דרושים » תוכנה » Senior Software Engineer - Data Platform

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.

Were looking for a Senior Software Engineer, to design and build scalable, production-grade systems powering our AI-native platform.
This is an AI-native engineering role- AI copilots and tools (such as Claude, Cursor, and Copilot) are a core part of how we design, prototype, and ship software. Engineers use AI as a force multiplier to move quickly, iterate rapidly, and focus their time on architecture, system design, and complex problem solving.
Youll work across multiple services, platform infrastructure, and AI-driven capabilities, owning features end-to-end and helping bring intelligent healthcare products from concept to production.
Key Responsibilities:
AI-Native Development - Design and build scalable systems using AI copilots such as Claude, Cursor, and Copilot as a core part of the workflow.
AI-Powered Features - Develop and integrate AI-driven capabilities and pipelines into production systems.
End-to-End Ownership - Own features from architecture and development through deployment and monitoring.
Cloud Infrastructure - Build and operate scalable cloud-native systems on AWS.
Collaboration & Engineering Excellence - Work closely with Product, Data, and AI teams, contribute to architecture decisions, and help raise the technical bar across the team.

Required Senior Data Engineer
Description
We are making the future of Mobility come to life starting today.
We support the worlds largest vehicle fleet operators and transportation providers to optimize existing operations and seamlessly launch new, dynamic business models - driving efficient operations and maximizing utilization.
At the heart of our platform lies the data infrastructure, driving advanced machine learning models and optimization algorithms. As the owner of data pipelines, you'll tackle diverse challenges spanning optimization, prediction, modeling, inference, transportation, and mapping.
As a Senior Data Engineer, you will play a key role in owning and scaling the backend data infrastructure that powers our platform-supporting real-time optimization, advanced analytics, and machine learning applications.
What You'll Do:
Design, implement, and maintain robust, scalable data pipelines for batch and real-time processing using Spark, and other modern tools.
Own the backend data infrastructure, including ingestion, transformation, validation, and orchestration of large-scale datasets.
Leverage Google Cloud Platform (GCP) services to architect and operate scalable, secure, and cost-effective data solutions across the pipeline lifecycle.
Develop and optimize ETL/ELT workflows across multiple environments to support internal applications, analytics, and machine learning workflows.
Build and maintain data marts and data models with a focus on performance, data quality, and long-term maintainability.
Collaborate with cross-functional teams including development teams, product managers, and external stakeholders to understand and translate data requirements into scalable solutions.
Help drive architectural decisions around distributed data processing, pipeline reliability, and scalability.

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.

We are looking for a Lead Software Engineer - Innovation Team to join our growing our new engineering innovation team who build our new product offering with our clients!
Our newest product line - a small, fast-moving team operating like a startup inside the company. While our core offering helps customers acquire better users and spend less doing it, Engage turns that intelligence inward: re-activating churned, dormant, and low-value users who are already on our customers' platforms. As a Senior Software Engineer, you'll work directly alongside the team's engineering lead, building the systems that take machine-learning predictions about user behavior and turn them into automated, continuously-learning decisions delivered straight into our customers' DB and CRM tools. This is a role with no narrow lane - you'll touch literally everything: data pipelines, ML and algorithms, applicative backend services, and even the UI. You'll partner closely with a VP Product and senior data scientists in a high-ownership environment where you shape the architecture, ship to production, and see your work drive a brand-new revenue stream for the company.
Responsibilities:
Design and build high-quality, production-grade systems across the entire Engage stack, from large-scale cloud data pipelines, to ML and decisioning services, to applicative backend and customer-facing UI, with an eye for performance, reliability, and easy maintenance.
Own the closed loop end-to-end: turning ML predictions into automated decisions, delivering them into customers' DB and CRM systems, and feeding outcomes back in so the system keeps learning.
Take features from idea to production largely on your own: designing the architecture, shipping it, monitoring it in production, and iterating, with the autonomy (and accountability) that comes with a small team.
Collaborate closely with the team's engineering lead, the VP Product, and senior data scientists to take models and research from prototype to reliable, scaled-up production systems.
Monitor performance and prioritize work by making data-driven decisions.
Participate in code reviews and uphold engineering standards and best practices across the team.

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.

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.

Were looking for a senior engineer who is ready to move beyond traditional software development and take full ownership of product delivery.

This is not a classic backend engineering role. You will work directly with Product to turn ideas and requirements into production-ready solutions, make the technical decisions, and use AI coding agents as a core part of your engineering workflow.

You will own the outcome, not just the code. AI-generated code is your code, and you are accountable for its quality, security, performance, and maintainability.


Own product features end-to-end, from requirements through production and monitoring.
Work with Product to translate business problems into clear technical solutions and execution plans.
Design scalable and maintainable solutions, including architecture, APIs, data models, and integrations.
Use AI coding agents to accelerate implementation, testing, debugging, and automation.
Review and improve AI-generated code, ensuring high standards for correctness, security, performance, and maintainability.
Make independent technical decisions and communicate architectural trade-offs clearly.
Contribute across backend, frontend, QA, CI/CD, and infrastructure when needed to deliver a feature.
Investigate and solve complex production and performance issues.
Continuously improve how we build, test, and ship software using AI-native development practices.

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.

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.