Staff AI Engineer, Innovation.
As a Staff AI Engineer in global CTO group, you will play a central role in building the next generation of AI-powered security capabilities across product portfolio. This role is focused on rapid prototyping, experimentation, and innovation, turning emerging ideas into working product features that can scale across multiple products and technology stacks.
You will design and build AI-driven systems end-to-end, from agent-based workflows and model integrations to backend services, data pipelines, and product-facing capabilities. You will work closely with product, engineering, and research teams across the company to explore new use cases, validate ideas quickly, and bring impactful AI features into production.
This role is ideal for an experienced AI engineer who enjoys moving fast, working across boundaries, and building real production systems, not just experiments. Your work will directly influence how AI is embedded across platforms and how customers experience secure AI at enterprise scale.

We're looking for a talented Applied Security Researcher to join our team and play a major role in our frontier research team, enabling contextual code understanding across complex cloud deployments.
WHAT YOU'LL DO
Investigate the Code, Cloud, and AI technologies that we integrate with and protects, answering key research questions to unlock new features and product areas.
Design and build high-quality functional prototypes, driving abstract product ideas from inception into working PoCs and supporting development teams through initial implementation.
Conduct technical research to model risks and attack vectors specific to modern cloud- and AI-native architectures and systems.
Define and implement novel agentic workflows and advanced methods to express consistent contextual understanding of evolving application and cloud environments.

As an AI Engineer at our company, you will own the intelligent decision-making pipelines that turn complex workspace telemetry into autonomous security actions. You will design, build, and deploy the autonomous reasoning workflows and advanced data classification systems that drive our company's preventive operating model. Your focus will be on creating resilient, production-grade AI systems capable of deep policy comprehension, real-time prevention at the point of adoption, and autonomous remediation of existing risks.
This is a ground-floor opportunity to shape the AI strategy of a fast-growing cybersecurity company alongside a lean, elite team of builders.
WHAT YOULL DO
End-to-End Ownership: Own our AI capabilities entirely from initial research, architectural design, and prototyping, through to production deployment, optimization, and continuous monitoring.
Design & Build Agentic Workflows: Architect multi-step AI agents capable of autonomously investigating workspace risks, interpreting complex enterprise policies, and taking precise remediation actions.
Integrate Multi-Faceted ML: Bring innovation and creative thinking to our core engine. Implement diverse ML models across our entire research and product pipeline-utilizing clustering, text extraction, document analysis, and tabular data classification.
Ship Production-Grade AI: Build high-throughput, resilient, and fault-tolerant production code. You will ensure our AI pipelines and agentic workflows are highly predictable, deeply observable, and built to scale under enterprise-grade loads.
Implement Guardrails & Evaluation: Build continuous evaluation frameworks to benchmark agent accuracy, mitigate hallucinations, and enforce strict data security/privacy guardrails.

We are hiring an AI Researcher to join the research team building the next generation of AI-native security systems. You will work alongside security and threat researchers to build large-scale AI agents that reason over software, code, endpoint activity, and security signals to detect malicious behavior, uncover vulnerabilities, assess risk, and make autonomous security decisions in real-world production environments. We are entering the Mythos era - where attackers operate at machine speed using autonomous systems and AI-generated software, and defenders must evolve the same way. We use state-of-the-art frontier models, including access to Mythos, to build reliable AI-native security systems at global scale. You will help design the evaluations, harnesses, and reliability infrastructure that make autonomous agents dependable under real customer load, while collaborating with leading AI organizations including Anthropic on initiatives such as Glasswing. This is an opportunity to work at the frontier of AI, autonomous systems, and cybersecurity while helping define how the next generation of security systems will operate.
Key Responsibilities
Build AI agents and autonomous security systems that reason over software, code, endpoint activity, MCPs, and security signals to detect malicious behavior, uncover vulnerabilities, and assess risk at production scale.
Develop systems, tooling, and infrastructure that enable agents to autonomously investigate threats, hunt for malware in massive datasets, and operate reliably in complex security environments.
Design and run experiments to evaluate frontier-model and agent capabilities in realistic adversarial scenarios, including benchmark creation, large-scale datasets, automated evaluations, and human-in-the-loop review systems.
Build the evaluation harnesses, observability systems, and reliability infrastructure required to make autonomous agents accurate, scalable, and dependable under real customer load.
Engineer for scale and performance across large distributed AI systems, including inference optimization, orchestration, batching, caching, cost controls, and graceful degradation under high demand.
Continuously evaluate emerging models, agent architectures, prompting techniques, and research directions to ensure our systems remain at the frontier of AI-native cybersecurity.
Rapidly prototype and test new approaches across reasoning, autonomy, evaluations, and security workflows as the AI landscape evolves.
Partner closely with threat and security researchers to extract domain expertise, translate analyst reasoning into AI workflows, and enable new forms of automation and autonomous investigation.
Collaborate with leading AI and security researchers to shape the future of AI-native cybersecurity as the industry transitions into the Mythos era.
Senior candidates will help define research direction, shape technical strategy, identify high-leverage problems, and influence how autonomous AI systems are deployed across the organization.

1. AI Architecture & Technical Leadership

Guide AI architectural direction across platform, focusing on system design, model lifecycle, and integration of AI components into product workflows.
Act as a senior technical reviewer and thought partner for complex or cross-team AI design decisions.
Provide technical oversight on areas such as exploring new models/technologies/opportunities for the company
Surface architectural risks, tradeoffs, and long-term implications, including cost, security and compliance aspects and clearly advise the VP of AI when certain technical directions should not be pursued.
This role influences judgment, clarity, and experience, not through blocking authority.

2. Hands-on Applied Innovation (Core Pillar | ~50%)

Spend at least 50% of time hands-on, building:
End-to-end AI prototypes
Technical demos and proofs of concept
Exploratory implementations of new AI capabilities
Drive applied innovation that:

De-risks new technologies
Demonstrates feasibility and impact
Informs product direction and business opportunities
Build fast, concrete examples that teams can learn from and extend.
Transition successful prototypes to team ownership for further development and scaling.
This role is expected to lead AI innovation by doing, while working closely with product, medical and engineering

3. Best Practices & Technical Enablement

Define and promote best practices for applied AI development, including:
Rapid prototyping and vibe coding.
Agent design, orchestration, and evaluation patterns
Experimentation, benchmarking, and validation workflows
Help teams align on shared technical patterns, tools, and standards.
Identify opportunities to consolidate duplicated efforts and improve cross-team coherence.
Lead technical deep dives, architecture discussions, and design reviews.
4. AI Compliance & Regulatory Enablement (Technical Scope)

Ensure Navinas AI development practices align with applicable AI regulations for a software product handling sensitive medical data.
Define and guide AI-specific compliance practices, including data usage, transparency, evaluation, and documentation expectations.
Support and contribute to AI-related compliance and regulatory documentation, in close collaboration with Legal, Security, and Medical Research teams.
Serve as a technical point of reference for AI compliance questions.