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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 company ronauts 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.

we are looking for a Senior Infrastructure Developer 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.
"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 company ronauts 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 Youll Be Doing
Design, build and set up development tools and infrastructure for use by the various teams in the R&D organization.
Among the different tools:
test infrastructure used by the QA
Maintain and develop API and interfaces facing the company storage product + different cloud providers.
full stack bug investigation portal
VM orchestration
Collaborate with other teams to improve the productivity of the entire R&D organization.
Dealing with diverse technologies and domains - Docker, Git, Python, Linux, Python, Storage.

We are seeking a talented and experienced Software Engineer to design, build, and optimize high-performance distributed systems, core data engines, and backend infrastructure.

required Desktop Application Developer.

As a Senior Software Engineer in the Platform Team, you will help deliver a smooth and consistent developer experience to our product/AI teams. This enables them to iterate quickly and deliver products faster to the market. The team aims to streamline development processes, reduce friction and provide developers with the right tools and infrastructure to build high-quality software efficiently which effectively aligns technical execution with our business objectives. Our techstack includes AWS, Python, RDS, EKS, ECS, RMQ and Redis.

You will:

You will have a direct impact on devs' daily smile :) , by focusing on their Devex and velocity through implementing and providing easy and intuitive self serve tools

Lead the design and implementation of infrastructure of complex, time-critical microservices systems, collaborating with AI, data, and product teams to ensure high-quality code using latest technologies while maintaining high developer velocity.

Drive improvements to backend infrastructure, focusing on scalability, reliability, and performance to enhance the daily experience and productivity of developers, including implementing intuitive self-serve tools.

Contribute to defining and realizing the technology vision of the company, evaluating and integrating new technologies to enhance platform capabilities including Gen AI, and troubleshooting complex issues to ensure platform performance and availability. Proactively establish and maintain CI/CD practices and processes including hybrid envs.

Enhance system scalability, performance, and reliability.

As a Senior Software Engineer, you will be responsible for designing and building core backend services and product capabilities, working on scalable systems that handle large volumes of security-related data, and developing robust features that improve security posture in cloud environments.

The ideal candidate will have strong software engineering foundations, a product-minded approach, and experience building distributed systems in production.

You will collaborate closely with Product, Research, and Engineering teams to deliver secure, performant, and reliable solutions end-to-end.

You will work within the engineering department, contributing to architecture decisions, improving code quality, scalability, and reliability, while maintaining strong ownership over development and delivery in a fast-paced environment.

Responsibilities
Design, develop, and maintain high-scale backend services and APIs.
Build features that identify and prevent cloud misconfigurations and security risks.
Write clean, maintainable, and testable code with high engineering standards.
Participate in system design and architecture discussions (scalability, reliability, performance).
Collaborate with Product, Research, and other engineering teams to define and implement end-to-end solutions.
Optimize performance and improve system reliability, monitoring, and observability.
Take ownership over services in production, including troubleshooting and incident resolution.
Contribute to engineering best practices: code reviews, technical documentation, CI/CD improvements.
Support and mentor other engineers, helping grow the teams technical excellence.

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.

We need a Director to set the strategy for everything underneath it - cloud, security, and the delivery lifecycle - and to bring AI into how that infrastructure is run.

This is a director-level leadership role, not an IC stretch assignment. You will lead our DevOps organization - which already has a team leader running day-to-day delivery - and operate one level up: setting direction, owning the roadmap, making architecture and build-vs-buy calls with authority, and representing infrastructure at the leadership table. Close enough to the work to guide it in depth, senior enough to own it end to end.

What Youll be Doing:
Own cloud infrastructure and security as one strategy: architecture, scale, and the path to our next order of magnitude of growth, with our security and compliance posture (IAM, secrets, hardened baselines, SOC 2 / ISO 27001 audit readiness) built in from the start, not bolted on.
Own the SDLC end to end, and drive AI into every stage of it: measure delivery performance (lead time, deployment frequency, change failure rate) and use AI to improve each stage of the lifecycle - planning, code review, testing, release, and operations - alongside AIOps practices like automated/self-healing recovery and intelligent alerting.
Own FinOps as a strategic discipline: the cloud bill is a P&L line you're accountable for, with unit economics driven down every quarter.
Own vendor and contractual relationships across cloud, tooling, and infrastructure services - negotiating leverage, not just approving invoices.
Lead the DevOps organization through its team leader: set technical direction and standards, develop the team leader into a stronger manager, and grow the bench beneath them.
Partner as a peer with Backend, Infra, AI, Data, Product, Security and Finance leadership - infrastructure decisions get made with you in the room, not after.

We're building one of the most agentic, fast-moving AI products in the web search category - and we need a leader who can own it end to end. This is a cross-functional group leader role sitting at the intersection of AI product leadership and high-scale AI infrastructure: you'll lead the team building our agentic search product, and own the data infrastructure that indexes and caches the web at scale.

What Youll be Doing:
Set technical and product direction for an agentic web search AI system, from research and benchmarking through production and scale.
Bring deep, hands-on expertise in LLMs, agentic architectures, evaluation/benchmarking, and modern AI/LLMOps practices; make build-vs-buy and architecture calls with authority, not just strategy.
Lead and develop small group of two teams with top notch engineers, providing technical leadership, growing engineering managers, and driving execution across both product and infrastructure.
Drive the product to a category-winning position within an aggressive timeline.
Own the infrastructure supporting an API surface currently serving millions of calls/month, with a mandate to lead its growth to billions/month.
Bring proven, hands-on experience scaling high-throughput, high-availability infrastructure - not just AI-adjacent platform experience - including reliability, cost, and performance at that scale.
Own the data infrastructure needed to run the product, including large-scale data pipelines, storage, and operations.
Lead a worldwide web caching and indexing operation at high scale, ensuring freshness, coverage, and cost-efficiency of the index.

We are looking for a Senior Cloud Engineer to join our Infrastructure team in Tel Aviv. In this role, you will be a key contributor to our AWS CDK projects, taking end-to-end ownership of high-impact infrastructure shifts like our migration to EKS. This is a hands-on position where youll balance long-term architectural projects with day-to-day support for our R&D teams, ensuring our cloud environment remains scalable, secure, and developer-friendly.

Responsibilities:

As a Senior Cloud Engineer, you will be the backbone of our infrastructure, ensuring that our cloud environment is scalable, secure, and developer-friendly. You will:

Serve as a core contributor to our central AWS CDK (TypeScript) project, ensuring every cloud resource-from S3 buckets to complex networking rules-is defined as code.

Act as a consultant for R&D and platform teams, helping microservice owners deploy new services and spin up sandbox environments while maintaining security standards.

Take end-to-end ownership of high-impact infrastructure shifts, including playing a key role in the transition from ECS Fargate to EKS.

Manage the lifecycle and maintenance of critical infrastructure components, such as security/observability agents and hosted open-source solutions.

Collaborate with our Boston-based teams on shared global projects to ensure architectural alignment and cross-region infrastructure support.

Balance long-term project work with active participation in internal help channels, troubleshooting real-time issues and resolving conflicts in central tools.

we are looking for a passionate and detail-oriented Product Owner & Engineer to join our team. In this role, you will collaborate closely with development teams to define new features, contribute to functional requirement documentation (FRD), and ensure seamless UX design and implementation.
A core part of this role is maintaining close alignment with customers. You will actively engage with customers, gather feedback, understand real-world use cases, and translate their needs into clear product requirements. You will work closely with Support and QA to ensure our testing strategy and supportability reflect actual customer environments and workflows.
Beyond core development, you will assist in critical escalations, manage complex or high-visibility installations, and develop tools that enhance the overall user experience. You will leverage telemetry data, production insights, and direct customer feedback to continuously refine and improve our products, ensuring they deliver measurable value in real-world deployments.
Key Responsibilities
Collaborate closely with Product and Engineering teams to define, refine, and prioritize features that directly address real customer needs and business impact.
Translate customer requirements and field insights into clear, structured Functional Requirement Documents (FRDs), while actively contributing to UX discussions to ensure intuitive and seamless user experiences.
Work closely with QA and Support to align testing strategies and troubleshooting workflows with real-world customer environments, ensuring reliability, operability, and supportability at scale.
Serve as a technical and product focal point during critical customer escalations and high-visibility deployments, ensuring timely resolution and long-term improvements
Develop tools and scripts to enhance user experience and operational efficiency.
Leverage telemetry, usage analytics, and direct customer feedback to drive data-informed decisions and continuously improve product performance and adoption.
Proactively identify risks, gaps, and cross-team dependencies, removing roadblocks to ensure successful delivery and measurable customer outcomes.

LLM optimization is a young field with no settled playbook, so the optimizations you invent here are genuinely new, and they ship into production rather than a paper. And they matter: real enterprises run enormous volumes of LLM traffic and feel every wasted token, so the work you do lands on live customer requests and solves a problem they actually have. It's about as close to the frontier, and as close to the product, as engineering gets.

03What you'll do
Invent and ship optimizations. Design new strategies across every layer of a request: prompt and context compression, tool pruning, file and dev-command trimming, semantic caching, cache-prefix stabilization. Then take them all the way to the hot path. Each one has to cut tokens on real traffic without degrading output.
Prove every win. Build the evals and the token/quality instrumentation that separate a genuine saving from a plausible-sounding one. An optimization only ships when the numbers back it.
Live in the caching trade-offs. Provider prompt caches only pay off on byte-stable prefixes, and a naive rewrite can cost more than it saves. A lot of the job is knowing exactly when an optimization actually wins: deterministic transforms, per-session decision pins, semantic dedup.
Build and own the gateway that runs them. The real-time proxy that carries production LLM traffic, with streaming, retries and backpressure, executing every optimization on the live request path.
Keep it fast and deploy anywhere. Defend a tight latency budget on the hot path, and package the whole thing so it installs cleanly into any customer's cloud, whether that's AWS, GCP, Azure, containers or Kubernetes, and upgrades without drama.
Own systems end to end. From first commit to code serving live customer traffic, plus the spend-visibility and governance product built on top, with a direct line to the founders.

Connect is a Node CLI and a signed tray app for macOS, Windows and Linux. It points a developer's AI coding tools at our gateway by writing each vendor's own config, signs them in, keeps their credentials fresh, and repairs itself when something drifts. For IT, it ships the artifacts they need to roll it out across a fleet.

It's real, it's shipping, and customers are using it. You'd own it.

03What you'll do
Own Connect. The CLI, the tray app, updates, docs, and what ships next.
Write into other apps' config without breaking them. Back up what you touch, roll back cleanly, and never leave someone's setup worse than you found it.
Keep up with vendors. Config shapes change under us. Check before writing, and fall back to a manual path instead of guessing.
Stay clear of antivirus. Persistence and credential helpers are exactly what EDR watches for. Measure what actually trips a scanner instead of assuming.
Ship for managed fleets. Profiles, policy, credential helpers, and silent rollout. That's what an admin needs to push this to a few hundred laptops at once.
Make it debuggable from far away. Health checks, repair commands, and diagnostics that carry metadata only. Never prompts, never keys.