דרושים » תוכנה » Senior Software Engineer Runtime Internals

Were building a runtime code sensor that operates where most tools dont: inside running applications. Our goal is to give engineers and AI agents real-time, high-fidelity visibility into how code actually behaves in production - under real load, real traffic, and real failures.
This role blends deep systems engineering with applied research. Youll dive into runtime internals, explore undocumented behavior, design low-overhead instrumentation, and turn research insights into production-grade components that safely run in customer environments. One day you might analyze GC or JIT behavior; the next, design tracing mechanisms that survive real-world distributed systems.
If you get excited about runtime internals, enjoy breaking (and fixing) complex systems, think like both a researcher and a production engineer, and care deeply about performance, safety, and correctness - youll feel right at home here. This is a hands-on, high-impact role for engineers who want to ship technology that engineers actually trust to run in their most critical services.
Engineering Excellence / Mindset
Ability to anticipate technical risks, identify bottlenecks, and drive long-term engineering improvements.
Takes ownership of code quality, documentation, reliability, and observability.
Comfortable working with product teams to balance technical trade-offs with user and business needs.
Autonomous and proactive; capable of mentoring others or leading technical initiatives.

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.

The Software Engineer - Cloud will join a foundational and growing cloud team with meaningful ownership over critical platform areas. You will help build the software systems behind a hybrid edge-cloud architecture powering real-time video streaming, recording, and AI processing at global scale. This role sits within the team led by the Head of Cloud, which owns a broad software domain across cloud, mobile, web applications, and related clients.
Youll work on a distributed backend ecosystem that connects edge devices with cloud services and customer-facing applications, with a strong focus on performance, reliability, and low-latency user experiences. This is a strong fit for an engineer who enjoys meaningful ownership, thrives in a fast-moving startup environment, and is comfortable contributing to systems that support customers worldwide. You will have a chance to work alongside teammates across the U.S., Israel, and Europe, contributing to a platform with broad impact and increasing customer demand.
Location & Travel
Hybrid Schedule:
Two days a week working from home.
Ramat Gan office, located just outside Tel Aviv and close to the train station.
Includes biweekly travel to our Caesarea office.
Responsibilities
Build and evolve the core cloud platform that supports real-time video streaming, recording, and AI processing across a global customer base.
Design, develop, and maintain distributed backend services that connect edge infrastructure with cloud systems and customer-facing products.
Develop and support data pipelines for both real-time and batch processing of video and AI-related workloads.
Work on systems responsible for ingestion, storage, retrieval, and secure handling of large-scale video data in a multi-tenant environment.
Architecting multi-tenant, highly available systems across regions in a cloud environment
Collaborate closely with Edge engineers and adjacent teams to enable seamless integration across the broader platform.
Use cloud provider services and SDKs as part of day-to-day development, including work across core cloud capabilities rather than a single isolated service.
Contribute to backend development in JavaScript/Node.js and, depending on background and team fit, potentially support growing work in Go as part of the cloud stack.
Participating in code reviews, debugging, and optimizing performance across distributed systems
Help support a production environment where reliability matters, including situations that may require responsiveness outside standard hours when cloud issues have broad impact.
Our infrastructure is powered by Google Cloud.
Other duties may be assigned.
We dont do cookie-cutter. If youve got the grit, the drive, and the track record-especially in security or AI-we want to hear from you. Even if you dont check every box, lets talk.

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 are looking for a Senior Software Engineer to join our Core Engineering group. The group is responsible for the real-time, low-latency infrastructure that powers our fraud decisions and external APIs.

Our systems process billions of requests every day, ensuring high availability, security, and performance at global scale.

In this role, youll work on core backend components such as our decision engine, ingestion and enrichment pipelines, schema management systems, and self-serve API platform. The software you build will power critical business decisions and directly serve some of the worlds largest merchants.

This is a high-impact, high-ownership position for an engineer who thrives on solving complex distributed systems challenges, cares deeply about production-grade quality, and wants to shape the foundation of our decisioning platform.


What you'll be doing:
Design, build, and scale backend systems that power our real-time decisioning and APIs.
Own projects end-to-end - from design and implementation to production rollout and monitoring.
Ensure systems are low-latency, fault-tolerant, and high-throughput across distributed environments.
Enhance observability, reliability, and developer experience through strong operational and tooling practices.
Collaborate with Product, analysts, data scientists, and infrastructure teams to drive innovation across Forters decision ecosystem.
Participate in technical discussions and customer interactions, providing expertise and clear communication when supporting enterprise integrations.

Were looking for a Senior Applied AI Engineer who combines deep data science expertise with the engineering skills to turn research into reliable, production-ready products.
Youll be a hands-on technical leader, owning significant AI capabilities from problem definition, academic survey, and system design through research, experimentation, deployment, and continuous improvement. Your work will span classical machine learning, large-scale data analysis, and AI agents that power brand intelligence, market research, and performance marketing.

You should have a track record of driving complex projects, not just contributing to them, and be comfortable making technical decisions, navigating ambiguity, and delivering in a fast-moving startup environment. Youll build systems that Fortune 500 marketing teams rely on to make consequential business decisions.
Responsibilities
Own AI capabilities end to end. Translate business and product needs into well-defined problems, research plans, and technical designs. Take solutions from initial exploration through production deployment and ongoing improvement.
Develop and improve our core algorithms.
Build production-grade AI agents - performance marketing, market research agents, auto-ML agents.
Turn research into maintainable software. Build reusable modules, data pipelines, and services with clear interfaces, automated tests, and robust deployment practices-not just standalone prototypes.
Own quality and performance in production. Monitor system behavior, investigate failure cases, and continuously improve accuracy, reliability, latency, and cost as usage and data volumes grow.
Drive technical decisions and execution. Choose the right approach for each problem, balancing statistical methods, classical ML, and LLM-based systems. Make explicit trade-offs between research depth, delivery speed, and operational complexity.
Provide hands-on technical leadership. Partner with product and engineering to shape priorities, lead technical initiatives, review designs and code, and mentor teammates.

We are looking for a Senior AI Engineer to design and build production-grade, LLM-powered systems. You'll work at the intersection of software engineering and applied AI - shipping agents, RAG pipelines, and tool-using systems that solve real problems at scale. This is a hands-on, high-ownership role for someone who thrives at the frontier of what's possible with modern LLMs and isn't afraid to write the glue, the infrastructure, and the prompts that make it all work.
This is a **cross-functional, company-wide role**. You won't be embedded in a single product team - instead, you'll partner with every department to identify high-leverage opportunities and build AI-powered tools and workflows that boost productivity and efficiency across the entire organization.
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
What You'll Do:
- Design, build, and operate LLM-powered applications, agents, and workflows end-to-end - from prototype to production.
- Architect retrieval, context engineering, and tool-use strategies that make models reliable, accurate, and cost-efficient.
- Integrate LLMs with internal services, third-party APIs, and data stores to automate complex business and engineering workflows.
- Build, evaluate, and continuously improve evaluation harnesses for non-deterministic systems.
- Collaborate closely with product, research, and platform teams to translate ambiguous problems into shipped capabilities.
- Stay ahead of the rapidly evolving LLM ecosystem (models, frameworks, agentic patterns) and bring the best ideas into our stack.

As a Senior Applied AI Engineer, you will lead the bridge between cutting-edge AI capabilities and production-grade software. You will design, build, and optimize the intelligent systems, agentic workflows, and LLM-driven architectures that power our companys conversational products.
Also, you will combine software engineering rigour with state-of-the-art Generative AI techniques - optimizing for conversational quality metrics, latency, and system reliability in high-scale production environments, serving millions of users. We are looking for an engineer who is hungry for AI innovation, eager to pioneer new generative capabilities, and passionate about shipping impactful AI solutions.
In this role, you will:
Design & Scale AI Systems: Architect and deploy high-performance LLM orchestration systems, agentic workflows, retrieval-augmented generation (RAG) pipelines, and AI microservices.
Bridge AI Research & Production: Transform frontier LLM research, foundation models, and generative techniques into robust, production-ready features with high availability and low latency.
LLM Evaluation & Guardrails: Design and implement automated LLM evaluation (evals) frameworks, benchmark suites, and guardrail policies to continuously measure accuracy, reduce hallucinations, and ensure safety across product flows.
Optimize Performance & Cost: Lead latency, throughput, and token-cost optimization strategies across commercial APIs and open-source models.
Set AI Engineering Standards: Elevate software craftsmanship across the team through architectural reviews, code quality, and LLMOps best practices, utilizing the latest AI tools.
Drive Product Innovation: Collaborate closely with product and engineering teams to translate complex human resource and conversational challenges into intelligent software solutions.

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 Full Stack Engineer to build our enterprise web application and control plane alongside our senior engineers. You will build the services, APIs, and interfaces that let engineering leaders monitor, understand, and control autonomous data workloads in real time. 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
* Ship features end to end across the control plane: services, APIs, and the interfaces built on top of them
* Build scalable, low-latency APIs over live telemetry from production data and AI workloads
* Build high-performance, real-time visual interfaces and explainability tools for monitoring an autonomous data platform
* Partner closely with backend, AI, and distributed systems engineers to ship complex, mission-critical platform features
* Own quality for what you ship: testing, CI/CD, observability, and the operational bar for a product enterprise customers depend on
What We Offer
* A chance to build the core execution engine for a new category of autonomous data platform — a product already running inside Fortune 500 environments Real ownership from day one : you own what you ship end to end, and you grow into owning whole domains of the control plane Engineering problems that are genuinely hard : real-time telemetry at enterprise scale, low-latency APIs, and interfaces that make autonomous decisions readable A talent-dense team : direct access to the founders and to the engineers who designed the platform, and a bar that pulls you up Top-of-market compensation and meaningful equity Ready to build the control plane for an autonomous data platform? Hit Apply.