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We are seeking an experienced and highly driven Senior Hardware NPI Program Manager to lead the successful introduction of next-generation hardware products from concept through volume production. In this role, you will partner cross-functionally with Hardware Engineering, Operations, Product Management, and Quality teams to ensure flawless execution of product launches. The ideal candidate has a proven track record of managing complex hardware programs, driving schedules and deliverables across global teams, and enabling a seamless transition from development to scalable manufacturing. There will also be opportunities to manage internal HW,SW and Operational projects with partners.
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.
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.
Key Responsibilities
Own and drive the end-to-end NPI program lifecycle for hardware products, from concept through ramp to sustaining to EOL
Develop, manage, and track detailed project plans, schedules, risks, and dependencies across multiple functions and suppliers
Partner with Engineering to translate product requirements into manufacturable designs and processes
Coordinate with Supply Chain, Manufacturing, and Quality to ensure suppliers and factories are ready for builds and scale
Lead cross-functional meetings, program reviews, and executive updates to communicate status, risks, and recovery actions
Proactively identify program risks, define mitigation strategies, and drive accountability for execution
Ensure manufacturing readiness by leading build events (EVT, DVT, PVT, MP) and ensuring exit criteria are met at each stage
Align stakeholders across engineering, operations, and customer support for smooth product release into the field
Continuously improve NPI processes and best practices to increase efficiency and scalability.

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.

Every LLM call carries tokens that don't need to be there, and the provider bills for all of them. Anyray sits between a company's users and the models and takes that waste out as the request goes through. The result is usually up to 60% off the inference bill with no change in output, and every saved token accounted for. It runs inside the customer's own cloud, so nothing leaves their network, works with whatever provider and model they already use, and goes in within minutes.

02What you'll do
Build your own pipeline. That means targeted outbound to engineering and platform leaders, starting in the Israeli ecosystem and moving into the US.
Run deals start to finish: demo the product, handle the technical conversation yourself, and carry evaluations through to a signature.
Own the GTM engine: the outbound, the deal process, the playbooks, the collateral.

What You Will Be Doing
Own the co-build agenda with AWS & GCP
Drive our active co-build initiatives with AWS/GCP product and engineering teams from scoping through launch.
Own the technical relationship with AWS/GCP product managers and engineers on the EKS/GKE, Karpenter, and container services teams. Be the person they call, and the person who can answer without scheduling a follow-up.
Track the EKS/GKE and AI/ML roadmap closely enough to tell us what it means. Dynamic Resource Allocation, MIG and time-slicing landing in Karpenter and Auto Mode/Auto Pilot, managed control plane work, and pod isolation all move the ground under our product. You will be the first person to see it coming.
Continuously validate that we run on where AWS/GCP are going, not just where it is. As AWS/GCP abstracts the node further, our agent, our scheduler, and especially our GPU device plugin need to keep working. Confirming that, early, is a standing part of the job.
Bring AWS/GCP requirements and constraints back into R&D as real engineering input, and represent our architecture back to AWS/GCP accurately enough that they design around it.
Look for opportunities to be a design partner and later a launch partner.
Technical depth on us and EKS/GKE
Be the person who can explain how we work on EKS/GKE to any technical audience, without an SE in the room: real-time pod right-sizing, HPA and replica management, intelligent pod placement, Karpenter and node optimization, Spot, and GPU fractionalization and right-sizing for inference workloads.
Hold your own with AWS/GKE Solutions Architects and customer platform engineers on scheduling, autoscaling, resource management, and where our approach differs from static MIG and time-slicing.

What You'll Be Doing:
Collaborate with the sales team to develop and execute strategies for opening new accounts.
Identify companies that fit our Ideal Client Profile.
Create personalized messaging to generate interest.
Schedule discovery calls for Account Executives.
Outbound prospecting through email, phone calls, and social media to schedule meetings.
Becoming an expert on how we help customers.
Meticulously track and improve your outbound activity.
Hitting daily KPIs for dials, meetings completed, and pipeline generated.
Collaborate with team members to share and learn from best practices.

What You Will Be Doing
Lead and grow a high-performing engineering organization responsible for our core product offering.
Define and execute the engineering strategy for our Kubernetes resource management platform, enabling DevOps teams worldwide to operate more efficiently.
Partner closely with Product, Design, and Go-to-Market leaders to translate business strategy into engineering execution.
Drive technical excellence, architectural direction, and engineering best practices across multiple teams.
Build, mentor, and develop engineering managers and senior engineers, fostering a culture of ownership, innovation, and continuous improvement.
Scale engineering processes, organizational structure, and delivery capabilities while maintaining a high bar for quality and execution.
Balance hands-on technical leadership with organizational leadership, making key architectural and strategic decisions when needed.
Create an environment where talented engineers can do their best work with a high degree of autonomy, accountability, and collaboration.

We're seeking a talented, experienced Software Engineer to join our Backend Engineering team - diving deep into Kubernetes and related technologies like Istio, Helm, and Prometheus, tackling daily engineering challenges, driving innovation in Kubernetes optimization, and working with cutting-edge tools and frameworks such as container orchestration, microservices architecture, and cloud-native applications.

Join a highly skilled team building our core product offering.
Build a world-class Kubernetes resource management platform to improve the productivity of DevOps teams across the world.
Gain a deep understanding of Kubernetes and container technologies.
Write extensive code in Go and develop deep expertise in Kubernetes internals.
Enjoy a high degree of autonomy and responsibility.

We are seeking a hands-on Tech Lead to join our Backend Engineering team and lead the shaping of the architecture and development of our Kubernetes-based platform. This role combines strong technical ownership with team leadership and is ideal for someone passionate about building complex systems and mentoring others. As a Tech Lead, you'll be a technical authority in everything cloud-native - leading feature development, making key architectural decisions, and collaborating with cross-functional teams to drive innovation.

Lead backend development efforts and serve as a key decision-maker on architecture, design, and implementation.
Work closely with other engineers to develop robust, scalable, and efficient systems.
Dive deep into Kubernetes, Go, microservices, and other backend technologies.
Take technical ownership while mentoring engineers and promoting best practices.
Collaborate with product and DevOps teams to ensure smooth feature delivery.
Act as a thought leader and help shape our technology vision.

We're looking for an experienced Software Architect to join ScaleOps and help shape the next generation of our platform. This role is ideal for someone who thrives on designing systems at scale and thinking strategically about performance, reliability, and scalability. As our Architect, you'll work alongside top-tier engineers and leadership to design the core infrastructure of our platform and guide engineering teams through best practices and architectural excellence.

Define and evolve the architecture of our cloud-native platform.
Drive technical direction and influence long-term product and infrastructure decisions.
Work hands-on with teams to review designs, suggest improvements, and solve deep technical challenges.
Collaborate with team leaders and senior engineers to scale the system while keeping it reliable and performant.
Lead complex architecture discussions around Kubernetes, Go, microservices, and cloud infrastructure.

We're looking for a Researcher who thrives on exploring the technical frontier and translating complex insights into real-world impact. This is a hands-on role, combining deep research with prototyping and cross-team collaboration, with the goal of driving innovation in Kubernetes internals, cloud infrastructure, and performance optimization.

Conduct deep research into Kubernetes internals, scheduling, autoscaling, and container resource usage.
Explore cutting-edge strategies for cloud resource optimization, cost efficiency, and performance engineering.
Design and deliver hands-on POCs, simulations, and benchmarks to validate new approaches.
Work closely with product and engineering teams to translate research findings into features and enhancements.
Stay at the forefront of the cloud-native and FinOps ecosystems, surfacing trends and opportunities.
Contribute to technical blogs, white papers, and internal knowledge sharing.

What You'll Be Doing
Own our infrastructure end-to-end - our self-hosted product, its installation and onboarding flows, our SaaS platform, and AI infrastructure.
Manage our cloud infrastructure across AWS, GCP, and Azure - networking, security, SSO, and compute.
Work closely with customers on deployments and troubleshooting.
Collaborate closely with backend, product, and R&D teams to support rapid feature delivery without compromising reliability.
Identify and eliminate operational toil through automation and tooling improvements.
Maintain security and compliance best practices across the infrastructure stack.

We're looking for a Head of Research to establish and lead our research group - a strategic and hands-on leadership role for someone who thrives at the intersection of AI, infrastructure, and systems innovation. You'll identify high-impact research directions, validate cutting-edge technologies, and drive new approaches that translate into long-term competitive advantage for us. This is not an academic position, but an opportunity to build a research function that directly shapes product and technology.

Define and lead the company's research agenda in AI, infrastructure, and distributed systems.
Explore and evaluate new algorithms, architectures, and approaches relevant to large-scale AI workloads and cloud cost efficiency.
Collaborate with product and engineering to translate research into real-world impact.
Build and manage a small, high-caliber research team.
Publish findings, represent us in the AI/infrastructure research community, and establish partnerships with academia and industry.
Act as a thought leader driving innovation across the company.