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we are looking for a AI Engineer.
Our R&D teams build and own the features that power platform - from deep code analysis to risk detection to developer-facing workflows. AI isn't a separate initiative here; it's how we build. Every engineering team is actively embedding LLMs, AI agents, and generative AI into the products they own, moving from experimentation to production and keeping things running reliably once they're there.
What You Will Do
Build and ship end-to-end AI-driven features and agentic workflows- from experimentation through validation to production deployment (Python and C#).
Design scalable backend services that support production-grade agentic AI capabilities.
Develop and improve solutions powered by LLMs, AI agents, multi-agent systems, and generative AI frameworks.
Evaluate agentic architectures and model performance, owning monitoring, reliability, and continuous improvement in production.
Collaborate cross-functionally with software engineers, data scientists, and analysts to drive AI innovation across the platform.

We are looking for a Senior Software Engineer to help build the core of our AI security platform and AI Control Plane.

You will build systems that help enterprises understand, monitor, and control how AI agents and LLM-based applications operate across their organization. We expect engineers to work in an AI-native way: leveraging and orchestrating AI agents to accelerate design, implementation, testing, debugging, and iteration, while owning the quality of the final result.

This role requires strong ownership, system design judgment, and the ability to turn complex AI-security problems into reliable production systems.

What you will do
Leverage and orchestrate AI agents and LLMs to design, build, test, debug, and ship core platform capabilities.
Build systems for monitoring, governing, and controlling AI agents, LLM applications, tool usage, prompts, context, policies, and runtime behavior.
Turn ambiguous AI-security problems into simple, scalable, production-grade systems.
Own technical decisions from design through production, working closely with Product, Security, and Engineering.

Security teams are not short on tools. They are short on time, alignment, and the ability to actually close exposure. That's why most breaches could have been prevented with a tool that was already in use.
our company was built to change that.
We are the first Agentic Exposure Ops Platform, designed to prevent the preventable breach by turning fragmented signals into coordinated action. Our agents investigate risk, drive remediation, and verify that issues stay closed, continuously, without adding overhead.
we are helping organizations move from reactive workflows to continuous execution, replacing manual effort with systems that actually move the work forward.
At our company, engineering isn't a service function it's where product happens. We're looking for a Fullstack (Product) Engineer who lives at the intersection of craft and product sense:You care as much about why we're building something as how it feels in the user's hands. You're an engineer who connects naturally with other engineers, and who enjoys mentoring and ramping up the people around you.
You'll own experiences end-to-end from the first PRD conversation to the KPI dashboard weeks after ship. You'll shape our component library, raise the bar on our frontend infra, and help define what "good" looks like across the R&D org. This isn't a role where you get handed pixel-perfect mocks and a closed ticket. You'll have opinions, and we'll want to hear them.
What you'll do
Craft the experience. Design and build polished, performant UI in Vue 3 (Composition API) from the tiny interaction details to the data layer behind them.
Own the full journey of a feature. Partner with Product on the PRD, define the KPIs that actually matter, ship it, then track whether it moved the needle and iterate honestly if it didn't.
Shape the component library. Evolve our patterns, primitives, and the infra that lets the whole team build faster without sacrificing quality or consistency.
Go full-stack when it counts. Write Node (NestJS) services and work across our data stack (Postgres, Snowflake, ClickHouse) to deliver features truly end-to-end.
Push AI-assisted development forward. Build the guardrails, skills, and workflows that let engineers contribute code quickly and safely you'll help make AI a force multiplier for the whole team, not a liability.
Raise the bar org-wide. Your taste in UX, and code quality should ripple well beyond your own team.

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.

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.

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 Autonomous execution is a new category, and we are the ones defining it — already running in production inside Fortune 500 environments , where being wrong is not an option. The team is deliberately talent-dense ; every hire changes what we are able to build next. We are looking for a Senior Full Stack Engineer to own Zipher’s entire product surface — the control plane that turns autonomous decisions into something engineering leaders can see, trust, and act on. You will own it end to end: the services and APIs behind it, and the real-time interfaces built on top of them. This is a backend-heavy role . It is best suited for candidates whose primary expertise and passion lie in backend development
What You’ll Do
* Own the product surface end to end : architecture, services, APIs, and the real-time interfaces built on top of them
* Set the technical direction of the control plane — stack, data contracts, and the patterns every engineer after you builds on
* Build high-throughput services that turn live telemetry from production data and AI workloads into decisions, and the explainability layer that makes those decisions readable
* Work directly with the founders on what gets built next, and lead the technical moves that follow — from what enterprise customers need to the architecture that answers it
* Drive quality end to end: testing, CI/CD, observability, and the operational bar for a product Fortune 500 engineering teams run in production
What We Offer A product that is already winning : a new category of autonomous data platform, in production inside Fortune 500 environments A domain of your own : you lead it end to end — the architecture, the stack, and the patterns every engineer after you builds on A seat on the core team : you are one of the engineers deciding what the platform becomes, not one implementing someone else’s decisions Engineering problems that are genuinely hard : real-time telemetry at enterprise scale, distributed decisions, and an explainability layer teams trust in production Engineers worth learning from : a deliberately talent-dense team, direct work with the founders, and a bar that pulls everyone up Room to grow and to lead : your ownership widens as the platform does, and the people who lead moves here keep leading them Top-of-market compensation and a meaningful equity package Ready to own the control plane for an autonomous data platform? Hit Apply.

We are looking for an AI Solution Engineer to design, implement, deploy, and operate AI-powered solutions for enterprise customers.

This is a hands-on, multidisciplinary role combining AI, integrations, customer-facing work, and technical problem-solving. Youll work directly with customers from discovery and solution design through implementation, production deployment, monitoring, and optimization.

Youll build solutions including Voice AI Agents, Text Agents, conversational workflows, and AI-powered conversation analysis, while supporting customers using our SaaS platform.

Key Responsibilities
Design, configure, and deploy Voice AI Agents, Text Agents, and conversation analysis solutions.
Translate customer business processes and requirements into working AI solutions.
Own customer implementations end-to-end, from technical discovery and solution design through production deployment.
Integrate us with APIs, CRM systems, telephony/PBX platforms, databases, knowledge bases, and other enterprise systems.
Configure prompts, workflows, business logic, AI models, tools, and integrations according to customer requirements.
Monitor production AI agents, troubleshoot technical issues, perform root-cause analysis, and continuously optimize performance.
Support enterprise customers using the SaaS platform.
Work closely with Product, R&D, Sales, and Customer Success, bringing insights from customer implementations back into the product.
Manage multiple customer implementations simultaneously and take ownership through successful production delivery.

Forward Deployed Engineering sits at the frontier of that work. We embed with our most strategic enterprise customers, running on-prem, air-gapped, and heavily regulated environments, and own the technical arc from discovery through production.

Your day might include designing a solution architecture for a high-impact agentic use case, debugging a production routing issue deep in our codebase, deploying a new MCP server with a customer team, or aligning with a CTO on a rollout plan; all in service of outstanding outcomes and rapid time to value for the organizations we work with.

This is a founding function. The first FDEs will define how we conducts field engineering: the standards, playbooks, and technical bar. The work is hands-on, commercially scoped, and high-leverage: youll partner closely with Product, Research, Platform, Security, and GTM, and what you learn in production directly shapes what the core team ships next. If you thrive under ambiguity, make fast and sound decisions when the stakes are high, and get energy from closing the gap between what customers hit in production and what we build next, this role is for you.

In This Role You Will
Own technical delivery across multiple deployments from first prototype to stable production, including core engineering work that unblocks strategic accounts.
Lead deep technical diagnosis and remediation in our codebase and production environments, model routing and gateway behavior, large-PR scaling, multi-pass behavior, performance and reliability issues.
Build customer-specific extensions (MCP servers, agent skills, platform integrations) that deliver immediate value and become durable product capability; upstream them into the main roadmap where appropriate.
Embed closely with customer engineering teams: serve as their senior technical counterpart for hands-on debugging, architecture reviews, and joint implementation.
Scope work, sequence delivery, and remove blockers early; make deliberate trade-offs between scope, speed, and quality to protect delivery timelines.
Partner with Product, Research, and Platform to convert account learnings and eval-driven feedback into roadmap items, specs, and prioritized engineering work.
Codify working patterns into tools, playbooks, runbooks, and reproducible benchmarks that Support and account teams can operate independently and help scale the field engineering function across the organization.