דרושים » תוכנה » Staff Software Engineer

our company's product is built around an AI agent that security analysts and detection engineers work with directly. It investigates coverage questions against live enterprise security data, authors and tests detection logic, and tunes noisy alerting.
That agent is already in production with enterprise design partners. Now we need to make it dependable and scalable enough for GA.
You will own that evolution: the agent architecture, its evaluation and quality system, and the production engineering around it. This is a hands-on senior IC role with real architectural authority - you set the technical direction and you write the code.
The agent operates inside customer security environments, where a wrong action can become a customer incident. Correctness, isolation, observability, and evaluation are not polish. They are the product.
What you'll be doing
Agent architecture: Design the evolution from today's production single-agent system to a multi-agent one: orchestration, task decomposition, runtime and framework choices, and a migration path that does not break what design partners already rely on.
Agent capability: Own the prompts, context, skills, and tool design that make the agent genuinely good at detection engineering across multiple security platforms, not just plausible-sounding.
Evaluation platform: Build the harnesses, judges, and golden datasets that turn "the agent feels better" into a number, plus the CI gates that keep regressions from shipping.
Reliability and safety: Keep long-running agentic sessions healthy in production, and build the isolation and guardrails required of an agent working inside enterprise security environments.
Production debugging: Work real failures from production traces, and turn each one into an eval case that can never regress silently.
Technical direction: Make the calls on architecture, sequencing, and quality bar and be accountable for the outcome, including raising how AI-natively the whole team builds.
Cross-team partnership: Partner with product and customer-facing teams on what the agent should do, and with platform teams on the data and integrations it depends on.

Our Applied Science group builds the intelligence behind the marketplace. We turn large volumes of unstructured data into structured understanding, and use it to connect the right people with the right work. We are a small team with an unusually large surface. We own the full path from raw data to production AI systems, and we are actively expanding what that platform can do. In this role, you will design, build and operate AI systems that run continuously in production: large volumes of unstructured data in, models and pipelines in the middle, structured signal that teams across us build on back out. The scope runs from data pipelines and retrieval infrastructure through to model quality, evaluation and cost. This is a hands on senior role, and you will help define how these systems get built here rather than inherit someone else's answer.
What am I going to do?
* Build and evolve our production LLM pipelines, turning unstructured text into structured data that the product consumes.
* Design and operate large scale batch and near real time data processing, including correctness, freshness and cost.
* Build the retrieval and serving layers that make our data usable in real time.
* Decide what runs on which LLM model, and prove the choice with numbers rather than intuition.
* Keep cost and latency predictable as volume grows: throughput, failure handling and monitoring.
* Build agentic workflows that makes the whole team faster, and help set the standards others work to.
Equal opportunities:
We prioritize diversity. We celebrate difference and embed it into every aspect of our workplace and product, as well as our community. We are proud and committed to providing equal opportunity employment to all individuals regardless of race, color, religion, sex, sexual orientation, citizenship, national origin, disability, Veteran status, or any other characteristic protected by law. In addition, we will provide accommodation to individuals with disabilities or a special need.

our company's platform runs inside the security stacks of enterprise customers, processing live detection and telemetry data from SIEM, EDR, and SOAR systems at real scale. Until now, infrastructure has been built and carried by the founding engineering team alongside everything else. You will be the first dedicated owner of it. That means designing our company's cloud foundation across GCP and AWS, building the deployment, scaling, and observability layers from the ground up, and setting the standards the rest of engineering builds on. It also means holding a bar that most startups can defer and our company cannot: we sell to security teams who audit their vendors seriously, so how we run our own infrastructure is part of how we win. This is a hands-on senior role with real architectural authority, and as engineering grows you become the person others learn cloud and infrastructure from.
What you'll be doing
Multi-cloud architecture: Own the design and implementation of our company's multi-cloud architecture across GCP and AWS, including the cross-cloud standards, boundaries, and tradeoffs that keep two providers from becoming twice the complexity.
Infrastructure as code: Build and maintain the entire environment in Terraform, so infrastructure is reviewable, reproducible, and scales without a person in the loop.
Deployment pipelines from scratch: Create the CI/CD foundation that lets a small team ship quickly and safely, with the testing, gating, and rollback paths that make fast releases boring rather than risky.
Kubernetes at data scale: Run and scale the Kubernetes and containerized workloads behind our company's security data processing, where volume, latency, and cost pressure all show up at once.
Security of our own stack: Own identity, access, secrets, network boundaries, and infrastructure hardening to a standard that holds up under customer security review.
Reliability and visibility: Build the logging, monitoring, and alerting layer that tells us something is wrong before a customer does, and make on-call sustainable as the system grows.
Technical direction: Partner directly with the founding engineering team on architectural decisions, and raise the infrastructure and cloud fluency of every engineer who joins after you.

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.

Required Senior Software Engineer (Scala)
About the Role:
A top player in its game and is heading for an exciting year. In this role, you will take an integral part in the creation of a new and innovative SaaS product.
We are building a brand-new team, from the ground up, around a core part of our identity platform. You will be one of the first engineers on it - which means you will shape the architecture, the standards and the way the team works, rather than inherit them.
If you are a talented Senior Backend Engineer that likes to solve complex problems and looking for your next challenge we want you to join our team!
What youll do:
Join a brand-new team, built from the ground up, that owns its product end-to-end - you will have a direct and visible influence on architecture, technology choices, engineering standards and the way we work.
Work both on delivering infrastructure and customer-facing features.
Own features end-to-end: from design, through backend and UI, to production and the customers using them.
Write modular, extendable, testable, efficient and secure code for the platform and microservices - in a functional, strongly-typed Scala codebase where correctness genuinely matters.
Contribute also to the front-end side of the product (in React / TypeScript).
Design and build scalable systems: latency-sensitive, highly-available backend services that run in the critical path of some of the worlds largest banks and retailers - slow and flaky are not options.
Grow with the team as its scope expands into data pipelines and large-scale data processing.
Develop a platform that will affect hundreds of customers worldwide, and billions of end-users worldwide.

As a Full Stack Engineer, youll help shape the brain and heartbeat of our product. This isnt a narrow coding role, youll own problems end-to-end, from first sketch to shipping, and watch your work come alive in production within weeks. Youll join a tight, ambitious team where every engineer helps define both the product and the culture.
What youll do
Work across the stack, from frontend polish to backend resilience.
Collaborate with product and design to shape features, not just code them.
Ship fast, ship often, and still take pride in craft.
Explore and integrate advanced AI (LLMs, GenAI) into a production-grade product.
Turn customer feedback into product improvements that stick.
How we work
In-office, side-by-side, with quick feedback and faster shipping.
Pragmatic and product-first: no feature ships unless it makes a real impact.
Supportive but demanding: we hold a high bar and help each other reach it.
The tools we use (today - youll help shape tomorrow)
Powering the logic that makes hardware data come alive in our backend is Python. On the frontend, React and TypeScript give users a simple, intuitive way to work with complex information. Everything runs in the cloud - AWS and GCP - with containerized microservices (and Kubernetes keeping the gears turning smoothly) ensuring we can ship fast and scale seamlessly. For intelligence, we weave in LLMs and data pipelines to unlock insights from documents. And for resilience, our real-time monitoring keeps an eye on the moving parts - so the system stays as reliable as the products it supports.

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're hiring a Senior/Principal Site Reliability Engineer to own production reliability for Cortex Agentix Endpoint Security (following an acquisition of KOI Start Up) as it scales. You'll define and operate our SLOs and error budgets, lead high-severity incident response, and ensure our Kubernetes and AWS infrastructure stays stable under growth. You'll also build and supervise the AI agents that handle routine alert triage and monitor tuning, focusing your own time on the reliability engineering that requires human judgment. This role is a strong fit for someone who treats reliability as an engineering discipline and enjoys ownership, incident command, and applying AI to operational work.
Your Impact:
Own reliability as an engineering discipline - define SLIs, set SLOs, and run error-budget-based decision-making so "how reliable are we" becomes a number that governs how fast we ship.
Own production incidents end-to-end - lead response, mitigation, and resolution for high-severity incidents, and drive blameless postmortems that feed real fixes back into the system.
Own the reliability and capacity of production infrastructure as we scale - forecasting headroom, validating scaling behavior under load, and keeping latency and error rates within SLO.
Run and evolve Kubernetes environments so releases and infra changes are safe by default across hundreds of tenant apps.
Own, build, and supervise our SRE AI agents that triage alerts, review monitors, resolves and summarize incidents. Set and expand the trust ladder that governs what the agents do autonomously, what needs approval, and what stays human. This is a core part of the role.

We're looking for a DevOps / Platform Engineer to own our infrastructure end to end- both sides of it.
Side one is our multi-tenant SaaS on AWS: you build it, you run it, you keep it fast, secure, and up. Side two is the part that makes this role unusual - our enterprise customers deploy Avon AI inside their cloud (and sometimes fully air-gapped, on-prem environments). You'll own that too: packaging the platform, running the installation with the customer's infrastructure and security teams, and being the person on the call when their environment doesn't look like anyone's reference architecture.
This is a customer-facing engineering role. You'll be in rooms with enterprise IT, security, and platform teams- walking them through our architecture, answering security review questions, and unblocking deployments. If you want a pure behind-the-scenes infra job, this isn't it. If you like owning infrastructure and being the trusted technical voice in front of a customer, read on.
You'll be our first dedicated DevOps hire, which means you inherit real systems in production and a lot of room to shape how they evolve.
Key Responsibilities
EKS, networking, data stores, CI/CD, cost, and uptime. Build and evolve it with Infrastructure as Code.
Maintain and improve our Helm charts and container distribution so Avon AI installs cleanly in a customer's Kubernetes cluster.
Plan and execute installations in customers' private clouds and on-prem/air-gapped environments, working hands-on with their infrastructure teams from kickoff through go-live.
Support security reviews and architecture discussions, and translate enterprise IT constraints back into our roadmap.
IAM, network segmentation, secrets management, WAF, and the controls enterprise customers audit us on.
Metrics, logs, tracing, and alerting for our SaaS, and self-contained monitoring for customers who won't ship telemetry outside their network.
CI/CD pipelines, ephemeral PR sandboxes, release automation, and local development so engineers ship quickly and safely.
For our SaaS tenants and for deployed customer installations, including on-call ownership of what you build.