--- title: 'Lead Endpoint Researcher at PointFive' canonical: 'https://feeny.ai/job/lead-endpoint-researcher-pointfive-tel-aviv-7t2rgbeb0jhc' type: 'job' last_seen: '2026-11-11' --- # Lead Endpoint Researcher at PointFive - **Company:** PointFive - **Location:** Tel Aviv, Israel - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-09-23 - **Last confirmed live:** 2026-11-11 - **Apply:** https://jobs.ashbyhq.com/pointfive/6e1c4d79-a7c3-473d-bb25-c670dca0b3e4 ## Job description ## About PointFive PointFive finds the cost buried inside enterprise infrastructure, from the cloud to coding agents. We pioneered DeepWaste across cloud and data platforms, and we are now doing the same for AI token spend with TokenShift. Fanatics, H&M, Hertz, Nubank, Citizens Bank and other Fortune 500 companies use PointFive to see and cut what their infrastructure and AI actually cost. We have raised $96 million, most recently a [$60 million Series B led by Accel](https://www.pointfive.co/press/pointfive-raises-60m-series-b). Engineering sits in Tel Aviv and our go-to-market team is focused on North America. PointFive Labs, our research arm, publishes original work on how infrastructure and AI actually get paid for. [CRN named us one of the 10 hottest cloud computing startups of 2026](https://www.crn.com/news/cloud/2026/the-10-hottest-cloud-computing-startups-of-2026-so-far?page=9), [Forbes Israel put us on its Next Billion Dollar Startups list](https://forbes.co.il/rankings/2025nextbilliondollarstartups/), and [Redpoint selected us for its InfraRed 100](https://www.pointfive.co/press/pointfive-infrared-100), its ranking of the private companies shaping the future of cloud infrastructure. ## About the Role TokenShift is PointFive's newest product — an endpoint runtime for AI coding agents that gives organizations control, visibility, and efficiency across how agents execute commands and consume models. As AI agents move from chat interfaces into developer machines, they increasingly need access to shells, filesystems, credentials, developer tools, and local compute. At the same time, enterprises are beginning to run models locally — on laptops, workstations, developer VMs, and managed endpoint fleets — across a wide variety of operating systems and hardware architectures. This role exists to push that frontier forward. You'll research how AI coding agents execute and isolate workloads, design secure sandboxing mechanisms, and build the infrastructure required to deploy and operate local models across heterogeneous endpoint environments. You'll work across macOS, Windows, Linux, WSL, developer containers, and other runtime environments, figuring out how to provide agents with powerful capabilities without giving them unrestricted access to the machine. It's a rare opportunity to work at the intersection of operating systems, endpoint security, AI infrastructure, local inference, and developer tooling — in a product already running inside enterprise engineering environments. ## What You'll Do - Research AI coding agent runtimes — reverse-engineer how tools such as Claude Code, Cursor, Copilot CLI, Codex, and emerging agents execute commands, access files, spawn processes, and interact with the operating system. - Design agent sandboxing architectures that safely constrain filesystem access, networking, process execution, credentials, and other sensitive endpoint capabilities. - Explore and implement OS-native isolation mechanisms across macOS, Windows, and Linux, including containers, namespaces, sandbox profiles, virtualization, restricted processes, and permission models. - Build endpoint "harnesses" that allow TokenShift to intercept, control, observe, and modify agent execution flows. - Design infrastructure for deploying and running local LLMs across heterogeneous endpoint fleets, accounting for operating system, CPU architecture, GPU availability, memory constraints, and hardware acceleration. - Evaluate local inference runtimes and model formats such as llama.cpp, MLX, ONNX Runtime, Ollama, vLLM-compatible runtimes, and emerging alternatives. - Develop mechanisms for model discovery, installation, versioning, updates, health monitoring, and lifecycle management across large numbers of developer machines. - Research hardware-aware model selection and routing — deciding which models can run effectively on Apple Silicon, NVIDIA GPUs, Windows workstations, Linux machines, CPU-only environments, and other endpoint configurations. - Build benchmarks that measure model latency, throughput, memory consumption, startup time, resource contention, and developer experience on real endpoint hardware. - Investigate security boundaries between local models, cloud-hosted models, agents, MCP servers, shells, and enterprise resources. - Collaborate with the core CLI and platform teams to take endpoint research from prototype through production. - Track the rapidly evolving AI agent, sandboxing, and local inference ecosystems and proactively identify technologies PointFive should support. ## What We're Looking For Must-have - Deep understanding of operating system fundamentals: processes, permissions, filesystems, IPC, networking, signals, and process trees. - Strong understanding of sandboxing and workload isolation concepts. - Hands-on systems experience across multiple operating systems, ideally including Linux, macOS, and Windows. - Experience building or debugging software that runs directly on developer endpoints, workstations, or servers. - Comfort operating close to the metal — binary behavior, system calls, OS APIs, environment variables, config files, process injection/interception, and runtime behavior. - Investigative, reverse-engineering mindset — you enjoy taking apart systems you didn't build and figuring out how they actually work. - Ability to move comfortably between research prototypes and production-quality systems code. ## Nice to have - Experience running or deploying local LLMs using frameworks such as llama.cpp, MLX, Ollama, ONNX Runtime, or similar inference runtimes. - Understanding of model quantization, KV-cache behavior, GPU memory constraints, model loading, and inference performance. - Experience with NVIDIA CUDA, Apple Metal, DirectML, ROCm, or other hardware acceleration stacks. - Experience with Linux namespaces, seccomp, cgroups, AppArmor, SELinux, eBPF, or container runtimes. - Familiarity with macOS sandboxing, Endpoint Security Framework, launchd, XPC, virtualization, or Apple Silicon. - Familiarity with Windows security primitives, Job Objects, AppContainers, Windows Sandbox, Hyper-V, WSL, ETW, or Windows process APIs. - Hands-on familiarity with AI coding agents such as Cursor, Claude Code, Copilot CLI, and Codex. - Experience with endpoint management or fleet deployment technologies such as MDM, Intune, Jamf, SCCM, or enterprise software distribution systems. - Experience with containers, microVMs, or lightweight virtualization technologies. - TypeScript experience. Our Tech Stack Go, TypeScript, Cloudflare, Snowflake, local inference runtimes, and OS-native endpoint technologies across macOS, Windows, and Linux. ## Why PointFive - Founders with a track record Built and sold IntSights to Rapid7. Backed by top-tier investors with deep conviction in this category. - Category-defining product We're building the control plane for how AI agents operate across enterprise engineering environments — from model access to endpoint execution. - Hard systems problems AI agents are becoming increasingly powerful, but giving them access to developer machines introduces an entirely new class of security, isolation, performance, and infrastructure challenges. You'll work directly on those problems. - Local AI is becoming infrastructure As capable models increasingly run on laptops and workstations, enterprises will need a way to deploy, manage, secure, and govern them across thousands of heterogeneous machines. You'll help define how that infrastructure works. - Early-stage leverage Your research will directly shape the architecture of the product and determine which capabilities PointFive can deliver next. - Frontier of AI developer tooling Agents, local models, and endpoint runtimes are evolving extremely quickly. You'll be researching and integrating technologies before they become standard parts of the enterprise developer stack. ## About PointFive ## Company Overview - **One-liner**: PointFive is an AI-powered cloud and AI efficiency platform that autonomously detects deep infrastructure waste and remediates it through engineering-native workflows. - **Entity Type**: Private (Seed & Series A funded) - **Headquarters**: New York City, New York, United States (with offices in Tel Aviv, London, Denver, and Boston) - **Founded**: 2023 - **Founders**: Alon Arvatz (CEO), Amir Hozez (CTO), Gal Ben David (CPO) ## Core Business - **Primary industry**: Cloud & AI Efficiency Management / FinOps / Infrastructure Optimization - **Target customers**: B2B, Enterprise, Engineering and FinOps teams at mid-to-large scale cloud-native companies - **Mission/purpose**: "To enable continuous cloud cost efficiency through deeper detection and collaborative remediation tools that integrate seamlessly with teams' natural workflows." PointFive aims to change the typical cloud operating efficiency from 66% to near-100% by making cost efficiency a core engineering principle. ## Products & Services - **Cloud Efficiency Platform (Core)**: A SaaS platform that connects read-only to AWS, Azure, GCP, Kubernetes, Snowflake, and Databricks. It uses DeepWaste™ detection (400+ detection types) to surface hidden waste and provides agentic remediation — drafting PRs, opening Jira tickets, routing owners via Slack, and verifying fixes land in production. - **TokenShift (AI Spend Governance)**: An extension that governs and accounts for every token used by coding agents in the IDE. It attributes AI coding-agent spend to specific teams and repos, enforces model and budget compliance, and provides a unified governance posture from cloud to coding agent. - **Remediation Workflow Engine**: Automates the full loop — from finding waste, to drafting Terraform/Kubernetes-native fixes, to owner routing (via Git blame + service catalog), to tracking realized savings back to the FinOps ledger. - **Unit-Economics Ledger**: Provides board-ready views of $/inference, $/customer, $/ARR, and other unit metrics with a full audit trail (SOC 2 Type II, ISO 27001). ## Market Standing - **Total Funding**: $36M across two rounds - Seed Round (June 2024): $16M led by Index Ventures - Series A (November 2024): $20M led by Salesforce Ventures and Ironwood Ventures - **Key Metric**: $50M+ in savings identified across customer environments; 1,200%+ customer ROI; 4.9 ★ rating on G2 - **Notable Investors/Partners**: Index Ventures, Salesforce Ventures, Ironwood Ventures - **Growth Signals**: - 111 employees (+70.7% YoY, +53 people) - Operating in 5 countries (Israel, USA, UK, Switzerland, Canada) - 17 active job postings (postings up 1600% YoY) - 6,623 LinkedIn followers (+82.3% YoY) - Proven at scale with customers like Nubank (10 days to value), Elastic, and Blackhawk Network - LinkedIn talent sources include Amazon Web Services, Rapid7, Check Point Software, and IBM Kubecost ## Competitive Advantages - **DeepWaste™ Detection**: Goes beyond utilization-based detection — correlates configuration, telemetry, and code to surface *why* a resource is wasteful, not just that it is. Covers 400+ detection types across 6 cloud/data platforms. - **Agentic Remediation**: Unlike legacy FinOps tools that stop at dashboards and spreadsheets, PointFive autonomously drafts and merges fixes (Terraform PRs, Jira tickets, Slack routing) and verifies them in production — turning insights into realized savings. - **InfraFabric™ Graph**: Proprietary infrastructure dependency graph that maps ownership, context, and relationships across the entire cloud estate without agents or data-plane access. - **Cloud-to-Coding-Agent Governance**: The only platform that follows AI waste from the cloud all the way to the IDE, covering both infrastructure and AI coding-agent spend in one unified posture. - **Engineering-Native Workflow**: Findings appear where engineers already work (Slack, Jira, as drafted PRs) with effort estimates and rollback paths included — making cost optimization a code-review concern, not a quarterly fire drill. ## Strategic Focus - **Product Expansion**: Deepening AI spend governance (TokenShift) and extending detection/remediation across more cloud services and data platforms. - **Go-to-Market**: Scaling enterprise sales in the US (West, East), UK/EMEA, and expanding the field sales and solutions engineering teams. - **Hiring Momentum**: Actively growing the team — 17 open roles across Engineering, Sales, Marketing, Research, and IT — with a focus on senior talent and leadership hires. - **Category Creation**: Establishing "Cloud & AI Efficiency Management" as a new category distinct from legacy FinOps dashboards, with a strong emphasis on autonomous remediation and realized savings. ## Why Work Here - **High-growth environment**: 70%+ YoY headcount growth, $36M in funding from top-tier VCs, and proven product-market fit with major enterprise customers. - **Engineering culture**: The platform itself is built for engineers, and the company's values — "Prioritize Efficiency," "Raise the Bar," "Trust Each Other," "Stay Humble" — reflect a deep technical and collaborative ethos. - **Remote/hybrid policy**: Multiple office locations (New York, Tel Aviv, London, Denver, Boston) with a distributed team across 5 countries; roles span in-office, hybrid, and remote depending on location and function. - **Notable perks/culture**: - "Cost as a code-review concern" — engineers get to work on a product that genuinely delights other engineers - Fast-paced startup with significant ownership and impact from day one - Strong Israeli engineering presence (53% of workforce in Israel) with deep cloud/infra expertise - Leadership team includes serial entrepreneurs and veterans from cloud/infrastructure companies - Recent hires from AWS, Rapid7, Check Point, and Kubecost — strong talent density - **Active roles**: Staff Backend Engineer, Staff Frontend Engineer, Business AI Engineer, Enterprise Account Executives (multiple regions), Director of Global Solutions Engineering, Inside Sales, SDR, Product Marketing, Brand & Creative, and more. ## Sources 1. [PointFive Website](https://www.pointfive.co/) 2. [PointFive Careers Page](https://jobs.ashbyhq.com/pointfive) 3. [PointFive About Page](https://www.pointfive.co/about) 4. [PointFive LinkedIn](https://www.linkedin.com/company/pointfive-us) 5. [Tracxn Company Profile](https://tracxn.com/d/companies/pointfive/__gEFj1ptC_oL8LB-nwyoGrueGMTGZ-7ciAetTjgZ_SvY) ## Other roles at PointFive - [Enterprise Sales Development Representative](https://feeny.ai/job/enterprise-sales-development-representative-pointfive-denver-9jsj4499nccn) — Denver, CO - [Technical Support Lead](https://feeny.ai/job/technical-support-lead-pointfive-new-york-60n716542w8s) — New York, NY - [Social & Content Lead](https://feeny.ai/job/social-content-lead-pointfive-tel-aviv-q5mdmrxzxpax) — Tel Aviv, Israel - [Senior Bookkeeper](https://feeny.ai/job/senior-bookkeeper-pointfive-tel-aviv-76pvfce1nfyn) — Tel Aviv, Israel - [Kubernetes Researcher](https://feeny.ai/job/kubernetes-researcher-pointfive-tel-aviv-1v6s6q3ev3a1) — Tel Aviv, Israel - [Senior Product Manager](https://feeny.ai/job/senior-product-manager-pointfive-tel-aviv-2vwrcpkq60gf) — Tel Aviv, Israel - [Staff Backend Engineer](https://feeny.ai/job/staff-backend-engineer-pointfive-tel-aviv-tr2g7ngpvhj4) — Tel Aviv, Israel - [Senior Software Engineer - Endpoint](https://feeny.ai/job/senior-software-engineer-endpoint-pointfive-tel-aviv-mk3c4nrfdsec) — Tel Aviv, Israel - [Enterprise Sales Development Representative](https://feeny.ai/job/enterprise-sales-development-representative-pointfive-boston-fjsner85c8yw) — Boston, MA - [Backend Tech Lead](https://feeny.ai/job/backend-tech-lead-pointfive-tel-aviv-2mdxkd7a3q7g) — Tel Aviv, Israel