PointFive

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. 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, Forbes Israel put us on its Next Billion Dollar Startups list, and Redpoint selected us for its 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 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. 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, Forbes Israel put us on its Next Billion Dollar Startups list, and Redpoint selected us for its InfraRed 100, its ranking of the private companies shaping the future of cloud infrastructure. About the Role We're looking for a Senior Product Manager to own TokenShift, PointFive's product for finding and cutting wasted AI token spend. This is a chance to define product strategy for a brand-new category, working hands-on with R&D on how AI agents and LLM models actually run, get monitored, and get paid for in production. You'll take TokenShift from early adoption to a core pillar of PointFive's platform, alongside our flagship DeepWaste product. What You'll Do • Own the product strategy and roadmap for TokenShift, from discovery through GA and beyond. • Translate a deep technical understanding of how AI agents and LLM workloads run — inference calls, endpoints, agent harnesses and orchestration — into requirements R&D can build against. • Partner with R&D, design, and data science to scope, prioritize, and ship features that surface and reduce AI token waste. • Work directly with enterprise customers and prospects to understand how they deploy AI agents in production and where their cost and visibility gaps are. • Define and track success metrics — adoption, cost savings, detection accuracy — and use them to drive roadmap decisions. • Collaborate with go-to-market teams on positioning, messaging, and launch plans for new capabilities. • Stay current on the landscape: coding agents and harnesses, LLM gateways and routers, AI observability, and endpoint management. • Represent the voice of the customer internally, balancing technical depth with business impact. What We're Looking For Must-have • Technical background, e.g. former software engineer or technical PM with hands-on coding or systems experience. You use AI coding agents daily and understand them from the inside. • Experience with products deployed as an agent on endpoints, such as EDR/XDR, AI agent security, or visibility and compliance tools: agents running on endpoints, telemetry collection, detection and policy logic. • Working knowledge of AI agent harnesses and frameworks — how agentic AI systems are built, evaluated, and deployed in production. • 4+ years of product management experience shipping complex technical B2B products, ideally developer tools or infrastructure. • Strong analytical skills; comfortable working with usage and cost data at scale. Nice to have • Experience with cloud cost management, FinOps, or infrastructure observability products. • Background in cybersecurity or threat-detection products. • Hands-on experience with LLM provider APIs (OpenAI, Anthropic, etc.) or token-based pricing models. • Hands-on experience with LLM routing, AI gateways, or model evaluation and benchmarking. 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 DeepWaste detection and agentic remediation with clear, measurable ROI for both engineering and finance teams. • Early-stage leverage Your work directly shapes the product, the culture, and the go-to-market playbook. • Ground floor of a new category You'll help define AI token cost management as a product category from near-zero, with direct access to founders and R&D leadership on where TokenShift goes next.

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. 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, Forbes Israel put us on its Next Billion Dollar Startups list, and Redpoint selected us for its InfraRed 100, its ranking of the private companies shaping the future of cloud infrastructure. About the Role We're looking for a Senior Bookkeeper to own bookkeeping for PointFive's Israeli company and US subsidiary, end to end. It's a hands-on role in a growing finance team in Tel Aviv, where you'll run the close, payroll and payments, and help build cleaner, more automated processes in NetSuite and Ramp. What You'll Do • Own full-cycle bookkeeping for PointFive Ltd. (Israel) and PointFive US Inc. up to a reviewed trial balance and balance sheet • Lead the monthly close for both entities: accruals, prepaid amortization, bank/card/AP/AR reconciliations, cut-off • Manage intercompany activity: monthly recharge invoicing per the transfer pricing model, intercompany reconciliation and FX • Run Israeli payroll end-to-end in Shiklulit: monthly payroll, pension and Bituach Leumi payments, Forms 102, 126 and 106, final settlements for leavers, and payroll journal entries • Own US bookkeeping in-house: TriNet payroll entries, AP and payments, 1099 filings, sales tax support, and coordination with the US tax preparer • Spend management in Ramp: card reconciliation, reimbursements, policy enforcement, and leading the move of AP invoices into Ramp • AP end-to-end for both entities, including vendor onboarding (W-9/W-8, Israeli withholding certificates) and payment runs • AR and cash application, including reconciliation of Marketplace disbursements against customer invoices • Record UK employee costs from Deel • Israeli statutory reporting: VAT, withholding (Nikuim), advance payments (Mikdamot), Form 856 • Support audits, the 409A process, and US/Israeli tax filings with external advisors • Improve processes and automation within NetSuite and Ramp What We're Looking For • 5+ years of bookkeeping experience in high-tech, including at least 2 years as the sole or lead bookkeeper of an Israeli company with a US subsidiary (must) • Certified Bookkeeper Type 3 (must) • Hands-on Israeli payroll processing (must) • Hands-on US bookkeeping experience, including PEO payroll entries, 1099s and sales tax basics (must) • Hands-on NetSuite experience in a multi-entity, multi-currency environment (must) • Experience with Brex or Mesh - must (Ramp is an advantage) • Experience with IL payroll processing tool (Shiklulit is an advantage) • Certified Payroll Accountant (strong advantage) • High-level English, written and spoken (must) • Strong Excel skills (Pivot, XLOOKUP) • Advantage: AI automation processes in finance, Marketplace experience 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: DeepWaste detection and agentic remediation with clear, measurable ROI for both engineering and finance teams. • Early-stage leverage: Your work directly shapes the product, the culture, and the go-to-market playbook. • Build the finance engine: Own the books for two entities and help a growing company move fast with clean, automated processes.

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. 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, Forbes Israel put us on its Next Billion Dollar Startups list, and Redpoint selected us for its InfraRed 100, its ranking of the private companies shaping the future of cloud infrastructure. About the Role TokenShift is PointFive's newest product — a lightweight CLI proxy that sits between AI coding agents and the shell or server, routing to different models for perfect model to effort fit, compressing command output to cut token spend and surface fleet-wide visibility. As an Senior software Engineer (Endpoint), you'll own the layer that makes TokenShift work: the per-agent harnesses, the compression rules and strategies, and the installation and hook mechanics that get us onto developer machines — reliably, invisibly, and at scale. This is a rare chance to build foundational infrastructure for AI developer tooling, at a company where your work directly shows up in the product used by engineering teams at companies like Expedia and EON. What You'll Do • Own the installation and enrollment mechanics — the CLI flows, MDM scripts, and platform-specific packaging (Windows msi/exe, macOS pkg, Linux deb/rpm) that put TokenShift on developer machines at fleet scale. • Instrument and monitor endpoint behavior through the telemetry pipeline, using signals to improve coverage and catch regressions. • Build and maintain a robust lab enabling automatic research and development of new capabilities and platforms by AI agents. • Build and maintain agent harnesses — the per-agent adapters that hook into Claude Code, Cursor, Copilot CLI, Codex, and future agents to route network and shell commands through the TokenShift proxy. • Develop and extend compression rules and strategies for new command types (git, build tools, infra CLIs, search, and more), ensuring token reduction never comes at the cost of semantic accuracy. • Maintain correctness and resilience of the proxy layer — compression must be reversible on demand, hooks must never block a developer's command, and failures must be silent and transparent. • Collaborate with the research team to translate newly supported agent architectures into production-grade harnesses. What We're Looking For Must-have • Solid understanding of Windows and Unix fundamentals: process model, shell execution, stdin/stdout/stderr, file permissions, and IPC. • Deep familiarity with MDM deployment patterns (Jamf, Intune, JumpCloud, Ansible). • Strong proficiency in Go — the TokenShift CLI is written in Go, and this is where the core work happens. • Experience building or maintaining CLI tools in production environments. • Attention to correctness and edge cases — you think about what happens when things go wrong before they do. • Ability to work across platforms (macOS and Linux) and understand their differences at the system level. Nice to have • TypeScript experience. • Hands-on experience with AI coding agents (Cursor, Claude Code, Copilot CLI, Codex) as a user or developer. • Experience with semantic compression, summarization, or output parsing. Our Tech Stack Go, TypeScript, Cloudflare, Snowflake 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 DeepWaste detection and agentic remediation with clear, measurable ROI for both engineering and finance teams. • Early-stage leverage Your work directly shapes the product, the culture, and the go-to-market playbook. • You'll build the infrastructure layer for AI developer tooling The part that actually runs on every developer's machine, quietly making every agent session cheaper and more visible.

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. 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, Forbes Israel put us on its Next Billion Dollar Startups list, and Redpoint selected us for its InfraRed 100, its ranking of the private companies shaping the future of cloud infrastructure. The Role We're looking for a researcher who has run real production workloads on Kubernetes and wants to turn that experience into detections that thousands of engineers will trust. You'll own Kubernetes cost efficiency end to end: it starts with "this looks expensive," moves through real billing, metrics and inventory data, and finishes with a shipped detection that gets adopted by verity of engineering teams who act on it. This role sits at the junction of research, product and engineering: you pick the problem, prove it against real customer data, and take it to production. You’ll set the standard and best practices for k8s efficiency. The detections you develop will run in a variety of complex Kubernetes environments across the planet, and engineering teams everywhere will build on what you discover. What You'll Do • Research and ship new Kubernetes detections. Find optimization opportunities, prove them against real customer data • Lead the Kubernetes domain end to end: the detection library and build the road map to maximize value. • Work hand-in-hand with engineering, and go deep wherever the problem takes you: Kubernetes internals, cloud provider APIs, billing systems, data pipelines. This is a technical role, not a research-only one. • Bring domain expertise into pre-sales and post-sales processes, directly and tightly working with prospects to maximize value • Publish thought-leadership content on Kubernetes cost efficiency: blog posts, white papers, OSS, webinars or live sessions. Must Have • 3+ years running production workloads on Kubernetes (EKS, GKE or AKS) as an SRE, platform, DevOps or infrastructure engineer. You've been on-call for it, and you know how requests and limits drive scheduling and pod packing, how the cluster autoscaler and Karpenter behave under real load, why a node group's minimum size is set where it is, and what breaks when you change instance architecture or generation. • Independent and comfortable owning a ambiguity problem e2e from first hypothesis to shipped detection. • Ability to orchestrate engineering work: translate research findings into clear technical requirements, align priorities with engineering teams, and coordinate delivery through to production. • Deep, hands-on AWS knowledge (EC2, EKS, ECR, networking, Savings Plans, RIs, and more), and working knowledge of Azure or GCP. • Strong quantitative skills: analytics, statistics, modeling. You can take complex, unstructured data, build the right model or calculation for it, and know exactly why the numbers hold up. • A skeptical, evidence-first mindset: you look for the reason a recommendation is wrong before you look for the reason it's right. • Clear communication skills. You can explain a technical finding and its business impact to different stakeholders. Nice to Have • Experience running AI/ML infrastructure: GPU node pools, inference serving, or managed model platforms (Bedrock, Azure OpenAI, Vertex AI), including per-token and provisioned-throughput pricing. • Hands-on FinOps experience: AWS CUR, Split Cost Allocation Data, FOCUS, cost allocation and chargeback. • Hands-on experience in dbt, Snowflake, GO • Experience with ARM/Graviton migrations or large-scale rightsizing programs. • Data platform experience (Databricks, Snowflake, BigQuery). • Published technical research artifacts (blog/white papers/OSS) or experience in public speaking (conferences, meetups). • Contributions to related open-source projects. • Prior cloud security research experience. • Academic background Success in Your First 6 Months • You own Kubernetes cost efficiency as an area and have shipped several new detections in it. • Customer teams have reviewed, approved and implemented your recommendations across their environments, and the findings held. Why Join • Your work reaches engineering teams that spend millions a month on cloud, and they act on it. • You'll work with real cost, inventory and metrics data from hundreds of production environments on every major cloud, so you'll see patterns no single company sees. • A small research team with high ownership: you pick the problem, prove it, and solve it. • Go deep You will study Kubernetes environments in full depth. You will define the best practices other teams follow. • A unique opportunity. No other company gives you this exact mix: real Kubernetes research, production-scale data, and direct customer impact.

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. 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, Forbes Israel put us on its Next Billion Dollar Startups list, and Redpoint selected us for its InfraRed 100, its ranking of the private companies shaping the future of cloud infrastructure. About the Role We're looking for an exceptional, hands-on technical leader to join our core engineering team as a true force multiplier and technological anchor for the company. You'll have the flexibility to drive high-impact initiatives from conception to production, own complex technical and AI domains end-to-end, or guide and level up a focused delivery team — operating with a high degree of autonomy in an ambiguous, fast-moving environment. What You'll Do • Drive strategic initiatives: lead complex technical projects, AI feature developments, and core architectural components with an ownership mindset. • Architect for AI & data at scale: design robust, scalable infrastructure and pipelines capable of handling massive volumes of cloud infrastructure data. • Bridge product, AI & tech: collaborate closely with Product Managers and data specialists to translate business roadmaps into high-performance technical systems. • Promote engineering excellence: establish development guidelines, lead design and architecture reviews, and raise the bar for code quality across teams. • Mentor & guide: act as a technical mentor to fellow engineers through hands-on collaboration, deep code reviews, and architectural consultation. What We're Looking For Must-have • 8+ years of experience in backend software engineering, with a proven track record designing, building, and operating large-scale cloud production systems. • Strong coding fundamentals in backend technologies such as Go, Python, Java, etc. • Experience leveraging AI coding agents (e.g., Claude Code) and implementing AI-oriented workflows to enhance team productivity and code quality. • Production-grade experience with AWS, containerization (Kubernetes/Docker), microservices, and distributed databases/data warehouses (e.g., PostgreSQL, Snowflake). • Practical experience working with large data volumes, data pipelines, or integrating AI/LLM technologies into production environments. • Demonstrated experience leading technical workflows, driving complex cross-team initiatives, or acting as a full-lifecycle domain owner. • A true independent operator who thrives in fast-paced environments and solves problems end to end. • Ability to build technical consensus, inspire peers, and drive alignment across stakeholders. Our Tech Stack Go, Python, Java, AWS, Kubernetes, Docker, PostgreSQL, Snowflake 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 — DeepWaste detection and agentic remediation with clear, measurable ROI for both engineering and finance teams. • Early-stage leverage — Your work directly shapes the product, the culture, and the go-to-market playbook. • Real technical ownership — as a force multiplier on a core team, you'll set architecture and engineering standards across the R&D org, not just execute against someone else's.

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. 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, Forbes Israel put us on its Next Billion Dollar Startups list, and Redpoint selected us for its InfraRed 100, its ranking of the private companies shaping the future of cloud infrastructure. About the Role We're looking for an exceptional, hands-on leader-engineer to join our core engineering team as a true force multiplier and technological anchor for the company. You'll have the flexibility to drive high-impact initiatives from conception to production, own complex technical and AI domains end-to-end, or guide and level up a focused delivery team — operating with a high degree of autonomy in an ambiguous, fast-moving environment. What You'll Do • Drive strategic initiatives: lead complex technical projects, AI feature developments, and core architectural components with an ownership mindset. • Architect for AI & data at scale: design robust, scalable infrastructure and pipelines capable of handling massive volumes of cloud infrastructure data. • Bridge product, AI & tech: collaborate closely with Product Managers and data specialists to translate business roadmaps into high-performance technical systems. • Promote engineering excellence: establish development guidelines, lead design and architecture reviews, and raise the bar for code quality across teams. • Mentor & guide: act as a technical mentor to fellow engineers through hands-on collaboration, deep code reviews, and architectural consultation. What We're Looking For Must-have • 8+ years of experience in backend software engineering, with a proven track record designing, building, and operating large-scale cloud production systems. • Strong coding fundamentals in backend technologies such as Go, Python, Java, etc. • Experience leveraging AI coding agents (e.g., Claude Code) and implementing AI-oriented workflows to enhance team productivity and code quality. • Production-grade experience with AWS, containerization (Kubernetes/Docker), microservices, and distributed databases/data warehouses (e.g., PostgreSQL, Snowflake). • Practical experience working with large data volumes, data pipelines, or integrating AI/LLM technologies into production environments. • Demonstrated experience leading technical workflows, driving complex cross-team initiatives, or acting as a full-lifecycle domain owner. • A true independent operator who thrives in fast-paced environments and solves problems end to end. • Ability to build technical consensus, inspire peers, and drive alignment across stakeholders. Our Tech Stack Go, Python, Java, AWS, Kubernetes, Docker, PostgreSQL, Snowflake 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 — DeepWaste detection and agentic remediation with clear, measurable ROI for both engineering and finance teams. • Early-stage leverage — Your work directly shapes the product, the culture, and the go-to-market playbook. • Step into a leadership track on a lean, senior engineering team — set direction for architecture and mentorship from day one.

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. 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, Forbes Israel put us on its Next Billion Dollar Startups list, and Redpoint selected us for its InfraRed 100, its ranking of the private companies shaping the future of cloud infrastructure. About the Role PointFive is building infrastructure for the next generation of AI-powered engineering. As AI agents become embedded into developer workflows, the underlying model layer is changing rapidly. Organizations are no longer choosing between a handful of hosted APIs. They are increasingly operating across frontier models, open-weight models, locally deployed models, specialized models, and dynamically routed combinations of them. We’re looking for an AI researcher to take an integral part in PointFive’s research into how these models behave, how they should be evaluated, and how they can be deployed and used more efficiently across real engineering workloads. This is a deeply technical research role with direct product impact. You’ll study frontier and open-source models, develop evaluation frameworks, investigate inference and model optimization techniques, explore local deployment strategies, and help answer questions such as: Which model should handle a particular task? How much capability do we lose when we quantize it? Can a smaller local model replace a frontier API for a specific workload? How should models be routed across latency, cost, privacy, and quality constraints? How do we measure whether one model is actually better than another for agentic software engineering? Your work will directly shape PointFive’s model strategy and the intelligence behind our AI infrastructure products. What You'll Do • Define and lead PointFive’s LLM research agenda across model evaluation, inference optimization, local models, routing, and model adaptation. • Continuously evaluate frontier and open-weight models across real-world software engineering and agentic workloads. • Design rigorous evaluation frameworks for model quality, reasoning, tool use, code generation, command execution, summarization, and agent behavior. • Build benchmarks that reflect actual developer workflows rather than generic academic tasks. • Research model efficiency techniques including quantization, distillation, speculative decoding, prefix caching, KV-cache optimization, batching, and context management. • Investigate when smaller or locally deployed models can replace expensive frontier models without materially degrading task quality. • Evaluate model architectures, parameter sizes, quantization formats, and runtime configurations across heterogeneous hardware. • Research and benchmark local inference stacks including llama.cpp, MLX, vLLM, SGLang, ONNX Runtime, Ollama, TensorRT-LLM, and emerging runtimes. • Study inference performance across Apple Silicon, NVIDIA GPUs, AMD GPUs, CPUs, Windows workstations, Linux machines, and other endpoint configurations. • Develop model-routing strategies that optimize across quality, latency, cost, privacy, context size, and hardware availability. • Explore intelligent cascades where smaller models handle common tasks and more capable models are invoked only when necessary. • Research model specialization through fine-tuning, LoRA, adapters, distillation, prompt optimization, and other model adaptation techniques. • Investigate model behavior under constrained environments, including offline execution, limited memory, limited compute, and local-only inference. • Evaluate agent-specific model behavior, including planning, tool selection, shell interaction, code editing, error recovery, and long-running task execution. • Analyze failure modes such as hallucination, tool misuse, context degradation, reasoning collapse, excessive token consumption, and unstable agent loops. • Design experiments that quantify the tradeoffs between model capability, inference cost, token consumption, latency, and resource utilization. • Build internal research infrastructure for reproducible model experiments, benchmarking, dataset management, and evaluation. • Track frontier model releases and emerging research, rapidly determining which developments are meaningful for PointFive’s products. • Collaborate closely with engineering and product teams to translate research results into production capabilities. • Build and lead a small, exceptional LLM research team over time. What We're Looking For Must-have • Deep understanding of modern large language models and transformer-based architectures. • Strong hands-on experience evaluating and experimenting with both frontier and open-weight models. • Strong understanding of inference behavior, including prefill, decoding, KV caches, context windows, batching, memory usage, and token generation performance. • Experience with model optimization techniques such as quantization, distillation, LoRA, fine-tuning, or model compression. • Strong experimental mindset — able to formulate hypotheses, design controlled experiments, and draw meaningful conclusions from noisy results. • Experience building evaluation frameworks for LLM quality and behavior. • Strong Python proficiency and familiarity with the modern ML ecosystem. • Ability to read, understand, and reproduce ideas from current ML research papers. • Comfortable working with ambiguous research problems where there may not yet be an established best practice. • Strong ability to bridge research and production — understanding not only whether something works, but whether it is practical to deploy. Nice to have • Experience with open-weight models such as Llama, Qwen, DeepSeek, Mistral, Gemma, GLM, or similar model families. • Experience with frontier model APIs including OpenAI, Anthropic, Google, and other leading providers. • Experience with inference frameworks such as vLLM, SGLang, llama.cpp, MLX, TensorRT-LLM, Ollama, or ONNX Runtime. • Deep understanding of quantization techniques including FP8, INT8, INT4, AWQ, GPTQ, GGUF, and related approaches. • Experience with GPU performance optimization, CUDA, Metal, ROCm, or DirectML. • Familiarity with distributed inference and multi-GPU serving. • Experience with model routing, mixture-of-model systems, cascades, or adaptive inference. • Experience with reinforcement learning, preference optimization, DPO, GRPO, or related post-training techniques. • Familiarity with agentic systems, coding agents, tool-use models, and computer-use models. • Experience building or evaluating coding benchmarks and software-engineering agents. • Experience with synthetic data generation, dataset curation, and automatic evaluation. • Research publications or meaningful contributions to open-source ML projects. • Experience leading a small applied research or ML research team. Research Areas Some of the problems we expect this team to work on include: • Model Routing Choosing the optimal model dynamically based on task difficulty, latency requirements, cost, privacy constraints, and hardware availability. • Local vs. Cloud Inference Determining which workloads can reliably move from cloud models to models running directly on developer endpoints. • Model Compression Understanding how far models can be quantized, distilled, or otherwise optimized before meaningful capability is lost. • Agentic Model Evaluation Building evaluation methods for agents that operate over codebases, shells, developer tools, and long-running workflows. • Inference Efficiency Improving throughput, latency, memory consumption, and token efficiency across different model architectures and runtimes. • Model Specialization Investigating whether smaller specialized models can outperform general-purpose frontier models for narrow engineering tasks. • Long-Context Behavior Understanding how models behave as context grows, what information gets lost, and how context can be compressed or structured more intelligently. • Hardware-Aware AI Matching models and inference strategies to available GPUs, CPUs, NPUs, Apple Silicon, and other endpoint hardware. • Cost vs. Intelligence Tradeoffs Quantifying when additional model capability actually produces better outcomes — and when it simply produces more expensive tokens. Our Tech Stack Python, Go, PyTorch, Hugging Face, vLLM, SGLang, llama.cpp, MLX, CUDA, Metal, AWS, Cloudflare, Snowflake, and a rapidly evolving ecosystem of frontier and open-weight models. Why PointFive • A rare research surface We operate where LLM research meets real enterprise infrastructure. The questions we work on have immediate implications for how thousands of engineers use AI every day. • Access to real workloads Instead of optimizing against abstract benchmarks, you'll be able to study how models perform across real software engineering and agentic workflows. • Research that ships This isn't a research lab disconnected from product. Successful ideas can move rapidly from experiment to production. • Models are becoming infrastructure Enterprises will increasingly operate fleets of models across cloud APIs, private infrastructure, and developer endpoints. Deciding how those models are selected, optimized, deployed, and governed is becoming a fundamental infrastructure problem. • Frontier moves fast New models, architectures, inference techniques, and agent systems appear constantly. Your job is to understand which developments matter — and turn them into an advantage for PointFive. • Founders with a track record Built and sold IntSights to Rapid7. Backed by top-tier investors with deep conviction in the category. • Early-stage leverage You'll define PointFive's LLM research strategy, research methodology, and eventually the team itself.

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. 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, Forbes Israel put us on its Next Billion Dollar Startups list, and Redpoint selected us for its InfraRed 100, its ranking of the private companies shaping the future of cloud infrastructure. About the role This is the connective tissue of our marketing. Product marketing, content, field, PR, partners, web and our outside agencies each own their piece. You make sure the pieces fit: that everyone knows what's coming, what they owe, and when, so we all move together. You won't write every word, run every event or own every relationship. You will see the dependencies nobody else sees, bring the right people together early, and keep everyone accountable to the dates, including very senior people. It takes real experience to do this well, and the judgment to know when to push and when to adjust. What you'll do • Keep one shared view of everything marketing has coming, months ahead, so every team plans against the same picture. • Think strategically about sequence. Decide what should come first, what builds on it and what lands last, so each launch, story, event and partner moment sets up the next one instead of competing with it. • Work backwards from the big moments on the calendar and map the interdependencies: what has to be true, by when, for each one to land. • Spot the connections early: which launch, story, event, partner and customer moment belong together. • Bring the right people into the room at the right time and make sure each knows what they own and when it's due. • Run the rhythm that keeps marketing, product, sales and partnerships in sync week to week. • Make sure the website and our other channels reflect what we're saying, working with the people who own them. • Give our agencies and outside partners clear direction so their work lands right the first time. • Notice when something is slipping before anyone else does, and fix it or flag it. The kind of situations you'll handle • A major conference is four months out. Work backwards so that the product news, the story behind it, the press, the partners and the customer voices are all ready at the right moment, and every owner knows it. • Three teams are planning three good ideas for the same month. Turn them into one moment instead of three competing ones. • A launch date moves. Figure out everything downstream that moves with it, and get everyone re-aligned before it becomes a problem. • A partner wants to do something together. Make sure it fits the bigger plan and doesn't collide with what's already coming. What we are looking for You probably haven't had this exact title. The people who do this well usually took a winding path through events, content, product marketing, community, sales, producing or founding something. What they share is that they make things happen. • You have real, hands-on marketing experience, ideally in B2B tech, across more than one discipline. • You have built something from scratch: a community, an event, a program, a side project, something nobody asked you to start. • You have kept many moving parts and many people on track at once, and you have the stories to prove it. • You think in plans, calendars and dependencies. Things don't fall through the cracks around you. • You have ideas and you see them through. Landing six moving parts in the right order is your idea of a good week. • You solve problems sideways when the budget, the time or a missing piece gets in the way. • You're hungry. Your scope keeps growing because you pick up what nobody owns. • You hold people accountable, kindly, including people more senior than you. • You write clearly in English and Hebrew and can brief anyone so they get it right the first time. What doesn't matter, and what's a bonus Doesn't matter: your current title, a specific number of years, a marketing degree, or whether you have held a role like this before. You don't need to code. Bonus points: • You have built things with AI tools (workflows, agents, automations) that made you or your team faster. • You have worked with cloud or AI infrastructure buyers, or alongside hyperscaler and partner teams. • You have run a launch, an event or a program end to end, from blank page to results. • You have worked at both an early-stage startup and a company that was scaling fast. You don't need to tick every box. Show us you can really own this. Your first 90 days • Days 1 to 30: You know every team, partner and vendor we work with. You have mapped what's planned, what's in flight and what's missing, and you've shipped at least one thing yourself. • Days 31 to 60: One shared view of what's coming is live, and every team plans against it. A weekly rhythm is running. The next major moment is mapped backwards, with every owner and date agreed. • Days 61 to 90: You've coordinated a connected moment from start to finish: launch, content, PR, partner and event pulling in the same direction. Other teams now come to you first. How we'll know it's working • Big moments land on time, with every piece pointing the same way. • Every team plans against the same picture of what's coming. • Agencies and partners deliver better work because the direction is clearer. • People across the company come to you first to find out what's happening and where they fit. What you might not love • A lot of your job is chasing people who are busy, some of them very senior. • Plans change often. You'll rework the picture more than once a quarter and still keep everyone aligned. • Much of your best work is invisible when it goes well. The moment lands, and it looks easy. 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 — DeepWaste detection and agentic remediation with clear, measurable ROI for both engineering and finance teams. • Early-stage leverage — Your work directly shapes the product, the culture, and the go-to-market playbook. • Your role has a view across the whole company — product, research, partners, sales and leadership all run through this seat. Direct access to founders and leadership, and room to act without layers of approval.