דרושים » תוכנה » Director, Engineering

Were growing and looking to hire a Director of Data & AI who embodies our core values: People First, Customer Obsession, Strive for Excellence, and Integrity.
About the Company:
A global leader in cyber-physical systems (CPS) protection, dedicated to securing the critical infrastructure that keeps the world running. Were a fast-growing, award-winning team where innovation meets purpose-and we want you to help us define the future of cybersecurity.
Our technology strategy is focused on solving real-world cyber-physical security problems at scale through robust, distributed, cloud-native architectures. We design and evolve a unified platform that serves as the technological backbone for all our products, delivering deep visibility across CPS environments-without disrupting critical operations. Our architecture emphasizes scalability, resilience, and extensibility to support both cloud and on-prem deployments.
About the Role:
We are seeking a visionary Director of Visibility to lead our core technology engine. This is a highly unique role that demands both top-tier professional expertise in cybersecurity research and the ability to seamlessly integrate Data Science and AI in a precise, highly productive manner. We have ambitious visibility goals that require uncompromising accuracy. Your mission is to combine precise, in-depth professional understanding of Cyber-Physical Systems (CPS/XIoT) with the immense scale and capabilities of AI. You will lead a multidisciplinary group comprising Data Science, Network/Protocol Research, and Asset Classification teams to revolutionize how we discover, classify, and secure critical assets across industrial (OT) and healthcare (IoMT) environments.
Responsibilities
As a Director of Data & AI your impact will be:
Multidisciplinary Leadership: Manage, mentor, and synchronize three distinct teams (Data Science, Network Research, and Asset Classification), ensuring cross-functional synergy and unified product delivery.
Scaling Accuracy with AI: Architect our visibility solutions to achieve unparalleled precision. Blend deep professional domain knowledge with advanced ML to scale asset discovery without sacrificing the exactness required in critical infrastructure.
Feature Engineering & Parsing: Oversee the translation of obscure, undocumented industrial and medical protocols into actionable features for our AI models.
Cross-Department Collaboration: Work closely with various data groups, product management, and R&D teams to translate network visibility into actionable risk management, segmentation, and threat detection policies.
Advanced Data Fusion & Collection Strategy: Manage diverse collection techniques (passive, active, and integrations), and architect how to fuse information for every single device at the scale of AI-bridging applications, algorithms, LLMs, and beyond.

We are seeking a strategic technical leader to drive the next phase of our engineering evolution. Reporting directly to the VP of R&D, you will carry two core mandates:
Manage one or more engineering teams with a focus on AI development.
Lead AI SDLC transformation efforts across the entire R&D organization.
This is a rare, high-leverage role at the intersection of people leadership, technical craft, and organizational transformation. If you want to define how an entire engineering organization works in the age of AI - and leave a lasting fingerprint on a fast-scaling SaaS platform - this role is for you.
What You'll Do:
Domain Ownership & People Management:
Assume operational leadership for critical R&D domains, including management of engineering teams focusing on AI.
Manage, coach, and grow Team Leads and senior engineers, building leadership depth across your domains.
Own team health, delivery velocity, and engineering quality for every team under your purview.
AI Developer Experience (AI DX):
Lead the transformation of our engineering processes by implementing AI-driven tools, frameworks, and workflows.
Significantly accelerate R&D throughput, optimize developer workflows, and foster an AI-first engineering culture - leading by example.
Drive adoption of agentic coding tools (e.g., Cursor, AI agents) across teams and measure their impact on productivity.
Technical Authority & Governance:
Challenge existing architectural paradigms and introduce innovative, out-of-the-box solutions to complex technical problems.
Mentor engineering teams and raise the bar for AI engineering quality and best practices across R&D.
Strategic Cross-Team Leadership:
Orchestrate complex, cross-functional initiatives that require deep technical alignment across disparate teams.
Manage project delivery, timelines, and execution to ensure seamless cross-functional results.
Architectural Vision:
Define and execute the long-term technical AI roadmap, ensuring high standards of scalability, reliability, observability and engineering excellence across the platform.

As an Engineering Manager at Cortex Cloud, you will lead a team of ~6 engineers operating in one of our most complex and cross-functional domains. This role requires a strong blend of people leadership and deep technical expertise, including systems design and large-scale distributed cloud architectures. You will be responsible for driving the design and delivery of complex, high-impact systems, while ensuring the team executes against the roadmap with both speed and engineering rigor.
Key Responsibilities
Build, mentor, and lead a high-performing software engineering team, fostering a culture of empowerment and driving both individual growth and collective impact.
Partner closely with Product Management and cross-functional teams (Infrastructure, Research, UX) to define priorities and shape multi-quarter product roadmaps, ensuring alignment across all stakeholders.
Own the end-to-end software development lifecycle, translating product strategy into executable plans and ensuring consistent, high-quality, on-time delivery.
Provide architectural leadership for scalable, distributed systems operating at petabyte scale, guiding the design and implementation of high-throughput, cloud-native backend microservices.
Drive production readiness by enforcing best practices around deployment, observability, reliability, and runtime stability, focusing on the details to ensure operational excellence.
Align stakeholders across business units through clear communication of technical strategy, trade-offs, priorities, risks, and execution plans.
Engage directly with strategic customers to lead technical deep dives and architecture reviews, and to influence future product direction.
Foster a culture of high engineering standards, accountability, and continuous improvement, with a strong emphasis on quality and security.

We are seeking an experienced and highly driven Director of Engineering to lead and scale our R&D team. This is a highly hands-on, deeply technical leadership role. You will be expected to actively contribute to codebases, lead by technical example, and ensure the high-quality delivery and scalability of our unified DataOps platform. This pivotal role requires a leader who can both deeply understand and solve complex technical challenges with code, while also inspiring and guiding a team to build innovative solutions. Reporting directly to the CTO, you will play a critical part in shaping our engineering culture, driving technical excellence, and fostering a collaborative environment that aligns closely with our product vision and business goals.
What You'll Do:
Provide Technical Leadership & Guidance: Offer deep technical leadership, actively participating in coding, architectural design, and complex problem-solving to ensure high standards of code quality, scalability, and system reliability.
Lead & Grow Engineering Teams: Lead, mentor, and grow our R&D engineering team, fostering a culture of technical excellence, hands-on problem-solving, and continuous improvement.
Drive Ownership & Accountability: Instill strong ownership, accountability, and a builder mindset within the engineering organization, empowering teams to execute with velocity and autonomy.
Solve Complex Challenges: Troubleshoot and resolve complex technical and organizational challenges to ensure smooth operations and delivery.
Collaborate Cross-Functionally: Collaborate closely with Product and other cross-functional teams to translate business requirements into robust technical solutions and align engineering efforts with company objectives.
Optimize Processes: Optimize engineering processes, methodologies, and tools to support rapid growth and evolving business needs.
Reduce Leadership Load: Strategically contribute to reducing the technical and operational load on current leadership, taking on key initiatives and areas of ownership.

We are looking for a Director of Data Engineering to join our team. This is a Hybrid (Ramat Gan) role, reporting to the VP Engineering - Lakehouse in the Exposure Management & Security Operations department. In this role, you will lead multiple data engineering teams driving the strategy, architecture, and operation of a high-scale, multi-tenant cybersecurity data platform.

What youll do (Role Expectations)

Manage and mentor engineering managers and technical leads while aligning platform strategy with company goals and cross-functional partners
Engineer, maintain, and scale core data pipelines and data platform infrastructure, designing reliable ETL and ELT flows across databases, APIs, event streams, business systems, and data lakes
Oversee platform reliability, cost optimization, CI/CD pipelines, and enterprise-grade observability
Build scalable data solutions for internal teams as well as external, user-facing products
Partner with business teams, product stakeholders, and support teams to transform data needs into robust self-serve analytics and AI-assisted insights

Required Director Software Engineering- CWP (Cortex Cloud)
Job Summary
As a Director of Engineering at Cortex Cloud, you will lead an engineering group of approximately 25 engineers operating in one of our most complex and cross-functional domains, focused on building KSPM (Kubernetes Security Posture Management) and CNS (Cloud Network Security).
This highly technical group works closely with some of the largest companies in the US across various domains.
This role requires a strong blend of strategic leadership and deep technical expertise, including systems design and large-scale distributed cloud architectures.
You will be responsible for driving the design and delivery of complex, high-impact systems, while ensuring your teams execute against the roadmap with both speed and engineering rigor.
Key Responsibilities:
Build, mentor, and lead high-performing backend engineering teams, fostering a culture of empowerment and driving both individual growth and collective impact.
Partner closely with Product Management and cross-functional teams (Infrastructure, Research, UX) to define priorities and shape multi-quarter product roadmaps, ensuring alignment across all stakeholders.
Own the end-to-end software development lifecycle, translating product strategy into executable plans and ensuring consistent, high-quality, on-time delivery.
Provide architectural leadership for scalable, distributed systems operating at petabyte scale, guiding the design and implementation of high-throughput, cloud-native backend microservices.
Drive production readiness by enforcing best practices around deployment, observability, reliability, and runtime stability, focusing on the details to ensure operational excellence.
Align stakeholders across business units through clear communication of technical strategy, trade-offs, priorities, risks, and execution plans.
Engage directly with strategic enterprise customers-including some of the largest companies in the US-to lead technical deep dives, review architecture, and influence future product direction.
Foster a culture of high engineering standards, accountability, and continuous improvement, with a strong emphasis on quality and security.

We are seeking an experienced Program Manager - Decisioning (Credit Risk) to own, evolve, and execute our risk decisioning products. This role partners closely with ML Engineers , Engineering Leads and Business Stakeholders to transition us from product-specific silos into a generic, high-velocity engine powering Card, BNPL, and emerging products.

Blending strategic oversight with hands-on, rigorous program execution, you will turn complex risk logic into scalable, explainable platforms. Youll own both long-range quarterly planning and sprint execution- defining who we approve, on what terms, and at what expected loss- while ensuring strict alignment with our risk portfolios, regulatory requirements, and long term unit economics. This role requires strong judgment, deep analytical thinking and meticulous detail standards.

As the Program Manager, your mission is to drive an advanced, adaptable decisioning platform that eliminates financial waste and prepares us for its next stage of hyper-growth. You will drive the delivery of core systems that determine how we approve, price, and manage risk-turning complex data into fair, instant, and transparent outcomes for millions of customers.

What Youll Do

Cross-Functional Partnership
Act as the glue in the "Decisioning Triangle," partnering with Business owners, ML Leads and Engineer Leads to operationalize underwriting policies, while taking into account the trade-offs between approval rates, loss, revenue, and customer experience. Partner and balance competing requirements from various business owners (Heads of Card, BNPL, etc.) as well as Compliance, Legal, and Operations to ensure high-quality execution and regulatory integrity.

Hands-On Program Management
Act as an owner for key initiatives, driving the full product lifecycle from discovery and definition through launch, iteration, and performance monitoring. Use data and experimentation to inform decisions and continuously improve outcomes. Identify and remove bottlenecks in the underwriting flow to drive toward high-automation and speed-to-market.

Were looking for an Engineering Team Lead, who will be responsible for the foundational infrastructure framework used by all our engineering teams to build, deploy, and operate AI agents safely in production. We are building the "operating system" for AI, 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 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 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 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 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 Machine Learning Engineering Manager, you will lead a team focused on the foundational ML & Data layers to power the ranking & recommendation systems in scope. You will drive the development of robust data & ML pipelines at scale, lead the implementation of the tools for ML scientists to test and productionize advanced ML RecSys solutions.

As a technical manager of Machine Learning Engineers and Data engineers, you should be passionate about technology, keep up to date with recent breakthroughs in the field, define and shape the teams ML and platforms roadmap, and not be afraid to get your hands dirty with code when needed.

You are expected to be the focal point for all technical aspects, make sure your team members deliver on their tasks, and work together with other stakeholders to define and shape the roadmap of our products. You will work independently and will also be responsible for making technical decisions within your team.

When it comes to management, your expertise in handling people will motivate and inspire them to reach outstanding success! You should have experience in developing people. You will mentor and coach your team while working closely with a Product Manager.



Key Job Responsibilities and Duties:

Lead and develop a high-performing team, fostering individual growth and collaboration.

Manage and mentor ML engineers and Data engineers, ensuring their professional development and effectiveness.

Develop scalable ML infrastructure and pipelines for efficient data processing and evaluations deployment.

Evaluate architecture solutions based on cost, business needs, and emerging technologies.

Collaborate closely with software engineers to ensure seamless deployment and model inference.

Monitor application health, set and track relevant metrics, and implement effective maintenance strategies.

Collaborate with stakeholders to translate business requirements into viable ML solutions.

Evaluate and integrate new ML technologies to enhance productivity and performance.