דרושים » תוכנה » Senior Software Engineer

we are seeking a Senior Engineer for Cloud Security Product Group.

Were extending mission of stopping breaches into the public cloud and cloud-native workloads. product offering will give customers the ability to monitor and track their cloud-native workloads as well as hardening and protecting them against attacks prior to deployment. This offering will help with defending against potential adversary activities involving cloud-native resources. When coupled with Falcon, endpoint security offering, our CSPG offering will provide a more comprehensive perspective on how the adversary is targeting key customer infrastructure. Our ultimate goal is to provide a single platform for securing the entire lifecycle of cloud workloads and cloud security posture.

What You'll Do:

Lead backend engineering efforts from rapid prototypes to large-scale applications across products

Leverage and build cloud-based systems to detect targeted attacks and automate cyber threat intelligence production at a global scale

Brainstorm, define and build collaboratively with members across multiple teams

Work in a startup-like environment with a small fast-moving team

Be mentored and mentor other developers on backend, and data storage technologies and our system

Constantly re-evaluate our product to improve architecture, knowledge models, user experience, performance and stability

Be given the autonomy to own your work in a high trust environment

Required Staff Software Engineer, Cloud Storage, AI/ML
Tel Aviv, Israel
About the job
Our software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to our needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As a part of the Cloud Storages, your mission is to provide the most trusted planet-scale storage system, with reliability, efficiency, performance, and simplicity.
As a part of the Storage AI/ML Solutions team, you will be dedicated to exploring, architecting and developing next-generation storage solutions for the AI/ML ecosystem. You will bridge the gap between core storage infrastructure and the evolving demands of AI/ML workloads, from large-scale training to high-performance inference. You will deliver innovative solutions and sharing performance insights through benchmarks, enable customers to achieve optimal results and solidify Cloud Platform (GCP's) position as the premier platform for AI/ML.Cloud accelerates every organizations ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage our technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
Design and implement high-complexity features, deliver production-ready code for storage solutions that address the specific demands of AI/ML workloads.
Architect scalable and performant storage solutions, apply data-driven decisions to optimize system efficiency and reliability.
Diagnose and resolve performance bottlenecks and intricate system issues, develop innovative, practical solutions to technical issues that arise at the intersection of storage and ML.
Collaborate with product and engineering stakeholders to translate customer requirements into technical specifications, ensuring the incubations output aligns with broader Cloud goals.

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 workers 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.

Were looking for a Senior MLOps Engineer to be a core driver in how our product empowers security teams. You will be expected to deeply understand customer needs and translate them directly into product features that deliver real value. You'll own key parts of our frontend stack, drive key architectural decisions, and turn complex security data into clear, actionable business insights.

As we scale our AIDR product and expand deeper into model-driven security intelligence, we are looking for a Senior MLOps Engineer to own the infrastructure, tooling, and operational foundations that power our NLP and LLM training, evaluation, and deployment workflows.

You will architect and operate the systems that enable us to train, fine-tune, deploy, and monitor models at scale making ML reliable, fast, cost-efficient, and production-ready.

This is a high-visibility, high-impact role where you will partner closely with DevOps, Backend, Data, and Product to establish world-class ML infrastructure from the ground up.

What Youll Do

Build & Scale ML Pipelines
Design, build, and maintain pipelines for training, fine-tuning, evaluating, and deploying NLP and LLM models across GPU and CPU environments.
Establish LLM-Focused CI/CD
Implement automated CI/CD workflows for ML models, including benchmarking, testing, performance gating, and production deployment.
Optimize Runtime & Inference
Select and optimize serving frameworks for low-latency, high-throughput inference, ensuring reliability and scalability.
Own ML Infrastructure
Manage training environments, experiment tracking, model registries, artifact versioning, and distributed training systems.
Operational Excellence
Monitor and optimize production models for performance, cost efficiency, availability, and observability.

we are seeking a Senior Data Infra Engineer. You will be responsible for designing and building all data, ML pipelines, data tools, and cloud infrastructure required to transform massive, fragmented data into a format that supports processes and standards. Your work directly empowers business stakeholders to gain comprehensive visibility, automate key processes, and drive strategic impact across the company.

Responsibilities

Design and Build Data Infrastructure: Design, plan, and build all aspects of the platform's data, ML pipelines, and supporting infrastructure.
Optimize Cloud Data Lake: Build and optimize an AWS-based Data Lake using cloud architecture best practices for partitioning, metadata management, and security to support enterprise-scale operations.
Lead Project Delivery: Lead end-to-end data projects from initial infrastructure design through to production monitoring and optimization.
Solve Integration Challenges: Implement optimal ETL/ELT patterns and query techniques to solve challenging data integration problems sourced from structured and unstructured data.

Are you a results-driven backend or full-stack engineer passionate about building scalable, cloud-native microservices? Do you thrive in an agile, startup-like environment while having the backing of a market leader? At our company, you wont just be a coder; you'll be an architect of innovation, shaping the future of identity security.
Our engineering team is the core of our success. We build high-quality, professional-grade products on a mature, event-driven microservices architecture hosted in AWS. We're now seeking a Senior Backend Software Engineer to be a foundational member of a new team building a cutting-edge, cloud-based SaaS identity analytics product from the ground up.
Your Mission: The First 12 Months

First 3 Months: You will be fully integrated into our agile team, actively contributing to the design and development of core microservices for our new SaaS product. You will have a comprehensive understanding of the product architecture and roadmap, and you'll be writing high-quality, test-covered code in Go.

First 6 Months: You will take ownership of significant features, from design and estimation to implementation and deployment. You'll be expected to contribute to our continuous delivery pipeline and improve code quality by producing unit and end-to-end tests, aiming to increase code coverage by 15-20%.

First 12 Months: You will be a key contributor to the product's evolution, mentoring junior engineers and collaborating with product management to define and implement new features. You will have made a measurable impact on the product's performance and scalability, and you'll be a go-to expert for critical components of the system.

What You'll Do

Design, develop, and deploy backend microservices in Go. Success will be measured by the delivery of well-tested, scalable, and maintainable code that meets product requirements and is deployed to production in a timely manner.

Integrate AI-assisted tooling into day-to-day DevOps and engineering workflows. Success will be measured by improvements in productivity, scalability, and operational efficiency. You will achieve this by leveraging AI tools to generate initial configuration drafts, validate infrastructure code, and recommend workflow improvements, while utilizing AI-driven automation to reduce repetitive manual tasks and accelerate engineering execution without sacrificing high-quality standards.

Collaborate on designs, code reviews, and testing. Success will be measured by your active participation in team meetings, providing constructive feedback on peer code reviews, and contributing to a collaborative and positive team environment.

Produce unit and end-to-end tests. Success will be measured by your consistent contributions to our test suites, with a focus on increasing code coverage and improving the overall quality and reliability of the product.

Create and refine design and engineering best practices. Success will be measured by tangible improvements to our development processes and documentation, leading to increased team efficiency and code quality.

we are seeking a Senior Software Engineer (Data Engineering). You will be responsible for designing and building all data, ML pipelines, data tools, and cloud infrastructure required to transform massive, fragmented data into a format that supports processes and standards. Your work directly empowers business stakeholders to gain comprehensive visibility, automate key processes, and drive strategic impact across the company.

Responsibilities

Design and Build Data Infrastructure: Design, plan, and build all aspects of the platform's data, ML pipelines, and supporting infrastructure.
Optimize Cloud Data Lake: Build and optimize an AWS-based Data Lake using cloud architecture best practices for partitioning, metadata management, and security to support enterprise-scale operations.
Lead Project Delivery: Lead end-to-end data projects from initial infrastructure design through to production monitoring and optimization.
Solve Integration Challenges: Implement optimal ETL/ELT patterns and query techniques to solve challenging data integration problems sourced from structured and unstructured data.

We're looking for a Software Engineer to join our core engineering team and help build the infrastructure behind one of the fastest-growing AI APIs. You'll work on systems that handle massive scale across a distributed microservices architecture running on AWS. You'll ship fast, take ownership of critical systems, and solve hard infrastructure problems as we grow.

This is a great role for an engineer who loves building ambitious systems from scratch, and wants to tackle the kind of scale and complexity challenges typically reserved for much larger companies.

What Youll Do

Design and build high-performance distributed systems

Design and implement backend infrastructure and API endpoints

Build and optimize real-time data pipelines that process billions of events per day across distributed queues and stream processors

Improve performance, monitoring, and reliability across the stack

Own core systems and contribute to key architectural decisions

Help shape a strong engineering culture focused on velocity and quality

Required Software Engineer
We believe financial opportunity should be more personalized and fair. We develop innovative technologies that provide underserved and overlooked borrowers with better access to credit. From our employees to our dealers, partners, and borrowers, weve built a company and a culture around a resolute belief in the promise and power of diversity. We value independent and critical thinking.
Were a small, highly-owned team at the heart of how engineering scales. Our work is challenging to define, and thats intentional.
We own the cloud infrastructure. We manage Kubernetes clusters, continuous deployment (CD) pipelines, and shared components like Kafka and Debezium. We also provide the necessary glue to ensure the organizations production systems are reliable and self-sufficient. When tasks are manual, operational, or rely on tribal knowledge, we transform them into scalable solutions, such as services, operators, or shared libraries. Our approach is production-first. We prioritize shipping products that must survive, scale, and improve over time with minimal intervention.
Responsibilities:
Youll transform operational tasks, currently residing in runbooks, Slack threads, and minds, into robust, observable, and maintainable systems. This involves:
Designing and constructing Kubernetes operators and infrastructure microservices that enable self-healing and self-management of the infrastructure.
End-to-end ownership of shared infrastructure components like Kafka and Debezium, facilitating safe and independent consumption by the rest of the R&D team.
Developing continuous delivery (CD) pipelines and deployment workflows that minimize time-to-deliver and eliminate bottlenecks between teams.
Designing systems with self-service in mind, allowing other teams to expedite their processes without initiating tickets.
Measuring key performance indicators (KPIs) such as ticket volume, hours of manual work per week, time-to-deliver, and the level of friction experienced by consumers.
This transformation goes beyond automation through scripting languages like Python or Bash. It demands genuine software engineering expertise, encompassing API design, extensibility, failure modes, observability, and upgrade paths.

We are looking for a talented Architect to join us. As a Data Architect, you will be the organizational point of contact for all things related to data persistence and architecture. You will work closely with engineering teams across the Product, Platform, and Data groups to design, govern, and evolve our data models, databases, and data-related systems. Your goal will be to ensure scalability, reliability, security, and efficiency for all data storage and retrieval across the organization.

A few of the things you will do:

Be the primary point of contact and subject matter expert for data persistence across the entire engineering organization.

Define and govern the data architecture strategy, standards, and best practices for relational, NoSQL, and data warehouse systems.

Partner with engineering teams from product, platform, and data groups to design and implement scalable and robust data models for new and existing services.

Lead the design and optimization of the organizations data flows. You will help to ensure that data moves efficiently, consistently, and with high quality across all systems and domains.

Evaluate and recommend new technologies and data solutions to meet evolving business needs.

Drive initiatives to improve data quality, consistency, and integrity across all production systems, from ideation to hands-on execution.

Establish, maintain, and communicate documentation for all data models and architectural decisions.