דרושים » תוכנה » Senior Software Engineer in Test - AI & Quality Infrastructure

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.
"our company's data management vision is the future of the market."- Forbes
we are the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, our company takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless company ronauts who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
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.

We're looking for a Senior DevOps Engineer with a strong Developer Experience (DevEx) mindset, someone who genuinely enjoys making developers more productive by building and improving the tools, infrastructure, automation, and workflows they use every day.
You will work across CI/CD, developer tooling, automation, infrastructure, observability and productivity. Your primary focus will be making development and delivery faster, simpler, more reliable, and more cost-effective.
We need someone who can independently identify developer pain points, proactively discover opportunities for improvement, and turn them into scalable engineering solutions. You will be expected to measure the impact of your work and continuously improve critical metrics such as CI feedback time, pipeline reliability, deployment time, infrastructure cost, and overall developer productivity.
This role is a perfect fit for someone who thinks far beyond just "keeping the infrastructure running" and is excited about revolutionizing the entire engineering experience.
Your Impact:
You will tackle high-impact engineering challenges across our platform. Representative areas you will own and work on include:
Optimize CI/CD Pipeline Velocity & Stability
Improve CI Stability: Leverage AI to automatically detect recurring test failures, dynamically disable problematic tests, and open Jira tickets for follow-up.
Automate Workflows: Utilize AI to automate merge conflict resolutions and keep the merge train moving smoothly.
Accelerate CI Velocity: Architect workflows to parallelize work both across jobs and within jobs. Introduce highly effective caching strategies and local Artifactory mirrors to drastically reduce build and dependency-fetch times.
Optimize CD: Reduce container image sizes and accelerate deployment times. Partner with QA to introduce and streamline automated regression testing against tenants.
Drive Repository Security & Maintenance
Improve Security Posture: Automate the identification and remediation of Go and Python dependencies with known CVEs.
Automate Maintenance: Design systems to automatically handle Go and Python version upgrades across the codebase.
Ensure Performance: Automate performance testing to proactively detect and alert on performance regressions before they hit production.
Cloud Infrastructure & Cost Engineering
Reduce Infrastructure Costs: Identify and implement innovative opportunities to reduce overall infrastructure and resource consumption.
Resource Efficiency: Introduce mechanisms to make our "slim tenants" even more resource-efficient for development and testing.
Smart Observability: Re-architect our logging strategy by streaming GCP logs to more cost-effective sinks instead of relying exclusively on Cloud Logging.
IaC Governance: Act as a gatekeeper for infrastructure quality by reviewing Terraform Merge Requests (MRs) for correctness, efficiency, maintainability, and strict adherence to engineering standards.

As an AI Engineer at our company, you will own the intelligent decision-making pipelines that turn complex workspace telemetry into autonomous security actions. You will design, build, and deploy the autonomous reasoning workflows and advanced data classification systems that drive our company's preventive operating model. Your focus will be on creating resilient, production-grade AI systems capable of deep policy comprehension, real-time prevention at the point of adoption, and autonomous remediation of existing risks.
This is a ground-floor opportunity to shape the AI strategy of a fast-growing cybersecurity company alongside a lean, elite team of builders.
WHAT YOULL DO
End-to-End Ownership: Own our AI capabilities entirely from initial research, architectural design, and prototyping, through to production deployment, optimization, and continuous monitoring.
Design & Build Agentic Workflows: Architect multi-step AI agents capable of autonomously investigating workspace risks, interpreting complex enterprise policies, and taking precise remediation actions.
Integrate Multi-Faceted ML: Bring innovation and creative thinking to our core engine. Implement diverse ML models across our entire research and product pipeline-utilizing clustering, text extraction, document analysis, and tabular data classification.
Ship Production-Grade AI: Build high-throughput, resilient, and fault-tolerant production code. You will ensure our AI pipelines and agentic workflows are highly predictable, deeply observable, and built to scale under enterprise-grade loads.
Implement Guardrails & Evaluation: Build continuous evaluation frameworks to benchmark agent accuracy, mitigate hallucinations, and enforce strict data security/privacy guardrails.

Were looking for a Senior Infrastructure Engineer who views "Infrastructure as Software." In 2026, we dont just manage servers; we build high-performance environments that allow multi-agent systems to operate at scale.
You will be a core member of the R&D team, blending deep DevOps expertise with the coding rigor of a Backend Engineer. You arent just "configuring" AWS; you are architecting the distributed systems and data pipelines that power our autonomous security brain. Your mission is to ensure that while our agents are evolving and taking actions, our underlying platform remains immutable, observable, and infinitely scalable.
What You'll Do
Design, build, and operate our company's cloud infrastructure using AWS, Kubernetes, and Infrastructure as Code.
Build internal tools and platform services using Python and Go to improve developer productivity and system reliability.
Own infrastructure automation with Terraform, Pulumi, and modern cloud-native tooling.
Partner closely with Backend, Data Science, and Security Engineering teams to build scalable, reliable platforms.
Improve observability, monitoring, and incident response across distributed production systems.
Design and optimize infrastructure for performance, scalability, security, and cost efficiency.
Help shape engineering best practices, platform architecture, and developer experience as our company continues to grow.

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.

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.

At Check Point, what you do matters. Every day, we protect over 100,000 organizations worldwide from increasingly sophisticated cyber and AI-driven threats, securing their AI transformation.
Our prevention-first approach safeguards hybrid networks, cloud environments, digital workspaces, and AI systems, stopping attacks before they happen.
This is where innovation meets real-world impact. Youll help customers across industries operate with confidence in a rapidly changing digital world, working alongside smart, curious people who take ownership, challenge assumptions, and solve complex problems.
Were proud to be recognized by TIME, Newsweek, and Forbes for excellence and workplace culture.
What really sets Check Point apart is the opportunity to grow, contribute, and help companies navigate their AI transformation securely.
If youre excited to work at the forefront of AI-driven security on a global scale, this is the place to do it.
Key Responsibilities
About the Team
We are looking for a passionate Full Stack Engineer to join our team, building modern, scalable, and intuitive web applications.
Our team owns user-facing capabilities end-to-end, from rich React experiences and frontend architecture to API integrations and supporting backend services. We work closely with product, UX, platform, and engineering teams to turn complex requirements into simple, reliable, and high-quality solutions.
AI is an integral part of how we work. We are looking for engineers who know how to use modern AI tools effectively and responsibly throughout the development lifecycle, including problem-solving, coding, debugging, testing, and code review.
This is an opportunity to take ownership of meaningful features, influence technical decisions, and help shape both our product and the way our team builds software.
Your Impact & Responsibilities
Design, develop, and maintain scalable web applications using React and TypeScript.
Build and integrate APIs and backend services that support complex user-facing workflows.
Own features end-to-end, from requirements and technical planning through implementation, testing, deployment, and production monitoring.
Create reusable frontend components and contribute to a consistent and maintainable application architecture.
Work with API contracts, asynchronous data flows, error handling, authentication, and application state.
Improve application performance, usability, reliability, security, and developer experience.
Use AI-assisted development tools and workflows to accelerate delivery while maintaining high standards of correctness, security, and code quality.
Review and validate AI-generated outputs rather than relying on them blindly.
Collaborate closely with product managers, UX designers, backend developers, and other engineering teams.
Contribute to technical discussions, architecture decisions, code reviews, and engineering best practices.

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.

As the leading provider of Talent Orchestration technology, HiredScores artificial intelligence, automation, and deep integrations empower the worlds most innovative companies to drive critical business outcomes in recruitment, diversity hiring, and internal mobility.
Now part of Workday, HiredScore is seamlessly integrated into the Workday ecosystem, streamlining complex HR processes and delivering AI-driven insights that allow recruiters to focus on what matters most: top talent.
At our Israeli site, we operate with an agile, high-trust culture. We believe our employees are our greatest asset, and we foster an environment of continuous learning, fast feedback, and collaborative problem-solving.
The Opportunity
We are looking for a Senior Backend Engineer to join the Sourcing Team within our Core Engineering group in Israel. This team is the architectural engine behind our candidate-matching solutions, finding the best roles for candidates and the best talent for organizations.
You will lead the design of robust, scalable systems leveraging Python, React, Kubernetes, MongoDB, and Celery, while integrating MS Teams to create a seamless communication experience for recruiters and candidates alike.
Work Model: Hybrid (3 days in-office, 2 days remote) at our Israel site.
About the Role
Architectural Leadership: Design and implement high-performance, scalable solutions for global enterprises using code generation. You will take full ownership of the lifecycle-from initial conceptualization and architectural design to implementation and global delivery.
System Evolution: Drive the evolution of our distributed systems built on Kubernetes, ensuring they meet the demands of a rapidly scaling client base.
Production Excellence: Set and maintain the gold standard for production systems. You will champion best practices in testing, observability, and proactive alerting to ensure mission-critical stability.
AI Integration: Partner closely with Product Managers and Data Scientists to embed cutting-edge AI and machine learning capabilities into our core offerings.
Technical Mentorship: Act as a force multiplier for the team. You will mentor and upskill fellow engineers, fostering their technical growth and execution potential through code reviews, design docs, and pair programming.
Strategic Input: Bring your deep industry experience to our agile processes, helping the team adapt, grow, and innovate.