דרושים » תוכנה » Software Developer - AI Security 25561

The Falcon Secure Access (FSA) team is expanding. As a Senior Software Engineer on our team, you will architect and deliver a next-generation secure access platform that converges Zero Trust Network Access with browser-native security.

You'll build the core systems that enable users to seamlessly and securely access internal sites, private applications, and cloud resources directly from the browser - without legacy VPNs or remote desktops - while enforcing real-time protection against zero-day exploits, phishing, data exfiltration, and unauthorized access.

This role sits at the intersection of network engineering and browser security: you'll design and implement advanced proxy communication, secure tunneling, and identity-aware routing - all operating at the browser's core to deliver holistic protection including DLP, insider threat detection, SaaS security, and continuous zero-trust verification.

What You'll Do:

Design and build ZTNA infrastructure - implement zero-trust access policies, secure tunneling, and identity-aware network routing that replaces traditional VPN architectures.

Develop advanced networking solutions - build and optimize proxy communication layers, WebSocket-based transport, and encrypted client-to-server channels that handle millions of concurrent connections.

Architect high-scale backend systems - design distributed microservices for policy enforcement, real-time threat detection, and access control at scale using Node.js / TypeScript.

Implement secure client-server communication - design highly secured agent-to-cloud architectures with certificate pinning, mutual TLS, and encrypted tunneling protocols.

Build browser-native security components - develop browser extensions and agents (Chrome, Edge, Firefox etc.) that enforce data protection, prevent data leakage, and provide granular visibility and control.

Own features end-to-end - from design through delivery, including deployment and monitoring.

Influence architecture and roadmap - play a key role in architectural decisions, building toward an efficient distributed zero-trust architecture.

Research and develop - drive new initiatives and POCs in zero-trust access domains and browser security.

Collaborate cross-functionally - work with security researchers, product, and platform teams across multiple locations to solve complex problems.

We are seeking a Software Engineer to join Dashs core development team. You will design, build, and ship the platform that powers discovery, session-aware detection, policy governance, and runtime enforcement across workstations, SaaS, and cloud. You will work on scalable, low-latency services that process agent activity in real time and enforce security policies without slowing builders down. This role requires strong engineering fundamentals, a focus on system reliability, and an interest in the unique challenges of agentic security.
Responsibilities:
Design and Implement Services: Design, develop, and deploy scalable backend services and APIs for the Dash Security platform (customer and admin APIs, detection ingestion, aggregation, and control-plane services).
Build Core Features: Implement features for agent/MCP/skill discovery, session and intent-aware detection, policies, and runtime enforcement across coding agents and enterprise AI platforms.
Optimize Runtime Protection: Maintain and optimize high-throughput detection and enforcement pipelines that operate at enterprise scale (ingestion, detectors, verdicts, and policy dispatch).
Integrate with Platforms: Build and deepen integrations with coding agents, SaaS AI platforms, identity providers, EDR, SIEM, and outbound action systems to ingest telemetry and enforce controls.
Ensure Reliability: Focus on code quality, performance, monitoring, and stability through robust testing, CI/CD, and operational excellence.
Collaborate with Research: Partner with the AI Security Research team to turn findings, signatures, and heuristics into production-ready detectors and enforcement logic.
Contribute to Architecture: Participate in technical design and architectural reviews across our codebases, agents, and event-driven backend services.
Stay Current: Continuously learn and apply new technologies, development methodologies, and security best practices.

Were looking for an Engineering Team Lead, who will be responsible for the foundational infrastructure framework used by all our company engineering teams to build, deploy, and operate AI agents safely in production. We are building the "operating system" for AI at our company, covering agent sessions, memory management, tool orchestration, durable execution, and multi-tenant isolation. You will lead a high-impact team of 5 engineers to create the runtime and platform that defines the future of autonomous enterprise intelligence.
Youll Own:
Agentic Framework Architecture: Designing and building our companys internal agentic framework, leveraging and integrating industry-standard tools such as LangChain, LangSmith, ADK, and similar ecosystems.
Evaluation and Quality Systems: Building evaluation frameworks and workflows for AI agents, including offline and online evaluations, quality metrics, regression detection, and experimentation infrastructure.
Team Leadership & Mentorship: Leading a squad of 3-4 senior engineers, fostering a culture of technical excellence, and managing end-to-end delivery in a fast-paced environment. You will spend approximately 50% of your time hands-on, architecting core systems and reviewing code, and 50% leading the team, mentoring engineers, and aligning with cross-functional stakeholders.
Observability, Monitoring, and Guardrails: Providing the organization with robust observability capabilities for AI agents, including tracing, logging, monitoring, cost tracking, and safety guardrails to ensure reliable and responsible usage.
Developer Enablement Platforms: Creating APIs, SDKs, and abstractions that enable product teams to easily build, test, and operate agents while adhering to platform standards.
Cross-Language Integrations: Designing integrations and tooling across Python and Java to enable seamless adoption of the AI framework within our companys broader backend ecosystem.
Youll Solve:
Agent Lifecycle and Orchestration Complexity: Managing agent execution, tool usage, memory, workflows, and failure modes in production-grade systems.
AI System Reliability at Scale: Ensuring agents remain observable, debuggable, and safe as usage scales across teams and products.
Evaluation and Drift Challenges: Detecting quality regressions, model behavior changes, and unintended agent behaviors through robust evaluation and monitoring systems.
Platform Adoption Friction: Balancing flexibility with guardrails so teams can innovate quickly without compromising reliability, security, or cost controls.
Youll Impact:
Company-Wide AI Enablement: Empowering every engineering team at our company to build agent-based solutions faster, with higher quality and confidence.
Foundational AI Infrastructure: Establishing the core frameworks, evaluations, and observability standards that all AI agents at our company will rely on.
AI Safety and Quality Bar: Raising the bar for how AI systems are evaluated, monitored, and governed across the company.

As a Software Engineer in the CrowdStrikes Browser Protection team, you will play a key role in building a browser protection platform focused on holistic security protection, including: data protection, data loss prevention, Identity protection and SaaS security. In this role, youll be responsible for developing CrowdStrikes next-gen browser protection solutions, that integrate seamlessly with CrowdStrikes security platform and leverages CrowdStrike agent. The product provides real-time protection against data leaks, unmanaged devices risk, insider threat, unauthorized data access, and other security risks. Working in close collaboration with our cross-functional team, youll leverage your expertise to build a high-performance, secure browser solution and extension that ensures user data is safe without impacting browsing experience. This position offers a unique opportunity to influence the future of data protection technology at CrowdStrike by delivering an extension that empowers users and protects them in todays dynamic digital landscape.

What You'll Do:​

Design and implement CRWD browser protection suite, including browser extensions (e.g., Google Chrome, Edge etc. ), leveraging CrowdStrike endpoint sensor and Leverage in-depth chromium knowledge to develop cybersecurity capabilities within the browser.

Own features from design to delivery.

Impact product roadmap and architectural design.

Collaborate with multi-functional team in various physical locations.

Troubleshoot issues with the product as reported from customers responsively.

Appdome's mission is to protect every mobile app in the world and the people who use them. We are the leader in AI-native mobile business protection, providing cyber and fraud teams with an agentic platform that builds, monitors, and maintains security defenses in Android and iOS apps — with no SDKs, no coding, and no disruption to engineering cycles.
Our platform delivers over 400 security, anti-fraud, anti-bot, and API protection capabilities, powered by deep learning models trained on a decade of mobile defense data and trillions of live threat events. From build time to runtime, Appdome's AI Agents help mobile brands detect, investigate, and respond to threats faster than ever — recognized as the best AI Platform for Cyber Resilience at RSA Conference 2026 for the second consecutive year. Leading financial, healthcare, m-commerce, and B2B brands rely on Appdome to secure over 50,000 mobile apps and protect more than 1 billion end users globally.
Appdome is an Equal Opportunity Employer. We are committed to diversity, equity, and inclusion in our workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law. All qualified applicants will receive consideration for employment without regard to any of these characteristics.
About the Role We are looking for a talented Software Engineer to join Appdome's Identity Group. You will take part in building advanced fraud detection capabilities, working closely with security researchers and data teams to develop cutting-edge solutions that protect hundreds of millions of mobile devices.
Responsibilities
* Design and develop core components of fraud detection systems from early prototyping through production-ready releases.
* Build scalable backend services and distributed systems that process data at scale.
* Work with large-scale datasets and collaborate with data teams to create actionable signals and features.
* Write high-performance, production-quality code in C and C++ optimized for reliability and performance.
* Take ideas from rapid proof-of-concept through to production, tackling complex engineering challenges across the full development lifecycle.

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer specializing in infrastructure to join our founding team. The focus of this role is to build and scale the infrastructure that powers autonomous AI agents automating complex enterprise workflows. You will own the systems, pipelines, and platforms that let our AI agents run reliably, securely, and at scale in production.

Your Impact
Infrastructure & Platform

Design, build, and own the core infrastructure powering our AI agent platform, from data pipelines to production deployment systems.

Build and scale the backend systems that support high-throughput document processing and data extraction workloads.

Cloud Infrastructure and Scalability

Architect and deploy infrastructure on cloud platforms (AWS, GCP, or Azure) with a focus on scalability, reliability, and cost efficiency.

Own containerization and orchestration (Docker, Kubernetes) for all production workloads.

Build and maintain CI/CD pipelines and DevOps practices that let the team ship fast without breaking things.

Data Infrastructure

Design and manage data pipelines to process and analyze large volumes of documents and unstructured data at scale.

Build the infrastructure layer connecting AI agents to databases, vector stores, and enterprise systems (ERP, CRM).

API & Systems Integration

Build and maintain robust, well-documented APIs connecting AI agents with external systems and enterprise software.

Design for reliability: retries, observability, and graceful degradation across distributed systems.

Security and Compliance

Implement authentication and authorization mechanisms (OAuth2, JWT) to secure AI-driven systems.

Ensure compliance with data privacy standards (e.g. GDPR, HIPAA) and drive best practices for secure data handling across the infrastructure.

Monitoring and Optimization

Build observability and monitoring systems to track infrastructure health, performance, and cost.

Continuously optimize system performance for speed, reliability, and cost-efficiency at scale.

Collaboration

Work closely with AI/ML engineers, product, and the founding team to make sure infrastructure decisions support fast iteration and production-grade reliability.

Participate in code reviews, design discussions, and architecture planning to drive infrastructure strategy.

We're looking for a Software Engineer to join our R&D team. In this role, you'll design and build scalable, high-performance systems that bring together rich backend capabilities and intuitive frontend experiences. You'll be part of a mission-driven team, building innovative technologies that enable security teams to detect, analyze, and respond to threats faster than ever before.





WHAT YOU WILL DO

Develop and own end-to-end features across the entire stack, from backend services to frontend interfaces.
Design and implement distributed backend systems that handle massive volumes of security data in real-time.
Build modern, responsive, and accessible user interfaces using React, TypeScript, Remix, Tailwind, and Shadcn.
Architect and maintain robust APIs and data contracts between the frontend and backend.
Collaborate with product, design, and security experts to deliver impactful user facing features.
Ensure high code quality by writing comprehensive unit, integration, and E2E tests using tools like Vitest, Playwright, and React Testing Library, as well as backend testing tools
Optimize system performance, reliability, and scalability on both ends of the stack.
Take part in critical architectural discussions and influence the technical direction of the platform.

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer to join our founding team. The focus of this role is to design, develop, and deploy autonomous AI agents that can automate and optimize complex enterprise workflows. You will work on building intelligent systems capable of decision-making, data extraction, document processing, and other tasks typically requiring human intervention. This is an opportunity to influence the architecture and strategy of AI-driven automation solutions for large-scale enterprise environments.

Your Impact
AI Agent Development

Design and develop autonomous AI agents using best of breed large language models to automate tasks such as document processing, data extraction, and workflow management.

Implement reinforcement learning techniques to enhance decision-making capabilities of AI agents.

AI Integration

Build and integrate APIs that connect AI agents with external systems and enterprise software (ERP, CRM).

Use frameworks like TensorFlow, PyTorch, or Hugging Face to deploy and optimize AI models for real-time processing.

Data Processing and Pipelines

Design and manage data pipelines to process and analyze large volumes of documents and unstructured data efficiently.

Optimize data handling to improve speed and accuracy of AI agents.

Security and Compliance

Implement authentication and authorization mechanisms to secure AI-driven systems.

Ensure compliance with data privacy standards (e.g., GDPR, HIPAA) and adopt best practices for secure data handling.

Cloud Infrastructure and Scalability

Deploy AI agents on cloud platforms (AWS, GCP, or Azure) ensuring scalability and reliability.

Leverage containerization (Docker, Kubernetes) for efficient deployment and management.

Testing and Optimization

Develop and execute unit, integration, and performance tests for AI-driven systems.

Continuously monitor and optimize system performance for speed, accuracy, and cost-efficiency.

Collaboration

Work closely with AI researchers, front end engineers, and product teams to align AI agent capabilities with business requirements.

Participate in code reviews, design discussions, and architecture planning to drive innovation.

A sensor runs on every customer machine, takes inventory of the software and AI tools in use, sends that back over an encrypted channel, and enforces policy locally. It runs as a service on Windows and a daemon on macOS, with the access and the responsibility that come with running as SYSTEM and root. This role owns the hard parts of it.

What you'll work on

The sensor itself: software inventory, secure telemetry, and on-device policy enforcement, on both Windows and macOS.

Real OS work. On macOS that means Launch Services, Spotlight, IOKit, the Security framework, and Open Directory. On Windows it means services, ETW, WMI, the registry, and WinSock.

The policy enforcement point: evaluating rules over events (including AI-tool use and browser extensions) against a policy engine, and talking to the backend that makes the decisions.

Encrypted logging and telemetry, crash handling and symbolication, and the recovery path that keeps the agent running and hard to tamper with.

Signed installers and macOS configuration profiles.

Tech you'll work with

The work is low-level systems development in Rust, close to the operating system across Windows, macOS, and Linux - memory, processes, files, and the OS internals that expose them. Alongside that, you'll lean hard on agentic coding tools; deep fluency with at least one is central to how we work, not a bonus. Expect to range across the stack - OS internals, AI tooling internals, CI, and a fair amount of reverse engineering - and to learn the parts you don't know yet.

We are seeking a Staff Systems Software Engineer to design and build the foundational infrastructure that powers products used by billions of people worldwide. In this role, you will architect and implement large-scale distributed systems, low-level platform components, and high-performance services that underpin our core product stack. You will drive technical strategy across system reliability, performance, and scalability, partnering closely with product, infrastructure, and data engineering teams to deliver systems that operate at global scale with high availability and efficiency.
Software Engineer, Systems Responsibilities
Architect and implement large-scale distributed systems and platform services that support high-throughput, low-latency workloads across our product infrastructure
Lead the technical design of systems components including storage layers, compute pipelines, networking abstractions, and service orchestration frameworks
Identify and resolve systemic performance bottlenecks through instrumentation, profiling, and targeted optimization across the full systems stack
Define and enforce service level objectives for owned systems, building dashboards, alerting pipelines, and runbooks to reduce mean time to mitigation during incidents
Drive reliability improvements by reducing failure surface, designing resilient rollout strategies, and leading regular resiliency and overload testing exercises
Collaborate with cross-functional partners across product engineering, infrastructure, and data science to align system architecture with evolving product and business requirements
Establish and evolve coding standards, architectural patterns, and engineering best practices for systems development across the broader organization
Leverage AI-assisted development workflows to accelerate design iteration, code generation, and systems analysis, applying sound judgment on when to rely on AI versus deep systems expertise
Mentor other engineers on systems design principles, debugging methodologies, and production operations, and contribute to onboarding programs for new team members
Lead incident retrospectives, identify root causes of complex production failures, and drive implementation of systemic improvements to prevent recurrence