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We are looking for a Backend Engineer with deep data engineering expertise to build and evolve the systems that power product, analytics, experimentation, and AI development.
You will work across production backend services and data infrastructure, taking technical ownership of the full data lifecycle - from event ingestion and real-time processing to orchestration, modeling, quality, and reliable data access. This role combines hands-on backend development with ownership of shared data platform, working closely with backend, frontend, AI, DevOps, analytics, and product teams.
Key Responsibilities:
Build and maintain production-grade Python and Java backend services, APIs, and reactive data-processing pipelines with clear interfaces, resilient failure handling, and comprehensive observability.
Own and evolve batch and streaming data pipelines supporting product analytics, learner insights, experimentation, and AI model training.
Design and maintain trusted data models, shared metrics, and semantic-layer business logic across the analytical data platform.
Define and enforce standards for data contracts, testing, lineage, freshness, and observability.
Develop reliable approaches to schema evolution, backfills, replay, workload distribution, and failure recovery.
Collaborate with DevOps, backend, frontend, AI, analytics, and product teams to deliver reusable data capabilities and maintain clear system boundaries.

We are seeking a skilled Automation Developer to join our team. As a Automation Developer, you will write and execute the automated tests and write the processes. You will collaborate with cross-functional teams to design, develop, and maintain automated test scripts, identify and report defects, and contribute to the overall improvement of our software development lifecycle.
Responsibilities:
Design, develop, and maintain automated systems for infrastructure deployment and management.
Build tools and frameworks that automate workflows across different environments.
Collaborate with development, DevOps, and QA teams to identify automation opportunities.
Write clean, scalable automation scripts using TypeScript.
Ensure system reliability, performance, and security through effective automation practices.
Monitor and improve the efficiency of automation systems continuously.
Participate in code reviews, architecture discussions, and contribute to technical documentation.
Troubleshoot and resolve infrastructure automation issues.

We're looking for a Support Lead to build our company's customer support function from the ground up, working on site in Tel Aviv offices.
You'll be the founding member of our support organization, designing the processes, tooling, and team that will sit between our enterprise customers and our Product and Engineering teams. You'll report to the VP Product Growth and work closely with Product and Engineering to ensure issues are resolved fast, with full ownership, and with as little engineering drag as possible.
This is a rare opportunity to define what great support looks like at an AI-first company serving some of the world's largest enterprises, and to build it your way.
What you'll do
Build the support function from scratch: processes, workflows, escalation paths, SLAs, tooling, and internal playbooks.
Lead day-to-day support operations for global enterprise customers, owning prioritization, escalations, and customer communication.
Hire and grow a team of Support Engineers who are technical enough to investigate issues independently, reducing reliance on Engineering for first and second-line resolution.
Design an AI-first support model: leverage AI tooling for log analysis, issue investigation, and knowledge retrieval to help the team punch above its weight across a fast-growing set of diverse customer solutions.
Build and maintain a living knowledge base that enables support engineers to ramp quickly on new solutions and handle complex issues without deep product expertise from day one.
Partner with Product and Engineering to surface recurring issues, drive root cause fixes, and close the loop between customer feedback and product improvement.

As a Forward Deployed Engineer at our company, you'll work at the intersection of Engineering, Product, and our customers. You'll use your engineering experience to help enterprise customers deploy AI systems into production, solve complex technical challenges, and deliver solutions with real business impact.
What youll do:
Work directly with enterprise customers to understand their business and technical challenges.
Translate open-ended problems into practical AI solutions.
Build production-grade integrations, workflows, and automations across customer systems, APIs, and data sources.
Build and ship customer-facing solutions, not just prototypes or technical designs
Deploy, test, and iterate in real customer environments.
Own customer implementations from discovery through production.
Partner closely with Product and Engineering to improve the platform.
Design and implement LLM-powered workflows and agentic systems for real enterprise use cases.

We're looking for an Infrastructure Engineer with a strong backend engineering mindset - someone who treats infrastructure as software.
In this role, you won't just operate infrastructure - you'll design systems, write code, and build controllers and automation that power our Kubernetes-native platform.
You'll work closely with platform, DevOps, and backend teams to create scalable, reliable infrastructure abstractions used by hundreds of developers.
What Youll Do:
Design and build backend-driven infrastructure workflows using Kubernetes controllers and declarative patterns.
Develop automation and tooling in Go or Python to manage infrastructure at scale.
Manage AWS resources through Kubernetes-native approaches (ACK or similar controller models).
Develop internal APIs, scripts, or services that improve developer workflows and platform capabilities.
Operate and evolve multi-cluster Kubernetes environments with a focus on automation and reliability.
Implement observability patterns and integrate monitoring signals into infrastructure logic.
Collaborate with backend engineers to design infrastructure that behaves like software - versioned, testable, and automated.

As a Full Stack Software Engineer, youll work across the stack to design, implement, and ship high-quality workflows that solve real problems for real users. Youll collaborate directly with product and enterprise customers, see your code in production within days, and be part of a team that values ownership and thoughtful execution.
What youll do:
Develop and deliver full-stack AI-powered applications on top of our companys platform.
Work closely with customers and internal teams to tailor solutions.
Extend the platform and UI/UX layer as needed.
Collaborate with platform and research teams to integrate AI capabilities into production use.
Write clean, tested, and maintainable code.

Were looking for an Engineering Tech Lead to help drive some of the most strategic technical initiatives at our company. This is not a traditional Tech Lead role. Were looking for someone who is deeply technical and highly hands-on, but also knows how to think strategically, lead architecture decisions, and represent the company in front of enterprise customers and senior stakeholders. Youll work across multiple teams and domains, partnering closely with Platform, Product, and Engineering teams to design and deliver AI-powered enterprise solutions at scale. One moment you might be deep in architecture or code, and the next youll be in a room with customer executives helping guide critical technical decisions. We work on site from our offices in Tel Aviv.
What Youll Do
Lead architecture and technical direction for strategic enterprise AI initiatives
Work directly with some of the worlds largest enterprises to design and deliver scalable AI-powered solutions
Partner cross-functionally with Platform, Product, and Engineering teams across the company
Stay deeply hands-on with the code and engineering teams
Drive complex technical decisions across scalability, reliability, performance, and system design
Help customers solve real production challenges and build long-term technical trust
Design versatile enterprise-grade solutions across different customer environments and use cases
Influence engineering standards, architecture practices, and long-term technical direction
Operate in a fast-moving, high-ownership environment where execution speed matters.

You'll be responsible for designing and implementing backend services that integrate AI capabilities including large language models (LLMs), retrieval-augmented generation (RAG), and conversational interfaces into our consumer-facing products. This is an opportunity to expand your expertise into AI while leveraging your strong engineering foundation.

What Youll Do
Design and develop scalable, high-performance backend services and APIs.
Implement integrations with AI platforms and services.
Work with AI specialists to translate AI capabilities into production-ready features.
Ensure high reliability, performance, and security of AI-powered systems.
Collaborate with product and engineering teams to gather requirements and deliver solutions.

As an Engineering Manager in the data department, youll build and scale our data platform and data apps that powers our business insights. Youll design and implement robust pipelines to process billions of daily records, leveraging cutting-edge cloud technologies to transform data into actionable intelligence.

If youre passionate about data engineering and driving business growth through insights, wed love to hear from you!

Responsibilities
Lead and grow Data Engineering and Machine Learning teams in a high-scale environment (tens of billions of events per day).
Own the design and evolution of a self-service data platform enabling internal teams to easily build, ship, and consume data products.
Architect and scale batch and streaming pipelines powering core business and ML use cases.
Drive production ML systems end-to-end (recommendation, ranking, prediction) with direct business KPI impact.
Ensure reliability, scalability, and observability of large-scale data and ML systems in production.

Were looking for a Senior Full-Stack Engineer to join our R&D team and help shape the product experience end-to-end. In this role, you will design and build features across our backend services and user-facing applications, collaborating closely with product, design, and other engineering teams. You will balance strong technical execution with ownership, craftsmanship, and a deep understanding of how customers interact with the product.
About the role
Youll design and develop robust backend services that ingest, process, and correlate large-scale security and cloud data.
Youll build intuitive, performant web experiences using modern frontend technologies, helping customers explore complex data with clarity.
Youll collaborate with designers and product managers to translate ideas and workflows into thoughtful, scalable product features.
Youll architect cross-service integrations, data flows, and APIs to support both customer-facing and internal features.
Youll ensure frontend and backend components are secure, resilient, and optimized for high-scale production usage.
Youll participate in design reviews, cross-team technical discussions, and efforts to continuously improve engineering velocity.
As part of a fast-paced startup, youll have a direct impact on product direction and how customers use our company to solve real-world security challenges.

We are looking for a Senior Software Engineer to own and evolve the runtime platform that powers production AI agents.

This is a hands-on backend and platform engineering role for someone who combines deep TypeScript expertise, strong distributed-systems fundamentals, and exceptional production debugging skills with a practical understanding of LLMs and agentic systems.

You will work closely with engineers building AI agents. Your responsibility will be to provide the reliable runtime, infrastructure, abstractions, and observability they need to deliver new capabilities safely and quickly.

What youll do

Own and evolve the production runtime responsible for executing and orchestrating AI agents.
Design platform capabilities for agent execution, tool calling, streaming, state management, persistence, and long-running workflows.
Build resilient integrations with multiple LLM providers and model-serving platforms.
Design provider-routing and fallback strategies based on availability, latency, quality, and cost.
Implement retries, timeouts, circuit breakers, rate-limit handling, idempotency, and graceful degradation.
Ensure the platform remains available when external dependencies or infrastructure components experience outages.
Build reliable mechanisms for loading, caching, versioning, and recovering agent configurations and artifacts.
Create end-to-end observability for AI requests, including model, provider, agent, latency, token usage, cost, errors, retries, and fallback behavior.
Define dashboards, alerts, SLOs, and runbooks for production AI workloads.
Lead the investigation of complex production issues across application code, infrastructure, external providers, distributed state, and agent behavior.
Improve platform scalability, concurrency, latency, and resource efficiency.
Build reusable APIs and abstractions that allow agent developers to add capabilities without duplicating infrastructure logic.
Strengthen platform quality through integration testing, load testing, failure injection, and dependency-outage simulations.
Turn production incidents into architectural improvements, automated tests, monitoring, and operational safeguards.
Collaborate with product, infrastructure, and engineering teams to translate customer and business requirements into platform capabilities.
Mentor engineers and establish best practices for building and operating reliable production AI systems.

We are constantly striving to make our systems reliable, scalable, and simple to operate so our services are available to travelers when they need them most. With our continued growth, we have exciting challenges ahead and we're looking for a Senior Site Reliability Engineer to join our team in Tel Aviv. This role blends classic SRE ownership with pragmatic AI SRE work: you will build and operate the platforms, automation, observability, and incident response practices that keep Navan reliable, while helping teams use AI solutions, AI providers, and their APIs safely and dependably.



This is a hands-on engineering role, not a research role. You will partner with product, platform, data, security, support, and incident response teams to make production systems and AI-powered experiences more resilient. You will use software engineering, infrastructure as code, SLOs, telemetry, provider observability, and automation as your main tools, and you will apply AI where it creates measurable reliability value rather than novelty.



This position is based out of our new Tel Aviv office.



What You'll Do:

Support AI-based application solutions where reliability matters. Partner with the development teams building AI-powered travel experiences to support the development and production operation of their solution.
Work with AI solutions, providers, and APIs. Partner with teams integrating AI capabilities and providers, with attention to API reliability, authentication, quotas, rate limits, latency and provider-specific operational constraints.
Troubleshoot AI tools and provider issues. Diagnose failures across AI-powered workflows, provider APIs, configuration, permission errors, degraded responses and related areas.
Operate reliable production platforms. implement and run cloud infrastructure,and help product teams move quickly without compromising reliability.
Improve observability. Build dashboards, alerts, traces, logs, and runbooks that make service health clear, actionable, and tied to SLOs and customer impact.
Apply AI to SRE workflows. Prototype and productionize AI-assisted systems that create effective and efficient operations
Automate operational toil. Create tools, workflows, and automation that remove repetitive manual work and make operational knowledge easier to use.

we are building a vertically integrated AI neocloud from the electron up. Because we own the entire stack-from clean energy generation to the GPUs running customer training jobs-we treat power as a control input, not a constraint. To support our massive scaling vector from 30,000 accelerators to 300,000 without a linear growth in headcount, we are building the Cloud Availability Platform Engineering (CAPE) organization. CAPE serves as the horizontal reliability spine beneath all of our company Cloud. As the founding Engineering Manager, Production Engineering in Tel Aviv, you will stand up our local presence from scratch, driving a cultural shift from reactive firefighting to software-defined engineering.
This is a hybrid leadership and technical role where you will hire, scale, and lead a local team of exceptional systems generalists while remaining deeply hands-on in the code and incident response. You will ensure that your team spends at least 30% of their bandwidth on strategic automation, tooling, and firmware optimization primitives to prevent the operational treadmill. If you want to bridge core software layers with physical infrastructure and write the playbook for an entire engineering site, this founding seat is for you. This is a full-time position located in Tel Aviv, Israel.
What Youll Be Working On
Team Leadership & Founding Culture: Recruit, mentor, and establish a high-performing Production Engineering footprint in Tel Aviv, setting an uncompromising cultural standard for operational discipline and systems-first engineering.
Incident & On-Call Ownership: Partner with US and Dublin teams to run a follow-the-sun global on-call rotation, while championing a strict blameless post-mortem culture that targets systemic failures over human error.
Software-Defined Operations: Drive alert-reduction initiatives to improve fleet signal-to-noise ratios, automate routine manual workflows using modern runbook automation (e.g., Temporal), and build predictive monitoring to catch SEV1/SEV2 events before customers do.
Collaborative Governance: Act as the ultimate Production Gatekeeper across cross-functional compute, storage, networking, and platform teams, holding a strict line on Production Readiness Reviews and change control.
Strategic Reliability Engineering: Protect team bandwidth to ensure engineers spend at least 30% of their time on strategic automation, tooling, and firmware optimization primitives rather than drowning in incident response.
Physical-to-Digital Automation: Instill a software-first approach to physical problems, ensuring that any physical intervention occurring twice is successfully converted into a software-defined auto-remediation.