דרושים » הנדסה » Software Engineer - Back-End

we are looking for a Software Engineer - Front-End.
You will own features end to end, from a Figma file or a rough idea through to production. Expect to spend real time on the workflow editor - a node graph that has to stay legible when a customer has built ninety nodes in it - and on the live views that show calls as they happen.
What you'll do
Build and evolve the customer-facing app in Next.js, React and TypeScript
Work on the workflow canvas: node graphs, drag interactions, undo
Make real-time views fast and calm under a few thousand concurrent calls
Take design from concept to shipped, including the details nobody specced
Review, refactor and delete code - the app is young enough to still fix

Harmony is the AI voice venture built inside monday.com. Our agents hold real phone conversations for businesses, and every one of those calls runs through systems we design and build ourselves: real-time audio pipelines, agent orchestration, telephony integrations, and the tools our customers use to build and monitor their agents.
We are a small team that ships fast. Engineers here own features end to end - from design through production - and work shoulder to shoulder with AI researchers turning models into product.
What youll do
Design and build backend services powering live voice conversations: low-latency, real-time, and reliable under load.
Develop the platform our customers use to create, test, and analyze their voice agents.
Integrate with telephony providers, CRMs, calendars, and the wider monday.com platform.
Turn research prototypes into production systems together with our AI scientists.
Own what you ship: architecture, code quality, observability, and performance.

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.

Member of Technical Staff - Islo Engineering teams want background agents that pick up tasks, run on their own, and hand back real results - PRs, fixes, verified outcomes. Islo is the runtime for autonomous coding agents. We run agents in isolated environments connected to real tools with a policy layer that blocks what you didn't approve. Enterprise teams use us to deploy agents they can actually trust. We're a small team in Tel Aviv. Engineers figure out what to build, talk to customers directly, and ship it. We're growing fast and hiring people who want to own product - not just tickets. If you're ready to solve hard problems in a space that's being invented in real time, come join us. As a Member of Technical Staff You will engineer innovative cloud solutions: - Build robust, scalable cloud services in Rust, Python and TypeScript for Islo's agent runtime. - Design and implement secure, isolated agent environments using MicroVMs, virtualization, containers, and other isolation techniques. - Develop Developer -facing surfaces creating clean abstractions over low-level infrastructure. - Build agent orchestration, policy engines, and verification layers that let background agents pick up tasks, use real tools, and hand back results humans can review. - Build resilient, high-performance solutions. You will shape the product: - Own problems end-to-end - from understanding the user's pain to shipping the solution. - Talk to customers regularly: discovery calls, onboarding sessions, debugging their workflows, gathering feedback on what we shipped. - Turn messy, ambiguous requests into clear product decisions - what to build and what to cut. - Write lightweight specs and design docs when it helps the team move fast; skip the ceremony when it doesn't. - Prioritize the backlog based on customer impact and what the team learns in the field. - Demo new capabilities to customers and iterate based on what you learn in the room. - Join customer calls - technical deep-dives, onboarding, troubleshooting live agent runs. - Attend and speak at conferences and meetups on agents, Developer tools, and AI infrastructure. - Be the technical face of Islo with early adopters: answer hard questions, collect real-world failure modes, bring insights back to the team. We encourage you to apply even if your experience doesn't perfectly align with all requirements. We prioritize a positive attitude and potential over an exact match in experience or skills. Juniors are welcome - if you've shipped something, enjoy talking to users, and want to learn how autonomous agents actually run in production, we'd love to hear from you.

We are at the forefront of the AI revolution, delivering brand new accelerated compute platforms for global impact. Our Network Architecture group is seeking a talented and motivated Sr. Software Engineer to build the agentic workflows that our architects use in their daily work. The software at the center of this role is our hardware network simulation environment - you will design multi-step agent workflows over it, engineer the context that grounds them in our own specifications and source code, and optimize their runtime performance. If you are passionate about building the practical infrastructure that brings intelligent agents to life, we want to hear from you.


What you'll be doing:
Build agentic workflows - loops, graphs, and multi-step pipelines - that carry real hardware network simulation and analysis work end to end.
Engineer the context these workflows run on, turning our simulation models, specifications, design documents, and source code into context that makes agents accurate in our domain.
Work closely with network architects to understand their workflows and translate them into agent workflows they use daily.
Optimize the runtime performance of our simulation tooling on these platforms, including execution time, compute cost, and end-to-end latency.
Define evaluation and regression testing for agent workflows, so that changes to a prompt, a graph, or a context source are measurable.
Build observability across agent runs: what the agent did, where it failed, and why.
Champion guidelines for secure and reliable agent workflows, including data handling, access control, and interaction boundaries.
Serve as a key technical resource for solving sophisticated integration issues between agents and internal tooling.

LLM optimization is a young field with no settled playbook, so the optimizations you invent here are genuinely new, and they ship into production rather than a paper. And they matter: real enterprises run enormous volumes of LLM traffic and feel every wasted token, so the work you do lands on live customer requests and solves a problem they actually have. It's about as close to the frontier, and as close to the product, as engineering gets.

03What you'll do
Invent and ship optimizations. Design new strategies across every layer of a request: prompt and context compression, tool pruning, file and dev-command trimming, semantic caching, cache-prefix stabilization. Then take them all the way to the hot path. Each one has to cut tokens on real traffic without degrading output.
Prove every win. Build the evals and the token/quality instrumentation that separate a genuine saving from a plausible-sounding one. An optimization only ships when the numbers back it.
Live in the caching trade-offs. Provider prompt caches only pay off on byte-stable prefixes, and a naive rewrite can cost more than it saves. A lot of the job is knowing exactly when an optimization actually wins: deterministic transforms, per-session decision pins, semantic dedup.
Build and own the gateway that runs them. The real-time proxy that carries production LLM traffic, with streaming, retries and backpressure, executing every optimization on the live request path.
Keep it fast and deploy anywhere. Defend a tight latency budget on the hot path, and package the whole thing so it installs cleanly into any customer's cloud, whether that's AWS, GCP, Azure, containers or Kubernetes, and upgrades without drama.
Own systems end to end. From first commit to code serving live customer traffic, plus the spend-visibility and governance product built on top, with a direct line to the founders.

We are hiring a Senior Robotics Software Engineer to build the system the autonomy runs inside. You own the runtime - ROS2 architecture, module lifecycle, orchestration, state management, configuration, fault handling, and both ends of the stack: World Model ingestion and the Vehicle Interface down to the platform control systems.

You will face hard real-time constraints, embedded compute, and a system that has to keep behaving correctly when parts of it do not. You own the stack across its full depth, from the interfaces at its edges to how the whole thing behaves in the water.

What Will You Do?
Own the autonomy runtime: ROS2 and modern C++ architecture, module lifecycle, orchestration, state management, data flow, configuration, fault handling and recovery
Implement the system's two contracts: World Model ingestion and Vehicle Interface adapters to the platform control systems
Own deployment to the vessel compute: builds, packaging, versioning, configuration management and CI
Work with system engineering and field teams on vessel bring-up, sea trials and debugging in the field
Build logging, recording, replay and observability - the ability to take any run at sea and reproduce it exactly on a desk
Integrate and operate the simulation environment (SIL)
Own reliability, timing and performance of the stack on embedded hardware

You'll be a senior engineer on a deliberately flat, entrepreneurial team. Day to day you'll design and build agentic AI systems - agents, workflows, the orchestration layer that ties them together, and the infrastructure that makes all of it reliable at scale. This is hands-on building, not oversight.
What you'll do
Design and build agentic workflows and the AI systems behind them - agents, the orchestration layer, and the infrastructure that runs them reliably
Take significant, ambiguous areas of the system and drive them from rough idea to working capability
Help scale the platform from a first working workflow to something used across the marketing organization
Contribute to evaluation, quality, and reliability - making sure systems don't just run, but run well
Work directly with the people who'll use what we build, and translate their needs into systems.

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.