דרושים » תוכנה » Senior Infrastructure Developer

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.

We are looking for a QA Automation Engineer to join our growing team!
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.
Key Responsibilities:
Develop Testing & Automation SW tools from the ground up, interfacing to various systems and tests (Python-based).
Work closely with developers to create and maintain a state of the art system tests
Define, develop and execute testing plans with deep system knowledge and understanding.
Location: Tel Aviv - Israel.

We are looking for a proactive and skilled Software Infrastructure Developer with a strong Agentic AI focus to join our team. In this role, you will design and build the infrastructure, tooling, and AI-powered automation that keep our engineering systems reliable, scalable, and intelligent.
You will be responsible for embedding GenAI and agentic capabilities into our internal developer platforms and CI/CD workflows - creating frameworks, libraries, and multi-agent systems that accelerate automation, improve system stability, and unlock new levels of engineering productivity. This is a hands-on role for someone who thrives at the intersection of infrastructure engineering and applied AI.
The ideal candidate brings deep technical expertise in Python (FastAPI) and/or TypeScript, Kubernetes, CI/CD (Jenkins, GitHub Actions), containerization, and cloud infrastructure - combined with hands-on experience building LLM-powered applications, agents, MCP servers, and RAG pipelines.
What you'll be doing:
AI Platform Development: Design and build internal AI platforms, reusable SDKs, libraries, tools, and MCP servers for agentic applications.
Agentic Workflow Development: Develop single- and multi-agent workflows covering planning, tool selection, delegation, state and memory management, execution, retries, fallbacks, error recovery, and human-in-the-loop approval.
AI-Powered Infrastructure & CI/CD: Integrate AI capabilities into Kubernetes infrastructure and Jenkins/GitHub Actions pipelines to improve development, testing, deployment, and operational workflows.
AI Observability & Evaluation: Implement agent tracing, prompt and tool-call logging, latency and error monitoring, token and cost tracking, regression testing, and failure analysis.
AI Security & Governance: Apply guardrails, access controls, auditability, and governance practices to ensure agents operate safely and reliably.
End-to-End Platform Ownership: Own AI platform capabilities from architecture through production and build reusable solutions that accelerate adoption across engineering teams.
Cross-Functional Collaboration: Collaborate with engineering and business teams to identify high-impact AI opportunities and translate them into scalable technical solutions.
AI Research & Innovation: Evaluate emerging AI frameworks, models, and cloud technologies and promote their adoption where they provide measurable value.

Required Software Engineer- Data Platform
Tel Aviv, Israel
About us
A global technology company making life-changing financial products and services available to more people nationwide, as it reshapes the financial services ecosystem. By using machine learning, a vast data network and a sophisticated AI-driven approach, we provide comprehensive consumer credit and residential real estate solutions for its partners, their customers, and investors. Its proprietary API and capital solutions integrate into its network of partners to deliver seamless user experiences and greater access to the mainstream economy.
About the Role :
The Data Engineering team is a cross-functional team responsible for data integration, monitoring, and quality. This includes automating data flows, alerting, fetching, and checking across various stages of data transformation and projection.
Key Responsibilities:
Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
Develop data architecture for data ingestion, validation, and processing.
Identify, design, and implement process improvements, such as automating manual tasks, optimizing data delivery, and redesigning infrastructure for enhanced scalability.
Create and maintain optimal data pipeline architecture using microservices.
Work with other members of the data team, including data architects, data analysts, and data scientists.
Key Takeaways:
Use the tools and languages that are best suited to the job - Complete flexibility to problem-solving with novelty and creativity encouraged.
Be around very bright and lovely people.
Your intellectual curiosity and hard work contributions will be welcome to our culture of knowledge sharing, transparency, and shared fun and achievement.
Provide education and documentation to empower team members to make the most of technical resources.
Contribute to our software engineering culture of writing correct, maintainable, elegant, and testable code.
Utilize AWS services and tools such as S3, EventBridge, Athena, and DynamoDB to build a robust and scalable data architecture for data ingestion, processing, and storage.
Collaborate on data infrastructure that supports LLM-driven workflows - leveraging tools like Cursor to accelerate code development, enhance reproducibility, and streamline iteration on intelligent systems.

we are looking for a Software Engineer - Verification and Reliability.
In this role as a SDET (Software Development Engineer in Test), you are a developer first. You will join a high-impact team of engineers who write production-grade code to build a massive-scale validation ecosystem. Your job is to act as "The Breaker"-designing the infrastructure, chaos experiments, and AI-driven tools that push our platform to its theoretical limits.
What Youll Build:
Adversarial Engineering: Design and implement Python-based distributed frameworks capable of orchestrating millions of concurrent IO operations to hunt down race conditions and memory leaks.
AI-Augmented Validation: Be at the forefront of the AI-Native transformation. You will leverage LLMs and Generative AI to automate complex scenario generation, build intelligent agents for root-cause analysis, and multiply your engineering velocity.
Simulation & Chaos: Build the "Entropy Engine." You will develop tools that inject real-world failures - latency, packet loss, and hardware crashes - to prove the resilience of our Raft and RDMA implementations.
Deep-System Observability: Move beyond "Pass/Fail." You will build telemetry pipelines to track P99 latency and jitter, providing critical architectural feedback to the Core Kernel teams.
Collaborative Architecture: You will operate with the same rigorous standards as the Core R&D team: design docs, production-grade code reviews, and high-level architectural planning.

we are seeking a Senior Python Software Engineer to join our high-impact Risk Team. The Risk Team sits at the heart of our decisioning engines, powering every product through a state-of-the-art fusion of predictive machine learning models and real-time market strategies.
In this role, you will lead backend development for new financial products, working closely with ML Engineers to build robust, fault-tolerant infrastructure that supports complex predictive models. You will design and scale high-volume, low-latency systems that execute critical financial decisions in milliseconds. We are looking for an engineer who understands end-to-end software architecture and possesses the business acumen to transform strategic goals into engineering reality.
Key Responsibilities
Architect & Build: Design and implement resilient, low-latency backend solutions capable of handling high-throughput, high-availability demands.
Solve Complex Systems Challenges: Tackle intricate architectural problems by applying deep expertise in distributed systems and performance optimization.
Cross-Functional Collaboration: Partner closely with ML engineers, product managers, and data scientists to operationalize decisioning logic smoothly.
Maintain & Scale Infrastructure: Safeguard system health, ensure continuous operational stability, and optimize runtime performance.
Drive Technical Excellence: Advocate for clean code, solid design patterns, robust testing, and maintainable software architecture.
Mentor & Empower: Elevate the engineering team by mentoring junior developers, leading technical discussions, and fostering a culture of continuous learning.

We're looking for an Infrastructure Engineer to go deep into that layer: build and own core proxy and networking infrastructure, not configure someone else's.
You bring the same range as our core infrastructure engineers - proxies and networking, browser internals, and cloud-native systems (Kubernetes, Docker, AWS) - with the depth to design and debug at every layer of the stack, plus a genuine specialization in networking and proxy systems.
What Youll be Doing:
Build core proxy infrastructure - reverse proxies, IP rotation, session management, intelligent routing.
Own IP pool health - reputation scoring, monitoring, blacklist recovery - across residential, mobile, datacenter, and ISP proxies.
Implement geo-targeting at country, city, and ASN level.
Work at the protocol level (TCP/UDP, sockets, HTTP/HTTPS/SOCKS5, HTTP/2/3) and the Linux networking stack underneath.
Build monitoring, health checks, failover, and bandwidth/usage metering for the proxy fleet.
Deploy and scale on cloud-native infrastructure (Kubernetes, Docker, Terraform).
Use AI-assisted development tools daily.

The AI Teams is shaping the future of how AI is built, integrated, and experienced across our platform. We develop the foundations, tools, and capabilities that enable intelligent experiences for customers, partners, and internal teams alike. From powering AI-driven product experiences to building the infrastructure and platforms that make them possible, we operate at the intersection of innovation, scale, and engineering excellence.
We work in a true continuous delivery environment, with fully automated QA processes and a modern microservices architecture, deploying to production multiple times a day.
Job responsibilities
Design, build, and maintain backend infrastructure and microservices supporting AI-driven features.
Collaborate closely with the infra and data groups to ensure smooth integration of AI models and services into Bobs core systems.
Develop and optimize APIs, data pipelines, and background processing workflows.
Ensure performance, scalability, and resilience of production systems handling real-time AI interactions.
Drive engineering excellence through code reviews, architecture discussions, and automation.
Mentor other backend developers and promote best practices in software design, testing, and deployment.

Required Senior Software Engineer
About the role
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.
Our Stack: Python, Go, K8s APIs, K8s ecosystem tooling (OPA/Gatekeeper, admission controllers), Docker & container runtimes, SingleStore, Postgres, Redis, Kafka, SQS, ElasticSearch, AWS, GCP, Azure.
On a typical day youll:
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 an experienced hands-on Python Engineer who can work independently with remote teams (SW, HW, logic,) and create products that will shape the future of Quantum Computers.
The Quantum Computing SDK is the interface through which our customers run our control system. Customers use it to configure their cutting-edge system and run their ground-breaking experiments. Various institutions from world-class universities to hyper-scalers use the SDK to calibrate their delicate QBits, perform Write and Read Quantum Computing Operations and run programs in higher level Quantum Computing languages like OpenQASM3.
Responsibilities:
Develop the software for the company's Quantum Computing SDK.
Take part in all the technical aspects of the SW development from design to delivery.
Work with high standards of SW methodology, clean-code and CI.