דרושים » תוכנה » Senior Software Engineer

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.

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 are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.
Operate and debug object store-backed data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

Join our AI Platform group as an AI Engineer in the AI Core team and help build the next generation of AI-powered networking and security solutions at our company.
The AI Core team is responsible for developing AI applications, intelligent agents, and backend systems that integrate directly into our company products and workflows. As part of our companys strategic AI direction, the team focuses on turning modern GenAI capabilities into scalable production systems that help customers operate, troubleshoot, investigate, and manage complex networking and cybersecurity environments more effectively.
This role combines strong software engineering, modern GenAI technologies, and deep product impact. Youll work on building production-grade AI systems, integrating LLMs and agentic workflows into large-scale products, and helping shape how AI transforms cybersecurity and networking operations across the company.
We are looking for engineers who are excited about building real-world AI systems in production, not just experimenting with models, but designing scalable applications, integrating intelligent agents into complex products, and solving challenging engineering problems with direct customer impact.
Key Responsibilities
Design, develop, and maintain AI-powered applications, agents, and backend systems
Build intelligent workflows and agentic systems integrated into our company networking and security products
Develop scalable APIs, services, and infrastructure supporting GenAI applications in production
Integrate LLMs, RAG pipelines, vector databases, and orchestration frameworks into robust production systems
Collaborate closely with AI researchers, software engineers, infrastructure teams, and product groups to deliver end-to-end AI solutions
Improve scalability, reliability, observability, and operational excellence of AI systems
Explore and adopt modern AI engineering methodologies, frameworks, and tooling
Participate in architectural and technical decisions shaping the future of AI across our company products.

As a Senior Site Reliability Engineer at our company 911, you'll own the infrastructure that keeps our platform reliable, scalable, and secure - work that directly supports mission-critical 911 systems used by public safety agencies. You'll drive infrastructure-as-code practices across AWS, lead observability efforts through Datadog, and bring modern AI-assisted engineering approaches into how the team builds and operates.
What You'll Do
Own and evolve AWS infrastructure using Infrastructure-as-Code (Terraform / Terragrunt)
Architect and scale AWS environments
Deploy, scale, and manage containerized workloads using Kubernetes and Docker; contribute to HA/DR architecture and platform strategy
Lead deployment and release processes using Argo (reference JD also names Bitbucket, Jenkins as part of the CI/CD toolset).
Define and enforce SLOs, SLIs, and error budgets; drive toil reduction across the platform
Drive full utilization of Datadog for monitoring, dashboards, and alerting across the platform (reference JD also names Prometheus, Grafana as potential observability tooling)
Build self-service internal developer platforms that empower teams to ship faster.
Take end-to-end ownership of infrastructure projects - define success criteria, execute, and measure outcomes.
Partner cross-functionally with engineering teams (e.g., network engineering, Dev owners) on long-term technical planning.
Bring AI-assisted engineering practices (e.g., Claude, MCP integrations) into daily workflows to improve team efficiency
Document work and provide cross-training to peers.
Resolve JIRA tickets across Cloud, CI/CD, deployments, and monitoring.

We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across the platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how evolves from AI-enhanced internal tools to customer-facing AI products.

We are looking for a Senior II Software Engineer to join the CX Platform team, the foundational engineering team powering our entire Customer Experience group. This is a high-impact, hands-on role at the intersection of backend engineering, AI infrastructure, and customer-facing product.

You'll work across the full platform stack (backend services, data pipelines, security, cost, and scale) with a meaningful and growing focus on AI infrastructure. We own the agentic platform for the entire Product Offering group: from building the LLM infrastructure and agentic workflows to ensuring they're reliable, observable, and safe in production.

What you'll be doing:
Own AI infrastructure for the Product Offering group. Design, build, and evolve the shared AI platform (agentic workflows, LLM integrations, observability, and guardrails) that CX product teams build on.
Ship agentic features end to end. Lead development of AI-driven capabilities using LangChain, LangFuse, and AWS Bedrock, from architecture through production deployment and monitoring.
Drive platform architecture. Set the technical direction for the CX backend (services, data pipelines, API patterns) with an eye for scalability, reliability, and developer experience.
Own core data foundations. Design resilient data-access patterns across Snowflake, Elasticsearch, Kafka, Redis, and MySQL; keep pipelines fast, fresh, and reliable.
Mentor and elevate. Help engineers across the CX group grow in backend craft, AI engineering, and system design thinking.
Collaborate cross-functionally. Work with product, design, and customer-facing teams to turn ambiguous problems into well-scoped, high-quality solutions.

Required Senior Developer (DevOps and Infrastructure)
We're revolutionizing how the world moves money with our unified global payments platform. Our team is at the forefront of ensuring the security and resilience of this critical infrastructure, and we're looking for a strong DevOps engineer to play a pivotal role in designing and implementing robust solutions across our infrastructure and applications.
If you have a passion for building secure-by-design systems, a deep understanding of both infrastructure and application principles, and the ability to translate complex requirements into actionable blueprints, we want to hear from you. You'll be instrumental in shaping our infra and security landscape, ensuring our platform remains a trusted and secure environment for our global users.
What You'll Be Doing:
You will work with Python and APIs, codifying infrastructure, and lead the architectural design and implementation of solutions for our cloud infrastructure, network, and applications.
Constantly push optimizations and best practices. Define and maintain security standards, frameworks, and best practices across the organization.
Collaborate closely with engineering, product, and operations teams to integrate security seamlessly into the development lifecycle and infrastructure deployments.
Evaluate and recommend security technologies and tools to enhance our security posture.
Develop security reference architectures and patterns to guide engineering teams in building secure solutions.
Participate in threat modeling and risk assessment activities to proactively identify and mitigate potential security threats.
Provide expert guidance and mentorship to engineering teams on security-related topics.
Stay current with the latest security trends, threats, and technologies, and translate them into actionable strategies for us.

Were looking for driven and talented people like you to join our R&D team and our mission to change the future of cloud security.

As a Senior Software Engineer on the KSPM team, you will join a mission-critical group building and scaling one of the companys core and fastest-growing security products. Our team enables customers to secure their Kubernetes environments across every major cloud provider, delivering deep visibility into cluster misconfigs, RBAC risk, admission control, compliance drift and container vulnerabilities.

In this role you will design the backend services and data models that discover, onboard, scan, and represent K8s workloads, APIs, and configurations at scale. You will own core services end-to-end, drive architectural improvements and partner with security researchers to turn complex threat vectors into actionable insights.

We are looking for backend engineers who care deeply about software design, cloud-native infrastructure, and container security. This is a high-impact role with real ownership - lead features end-to-end, mentor teammates, and help shape the technical direction of our KSPM offering.

What Youll Do:
Design & build at scale: Design, implement, and maintain scalable backend services that discover, onboard, scan, and analyze Kubernetes environments across multi-cloud and managed clusters.
Model K8s security: Map and represent Kubernetes resources as clean data models that surface misconfigurations, exposure risks, and compliance violations.
Integrate detection engines: Integrate and evolve detection engines for container vulnerabilities, secrets, RBAC risks, misconfigurations, and compliance frameworks.
Collaborate on research & product: Partner with security researchers and product managers to translate novel findings and complex requirements into impactful features.
Design for quality: Write clean, well-tested code in Python or Go, with thoughtful abstractions and APIs that keep the system correct and maintainable as it grows.
Lead & mentor: Lead design discussions and code reviews that uphold high engineering and security standards across the team.
Own it end-to-end: Own features through their full lifecycle - from technical specification and design through implementation, testing, and release.

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.