דרושים » תוכנה » Senior Software Engineer

We are looking for a Senior Backend Engineer (AI DLP) to join the team building our next-generation DLP product. The team is extending our data-security platform from understanding sensitive data at rest to protecting it at the moment it is used or shared-including across browsers, GenAI applications, and employee endpoints.

You will help build the control plane behind this product: the services that manage endpoint identity and enrollment, policies, classification, device configuration, telemetry, and the connection between our DSPM intelligence and real-time DLP decisions. This is a role with substantial technical ownership, direct customer impact, and close collaboration across Product, Research, Data, Frontend, and Infrastructure.

Responsibilities
Design and implement core backend components of our DLP control plane.
Own features end-to-end: architecture, implementation, testing, rollout, observability, and production operation.
Build secure, reliable multi-tenant services that communicate with browser extensions and endpoint agents deployed across customer endpoint fleets.
Connect our DSPM classification and policy systems with real-time endpoint enforcement, translating data-at-rest intelligence into actionable protection.
Design APIs and data models that support large endpoint fleets, frequent policy updates, offline clients, credential rotation, and safe software upgrades.
Improve the scalability, performance, reliability, and operational visibility of the DLP platform.
Conduct design and code reviews and help establish strong engineering practices.

Cortex Cloud Application Security (AppSec) is building the security platform for the modern software development lifecycle. We help organizations identify, prioritize, and prevent security risks across source code, open-source dependencies, infrastructure as code, secrets, container images, CI/CD pipelines, and the broader developer ecosystem.
At the heart of AppSec is a large-scale platform responsible for connecting to customers' development environments, collecting and processing massive amounts of data, and making it reliably available to security products and experiences across Cortex Cloud.
We are looking for an exceptional Senior / Principal Backend Engineer to join our AppSec Platform group, reporting directly to the Group Leader.
This is a highly autonomous, hands-on role for an engineer who wants broad technical ownership rather than a narrowly defined domain. You will work on some of AppSec's most important and challenging engineering problems - spanning high-scale distributed systems, data infrastructure, onboarding and integrations, developer experience, reliability, performance, and AI-driven engineering.
You will frequently operate across team boundaries, take ambiguous problems from idea to production, and lead technical initiatives that have an impact well beyond a single service or team.
We are looking for someone who combines deep backend expertise with strong execution: an engineer who can design the architecture, dive into the code, debug production systems, challenge existing assumptions, rapidly prototype new approaches, and bring others along with them.
Key Responsibilities
Lead Critical Initiatives End-to-End - Own complex, business-critical engineering efforts from problem definition and architecture through implementation and production, often spanning multiple teams and domains.
Build and Scale the Backbone of AppSec - Design and evolve distributed systems and data infrastructure supporting large enterprise environments and hundreds of millions of entities, while balancing scalability, reliability, performance, and cost.
Stay Hands-On and Raise the Engineering Bar - Write and review production code, solve complex technical problems, and champion excellent architecture, maintainable code, testing, observability, and production ownership.
Drive Performance & Reliability - Identify architectural and operational bottlenecks and lead meaningful improvements in scalability, resiliency, efficiency, observability, and production readiness.
Shape DevEx and AI-Driven Engineering - Improve how engineers build, test, debug, and operate software while leveraging AI, automation, and agentic approaches to accelerate development and unlock new capabilities.

we are using technology to transform transportation around the world. From changing a single persons daily commute to reducing humanitys collective environmental footprint - weve got huge goals.
As a Senior Backend Engineer in the Routing team, you will be responsible for designing, building, and scaling the backend systems that power our companys core products. Youll work on high-impact, distributed services that manage geospatial data, large-scale databases, real-time events, and mission-critical workflows used across multiple teams and regions. Your work will directly influence system reliability, performance, and developer productivity at scale.
You will collaborate closely with Product, Infrastructure, Data, and other engineering teams to define system boundaries, evolve shared services, and ensure our backend platform can support rapid product growth. You will be part of a highly skilled and motivated engineering group responsible for building robust, scalable, and maintainable backend systems that operate in real time and at high load.
What Youll Do:
Design, build, and scale backend systems and data pipelines that power our companys GIS and mapping platform, from initial design through production deployment and long-term ownership.
Own features end-to-end with strong accountability, including design, implementation, testing, deployment, monitoring, and ongoing maintenance.
Develop and maintain Python-based data pipelines that ingest, process, and transform large-scale OpenStreetMap (OSM) and other geospatial datasets.
Model, store, and query complex geospatial data using PostgreSQL and PostGIS, including road topology, zones, polygons, points, and other business-critical spatial entities.
Optimize database schemas, spatial indexes, and queries to efficiently handle large datasets and high-throughput workloads.
Build and maintain backend services and APIs that expose geospatial and mapping data to other backend services, frontend applications, and data consumers.
Collaborate closely with other backend teams, frontend teams, data teams, and infrastructure to align on data contracts, system boundaries, and cross-team initiatives.
Improve system reliability, observability, and performance through monitoring, alerting, benchmarking, and continuous optimization.
Contribute to architectural decisions, technical standards, and best practices, while mentoring other engineers and raising the overall engineering bar.

We are looking for an exceptional Senior / Principal Backend Engineer to join our AppSec Platform group, reporting directly to the Group Leader.
This is a highly autonomous, hands-on role for an engineer who wants broad technical ownership rather than a narrowly defined domain. You will work on some of AppSec's most important and challenging engineering problems - spanning high-scale distributed systems, data infrastructure, onboarding and integrations, developer experience, reliability, performance, and AI-driven engineering.
You will frequently operate across team boundaries, take ambiguous problems from idea to production, and lead technical initiatives that have an impact well beyond a single service or team.
We are looking for someone who combines deep backend expertise with strong execution: an engineer who can design the architecture, dive into the code, debug production systems, challenge existing assumptions, rapidly prototype new approaches, and bring others along with them.
Key Responsibilities:
Lead Critical Initiatives End-to-End - Own complex, business-critical engineering efforts from problem definition and architecture through implementation and production, often spanning multiple teams and domains.
Build and Scale the Backbone of AppSec - Design and evolve distributed systems and data infrastructure supporting large enterprise environments and hundreds of millions of entities, while balancing scalability, reliability, performance, and cost.
Stay Hands-On and Raise the Engineering Bar - Write and review production code, solve complex technical problems, and champion excellent architecture, maintainable code, testing, observability, and production ownership.
Drive Performance & Reliability - Identify architectural and operational bottlenecks and lead meaningful improvements in scalability, resiliency, efficiency, observability, and production readiness.
Shape DevEx and AI-Driven Engineering - Improve how engineers build, test, debug, and operate software while leveraging AI, automation, and agentic approaches to accelerate development and unlock new capabilities.

Zipher is building the Autonomous Execution Layer for cloud data and AI workloads. Backed by $50M in funding , we dynamically orchestrate clusters, predict bottlenecks, and auto-heal infrastructure in real time — with zero human intervention . Our platform runs in production at global enterprise customers, including Fortune 500 companies , delivering mission-critical resilience and sub-second optimization We are looking for a Senior Backend Engineer to build the systems behind Zipher’s autonomous execution engine. You will own core infrastructure that turns high-volume telemetry and changing cloud conditions into reliable, real-time decisions across production data and AI workloads.
What You’ll Do
* Architect and scale the core backend services that power real-time workload orchestration, optimization, and self-healing
* Build resilient, high-throughput systems for processing distributed state, event streams, and production telemetry at scale
* Design infrastructure that makes autonomous decisions observable, explainable, and safe for enterprise engineering teams
* Partner closely with data, ML, and platform engineers to bring optimization models and control loops into reliable production systems
* Drive architectural decisions, raise the engineering bar, and own services from design through deployment, observability, and incident response
What We Offer
* A chance to build the core execution engine for a new category of autonomous data platform High ownership from day one : real architectural influence, direct exposure to founders, and responsibility for mission-critical systems
* Technical, high-velocity team that values curiosity, speed, and engineering craftsmanship Top-of-market compensation and meaningful equity Ready to build the infrastructure that lets data and AI workloads run autonomously? Hit Apply.

We are looking for an exceptional Senior / Principal Backend Engineer to join our AppSec Platform group, reporting directly to the Group Leader.
This is a highly autonomous, hands-on role for an engineer who wants broad technical ownership rather than a narrowly defined domain. You will work on some of AppSec's most important and challenging engineering problems - spanning high-scale distributed systems, data infrastructure, onboarding and integrations, developer experience, reliability, performance, and AI-driven engineering.
You will frequently operate across team boundaries, take ambiguous problems from idea to production, and lead technical initiatives that have an impact well beyond a single service or team.
We are looking for someone who combines deep backend expertise with strong execution: an engineer who can design the architecture, dive into the code, debug production systems, challenge existing assumptions, rapidly prototype new approaches, and bring others along with them.
Key Responsibilities:
Lead Critical Initiatives End-to-End - Own complex, business-critical engineering efforts from problem definition and architecture through implementation and production, often spanning multiple teams and domains.
Build and Scale the Backbone of AppSec - Design and evolve distributed systems and data infrastructure supporting large enterprise environments and hundreds of millions of entities, while balancing scalability, reliability, performance, and cost.
Stay Hands-On and Raise the Engineering Bar - Write and review production code, solve complex technical problems, and champion excellent architecture, maintainable code, testing, observability, and production ownership.
Drive Performance & Reliability - Identify architectural and operational bottlenecks and lead meaningful improvements in scalability, resiliency, efficiency, observability, and production readiness.
Shape DevEx and AI-Driven Engineering - Improve how engineers build, test, debug, and operate software while leveraging AI, automation, and agentic approaches to accelerate development and unlock new capabilities.

Required Founding Engineer
Tel Aviv
Full-Time
About Us:
Were building the first AI-native autonomous revenue engine for D2C brands, a new category of AI infrastructure replacing the entire revenue stack.
If you want to build category-defining infrastructure with a team that ships weekly, lets talk.
About the Role:
This is a broad, hands-on engineering role.
Youll work directly with the founders and own the most challenging parts of the platform end to end.
The focus is backend and infrastructure, but youll work across the full stack whenever a problem calls for it.
Youll help shape the technical direction, and how engineering works as the team grows.
Responsibilities:
Own the Challenging Problems - Take the most complex parts of the platform end to end, from architecture through production.
Shape Architectural Decisions - Help define service boundaries, data models, and technical direction as the platform scales.
Build the Core - Design and ship the systems at the heart of the platform.
Scale the Data Pipeline - Build the ingestion, processing, and orchestration layers that move data through the platform reliably.
Own Infrastructure - Shape deployment, observability, and reliability across cloud infrastructure and Kubernetes.
Build End to End - Work across the full stack when the problem calls for it, including the surfaces your services power.

Required Senior Backend Engineer - AI Framework (Python)
As a Senior Backend Engineer on our AI Framework team, you will build the foundational platform that enables the entire organization to design, evaluate, deploy, and operate AI agents at scale. This is a new, high-impact team responsible for creating the frameworks, tools, and guardrails that power our agentic ecosystem.
Youll work deeply in the agentic space, designing systems for orchestration, evaluation, observability, and safety. The platforms you build will be used by multiple teams across, making your impact immediate and company-wide.
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.
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.
Agent Runtime and Execution Engine: Building the runtime responsible for orchestrating agent execution, managing tool calls, maintaining state and memory, and ensuring reliable execution across distributed systems.
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.

Our engineering team is at the core of how modern data security is built. We are redefining how organizations understand and protect their most sensitive data in a world of growing scale, speed, and complexity. By combining high-performance systems with intelligent, AI-driven capabilities, we challenge traditional approaches and push the boundaries of what data classification can achieve.
Were looking for engineers who thrive in open-ended environments, are energized by hard problems, and are motivated to build solutions that dont yet exist. This role is about more than writing code. Its about shaping how intelligent systems detect, interpret, and protect data across cloud and endpoint environments.
In this role, you will play a central part in designing and building a core classification engine that powers multiple security solutions across the platform. Your work will directly influence how different products identify risk, enforce protection, and operate at scale. Youll work at the intersection of large-scale systems and applied AI, turning raw signals into accurate, reliable insights that help customers secure their data with confidence.
Key Responsibilities
Build and scale AI-driven data classification and detection capabilities for next-generation data security products.
Design systems that identify, classify, and protect sensitive data in real time across cloud and endpoint environments.
Lead technical design discussions and influence architecture for large-scale data processing systems.
Partner with product, infrastructure, and other engineering teams to deliver tightly integrated solutions.
Solve complex engineering challenges related to scale, performance, reliability, and operations.
Raise the technical and collaborative bar by mentoring, sharing knowledge, and improving team practices.
Proactively suggest ideas, lead initiatives, and drive continuous improvement across the product and engineering processes.

We're looking for a Senior Backend Engineer to help build and scale the Machine Learning Platform that powers how we use AI across the business. You'll be part of the ML Platform team, designing the infrastructure that lets our data scientists move faster, ship smarter, and operate with confidence in production.
We believe three things matter for every role: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work. Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll:
Design and build the foundational ML platform and AI agents to accelerate data science model delivery across all business units
Architect cloud-native microservices running on Kubernetes, using infrastructure-as-code to automate model deployment and management
Own the end-to-end ML lifecycle, covering training, testing, deployment, and real-time monitoring
Evaluate and choose the right tools and technologies based on workload demands and performance requirements
Collaborate with engineering, data science, and product teams to keep ML projects aligned with business goals
Identify and fix reliability, scalability, and performance gaps before they become problems.