דרושים » תוכנה » Software Developer - Cyber Security & AI Agents Development 25975

We're looking for an innovative Software Developer to join our company and build the next generation of automation platforms that measure, validate, and improve our security products.
You'll develop cloud-based systems that orchestrate cyber security tools, collect and analyze large-scale security data, and build intelligent automation using modern AI development methodologies. Your work will generate trusted security insights that help engineering teams improve our products, enable Sales to demonstrate their effectiveness, and provide the company with a clear understanding of its security posture.
Key Responsibilities
Build and own end-to-end features, from design through deployment and monitoring
Develop scalable cloud-based automation platforms that orchestrate security tools and large-scale data collection.
Build intelligent automation using modern AI development methodologies
Build platforms that transform large-scale security testing into actionable insights for engineering, management, and customer-facing teams
Collaborate with researchers, analysts, and product teams to deliver impactful solutions.

We are looking for a Security C++ Software Engineer to join our R&D organization and take part in developing high-end security technologies that protect critical business infrastructures from network and application downtime, application vulnerability exploitation, and emerging cyber threats.

You will join a highly skilled engineering team focused on building the next generation of cybersecurity defense systems, as well as enhancing the effectiveness and control of existing capabilities.

This role offers the opportunity to work in one of the most challenging and fast-evolving domains in cybersecurity, delivering cutting-edge solutions to customers worldwide.

What will you do?
Be part of a small, highly technical team responsible for designing and developing our cross-platform security products, with a strong focus on virtualization solutions.
Gain deep familiarity with the application code and serve as a focal point for R&D technical discussions and design decisions.
Develop advanced techniques to prevent cyberattacks by inspecting network traffic across all layers (Layers 2-7).
Ensure that applications run efficiently in virtualized and cloud environments, as well as on high-end platforms supporting multi-gigabit traffic.

This role is ideal for experienced backend engineers (ideally with strong Python skills) looking to transition into program leadership.You must thrive in a fast-paced environment and bring a proven track record of designing, building, and operating AI agents or agentic workflows.
We are at a pivotal point in our journey, transforming how we deliver product integrations-the core of our platform-by shifting from manual engineering to AI-first workflows powered by agents and agentic pipelines.
As a Senior Technical Program Manager, you will lead this transformation. You will collaborate closely with Customers, Partners, Product, and Engineering to scope and design integrations with IT and security tools. Simultaneously, you will redefine the entire integration lifecycle-using AI to automate how customer requests are analyzed, connector designs are created, and software is delivered from early access through full launch.
Your Impact
Lead AI Workflow Transformation: Drive the evolution of key business and engineering workflows from manual execution to AI-first, agent-driven processes.
Design & Scale Agentic Pipelines: Build, deploy, and continuously optimize multi-agent workflows that automate the lifecycle of integration requests-from intake and API requirement analysis to automated design generation, code reviews, and validation.
Drive Technical Integration Scoping: Work closely with Customers, External Partners, Business Development, Product, and Security Architects to scope use cases and create technical design requirements for third-party IT and security integrations.
Enhance Engineering Productivity: Improve developer throughput and software quality by integrating AI-powered tools (e.g., GitHub Copilot, OpenAI APIs) and agentic knowledge systems into the daily engineering lifecycle.
End-to-End Program Ownership: Support cross-functional teams throughout the full software development lifecycle of integrations, establishing scalable operational engineering processes to transition projects seamlessly from early access through full launch.
Cross-Functional Alignment: Partner with cross-functional peers to align solutions, resolve conflicts, clear operational bottlenecks, and drive complex technical issues to resolution.

We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across the platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how evolves from AI-enhanced internal tools to customer-facing AI products.

We are on a mission to secure the AI transformation that every company is going through, building a platform that protects organizations as they adopt AI tools at scale. This is your chance to join one of the fastest-growing areas in our company and develop technology that will define how cybersecurity operates in the AI era. You will be part of a multidisciplinary team of backend engineers, endpoint developers, AI researchers, and product experts from Israel and global acquisitions, all working together to deliver cutting-edge, end-to-end security solutions to the worlds largest enterprises.
As a Software Developer on our team, you will work across both backend services and endpoint components, designing scalable systems that connect endpoint-level data collection with cloud-based analysis and enforcement. Youll play a key role in building the agents and services that monitor and control interactions with AI tools, shaping a new category of security products that operate seamlessly across platforms and environments.
Key Responsibilities
Develop and maintain backend services alongside endpoint components for a cross-platform security platform
Design scalable systems that integrate endpoint-collected data with cloud-based processing and enforcement
Build and enhance endpoint agents responsible for monitoring and controlling interactions with AI tools (e.g., coding assistants, web-based AI services)
Implement data pipelines, policy enforcement logic, and secure data handling mechanisms across endpoint and backend layers
Collaborate with AI and product teams to deliver end-to-end solutions
Troubleshoot and resolve complex issues across distributed system and endpoint components.

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 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.

We are seeking a Senior Software Architect to lead and shape the architectural vision of our SaaS healthcare platform, guide the adoption of cutting-edge AI technologies, and ensure our solutions remain scalable, secure, and future-ready. This is a hands-on, strategic leadership role that combines visionary system design, proof-of-concept development, and AI-first innovation enablement.

Responsibilities
1. Architectural Leadership

Define, communicate, and evolve the platforms architectural vision to ensure alignment with business goals.
Lead high-level design discussions and decisions for new and existing products.
Establish and maintain architectural principles, standards, and patterns across all engineering teams to ensure consistency and coherence.
Drive cloud-native architecture in AWS with a strong focus on scalability, availability, performance, and cost efficiency.
2. Innovation & Emerging Technology

Build POCs and pilots for new solutions, frameworks, and AI capabilities.
Evaluate emerging trends in AI, LLMs, MCPs, agents, and developer productivity tools, ensuring strategic adoption where relevant.
Initiate projects/features to solve widespread problems (including work with Support, DevOps, Infosec)
3. AI Tooling Evangelism

Spearhead engineering-wide adoption of AI-assisted development workflows, including developer productivity tools, code copilots, automated quality checks, and automated documentation.
Define best practices, guidelines, and governance for AI usage in development (e.g., Cursor configuration rules, prompt engineering standards).
Educate and mentor teams on effective AI utilization for engineering, product, and operational tasks, taking into account security, costs, and compliance.
4. Technical Governance & Best Practices

Overall ownership of the system scalability, COGS, and stability of the product(s)
Define standards for coding, testing, CI/CD, and monitoring.
Enforce architectural and design reviews for key initiatives.
5. Cross-functional Collaboration

Work closely with Engineering, Product, Data Science, DevOps, and Security teams to deliver well-architected solutions.
Communicate complex technical concepts to non-technical audiences, including executives and external partners.

We are looking for a Principal MLOps Engineer with a deep focus on ML Platforms and Infrastructure to join our Data & AI group at Cortex Research. Our team is responsible for designing, building, and scaling the foundational MLOps and LLMOps platforms that power both our Data Scientists and Security Researchers. You will architect the high-performance core infrastructure that enables these roles to build, train, and deploy advanced AI systems-ranging from optimized Small Language Models (SLMs) to complex agentic workflows and RAG systems. If you are passionate about building scalable compute platforms and automating the full ML lifecycle to solve complex data and security challenges, we want to hear from you.
Key Responsibilities
Scale Distributed Training: Design and optimize infrastructure for training and fine-tuning LLMs and SLMs, leveraging distributed GPU workloads, efficient clustering, and compute optimization.
Automate the ML Lifecycle: Architect robust, automated pipelines for continuous training (CT) and deployment (CD) of models, ensuring a seamless flow from raw data collection to production environments.
Build Model Infrastructure: Own the serving architecture for LLMs/SLMs, balancing latency, throughput, and GPU utilization under production traffic.
Implement Advanced Monitoring: Establish comprehensive observability systems to monitor live model performance, data drift, and computational metrics, feeding insights back into the automated training loops for continuous improvement.
Collaborative Architecture: Partner closely with data scientists and security researchers to productize complex model architectures and streamline their workflows, while collaborating with our DevOps team to integrate with core cloud infrastructure.

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.