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We are seeking a highly skilled and detail-oriented Controller to join our finance team. This role is responsible for overseeing financial reporting, tax compliance, and day-to-day financial operations across the group. The Controller will manage consolidated financial statements, ensure accuracy and consistency across subsidiaries, and work closely with senior management, auditors, banks, and external partners.

The ideal candidate is a CPA with experience in a commercial company following their CPA internship, preferably in a high-tech or SaaS environment. Hands-on experience in accounting/bookkeeping is a significant advantage

Key Responsibilities:
Prepare annual consolidated financial statements and tax reports.
Oversee and monitor the financial activities of subsidiary companies.
Supervise bookkeepers and review core financial operations, including billing, collections, journal entries, and payroll.
Manage and maintain strong relationships with auditors, banks, financial institutions, clients, and vendors.
Act as a key partner in the budgeting process, including annual budget preparation and monthly variance analysis (actual vs. budget).
Develop financial forecasts and deliver in-depth financial analyses to support management decision-making.

Build the dashboard security teams live in all day. You'll own the experience where customers actually do the work: dense inventory tables, identity and software graphs, and the policy builders that turn discovery into enforcement. This is data-heavy, detail-heavy product surface where performance and clarity matter as much as polish.

What you'll work on

Inventory and findings screens over large datasets - fast, filterable, URL-addressable table state.

Identity and relationship views that make a messy org legible.

Policy and rule builders: complex, stateful UI that has to stay understandable.

Our internal design system and its Storybook - the shared vocabulary every screen is built from.

The design-to-code pipeline: design tokens synced from Figma and enforced in CI.

Our Networking System Product Engineering organization is looking for a Senior Data & AI Solutions Engineer - high-agency, self-directed Data & AI Solutions Engineer to partner with engineering teams and transform data, BI, automation and agentic AI into measurable engineering productivity gains.

What youll be doing:
Work closely with engineers, managers, and cross-functional teams to understand complex engineering domains, identify bottlenecks, and build practical solutions that improve decision-making, execution speed, and operational quality.
Develop and deliver production-grade tools, automated workflows, and agentic AI solutions from concept through deployment.
Run fast, high-quality proof-of-concepts on emerging AI and agentic technologies, and productize successful ones.
Implement data flywheels that continuously improve quality through telemetry, benchmarking, automated evaluation, and structured feedback loops.
Collaborate and contribute ideas and code to Product Engineering's evolving data infrastructure.
Improve data quality, integrity, governance, metric definitions, and usability across engineering domains.
Train and enable engineers, managers, and stakeholders to use data, BI, and AI tools effectively.

We are looking for a Distinguished Engineer to help shape the future of AI infrastructure. As part of our advanced development and research efforts, you will drive technical vision and innovation across the AI software stack, spanning GPU computing, RDMA, NVLink, storage, and large-scale distributed systems. You will research next-generation system designs, influence product and platform direction, and help define how massive-scale AI environments are built, optimized, and operated through hardware-software co-design.

What youll be doing:

Research, define, and drive co-design solutions across AI software stacks involving GPU computing, RDMA networking, NVLink interconnects, storage, and large-scale distributed infrastructure.

Lead deep technical investigations and proof-of-concept development in areas related to distributed AI, deep learning systems, high-performance computing, virtualization, memory management, and large-scale systems design.

Work closely with multiple teams across us to advance next-generation AI infrastructure technologies and influence cross-stack co-design decisions.

Analyze end-to-end system bottlenecks and opportunities across compute, networking, memory, and storage layers to improve performance, scalability, and efficiency.

Guide the design of environments that support massive-scale AI training and inference workloads in production.

We are seeking a highly motivated High-Performance System Architect to join our team of experts and help shape the future of high-performance and ML / AI computing. Our next-generation NVL systems will be at the forefront of connecting and powering the world's most advanced compute clusters, which would be used to train the most advanced AI models such as GPT and DeepSeek. As a high-performance system architect, you will have the opportunity to work on some of the most cutting-edge technology and help to drive the innovation of our next generation networks that will be used by top researchers and engineers around the world.

What youll be doing:

Define the NVL system architecture end-to-end, by internal requirements and customers requirements through all product life cycles (post/pre silicon, on deployments).

Research various of solutions to enable the next large-scale-high-performance computing clusters. The position spans over various layers from algorithms, software, firmware, and HW.

Collaborate with cross-functional teams, including other architecture teams, logic design, system software, firmware, and research teams, to ensure the successful execution of the project.

We are seeking an AI Networking Architect to join the Networking Research Group. This role will help bridge the gap between emerging tasks supported by advanced technologies and the data center infrastructure that powers them. In this role, you will work at the intersection of AI applications, distributed systems, networking hardware, and software architecture.

You will join a focused team of multidisciplinary engineers driving AI workload optimization through deep application understanding, network analysis, and end-to-end systems thinking. Your insights will directly shape our products across the full stack - from applications and software libraries to hardware architecture and physical design.

What Youll Be Doing:

Model the performance of complex AI workloads to identify bottlenecks and recommend system-level optimizations.

Analyze brand-new AI models, distributed training techniques, and inference workloads to understand their infrastructure requirements.

Build Platforms, simulations and HW platforms, execute AI workloads and build analytical tools to evaluate trade-offs across compute, memory, storage, and network behavior.

Translate research insights and workload behavior into actionable software, hardware, and networking architecture requirements.

Partner with architecture, software, and product teams to influence our future networking and AI infrastructure roadmaps.

Drive architectural innovation by applying deep workload analysis to real-world advanced machine learning frameworks.

The System product engineer is responsible for stabilizing hardware products from the first build unit through ramp-up and transition to high-volume mass production. This role plays a critical part in ensuring product quality, yield, and test robustness for our cutting-edge platforms by leading debug infrastructure development, systematic failure analysis, and data-driven continuous improvement across the NPI lifecycle.

What you'll be doing:

Own end-to-end product stabilization from first article to production release.

Develop and maintain hardware debug infrastructures, tools, and methodologies to support efficient root cause analysis.

Monitor, analyze, and improve yield performance during NPI.

Perform deep-dive failure analysis and root cause investigations to improve product robustness, quality, and throughput.

Improve test stability, coverage, and repeatability while reducing false failures.

Collaborate closely with Mechanical NPI engineers, Test Development teams, R&D, and manufacturing partners.

Apply data analysis techniques to identify systemic issues, trends, and optimization opportunities.

Our team is looking for a Senior DevOps Engineer to join us and take ownership of the CI/CD infrastructure, automation pipelines, and development tooling that power our engineering teams. This position plays a key role in enabling fast, reliable, and scalable software delivery - from code commit to test execution and reporting. You will be the go-to expert for DevOps practices, collaborating closely with software engineers, validation teams, and infrastructure stakeholders across the organization.

What You'll Be Doing:

Design, implement, and maintain CI/CD pipelines for software and validation projects, ensuring fast, stable, and automated delivery workflows.

Own and evolve the DevOps infrastructure - including build systems, artifact management, deployment automation, and environment provisioning.

Develop and maintain automation tools, scripts, and integrations that streamline developer workflows and reduce manual overhead.

Collaborate with validation, infrastructure, and software engineering teams to define and enforce DevOps best practices across the organization.

Monitor system health, pipeline reliability, and build performance; identify bottlenecks and continuously improve observability and stability.

Manage containerization and orchestration solutions (Docker, Kubernetes) for test environments and internal services.

Support the integration of automated testing frameworks into CI/CD flows, ensuring test coverage and results are tracked and visible.

Evaluate and introduce new DevOps tooling and methodologies to keep the team at the forefront of engineering efficiency.

We are seeking a Director of Software Architecture to lead and accelerate the evolution of next-generation AI data center and networking technologies. This role is designed for a hands-on, execution-driven leader who pushes boundaries, translates vision into reality, and delivers high-impact solutions at scale. You will operate at the intersection of innovation, architecture, and delivery-shaping the future of AI networking and infrastructure.

What you will be doing:
Drive identification, evaluation, and rapid adoption of emerging technologies, ensuring strong alignment with strategic roadmap and measurable business outcomes.
Lead the design and delivery of advanced networking applications, leveraging data plane programming and modern networking protocols to solve complex, large-scale challenges.
Architect solutions across AI data center environments, integrating GPU-based systems, hardware acceleration, and high-performance networking.
Act as a thought leader and industry influencer-engaging directly with customers, publishing technical content, and representing us at key conferences and forums.
Define and execute a bold architectural vision for our networking in close collaboration with cross-functional software and hardware leaders.

We are looking for a high-ownership Product Manager to take full end-to-end responsibility for a core domain within Oak's platform. Reporting to a Director of Product, you will bridge the gap between customer discovery and technical R&D execution to ship market-ready, AI-native identity solutions at speed.

What you will Do:

Own a product domain end-to-end within platform, driving it from zero to a shipped, market-ready capability.

Lead structured discovery: conduct customer interviews, engage with industry analysts and IAM/IGA consultants, and synthesize findings into sharp problem definitions and opportunity sizing.

Map the competitive landscape across identity governance, NHI management, and adjacent security tooling to identify differentiated positioning for your domain.

Translate discovery into a clear product strategy and roadmap, making deliberate prioritization decisions backed by evidence from the market and identity graph data.

Partner closely with R&D throughout the full build cycle - from shaping requirements and reviewing designs to driving execution and managing trade-offs under real delivery constraints.

Work hand-in-hand with GTM teams to define go-to-market strategy, equip sales and marketing with the right positioning, and ensure a tight feedback loop from the field back into the roadmap.

We're hiring for leverage, not years. If you can wield agentic coding tools better than most senior engineers - and you've shipped real, working software with them - we want to talk, regardless of how long you've been doing this or where you learned it. This role is designed for someone earlier in their career who, armed with the right tools and the judgment to use them, delivers like someone far more senior.

You'll work across the whole stack: a single feature might run from a Drizzle schema change, through a Hono endpoint, to a new React screen. The agentic toolchain is how you cover that ground - but the judgment to review, verify, and take responsibility for what the tools produce is what makes it work.

What you'll work on

Full, thin vertical slices - backend to frontend - shipped behind previews and a merge queue.

Extending and hardening our agentic-dev toolchain: skills, workflows, and MCP servers the whole team relies on.

Whatever's highest-leverage that week - you'll move across the codebase more than most.

Own the intelligence layer - the AI research pipeline that classifies and risk-scores every tool we find. Discovery tells us what software an organization runs; the AI does the hard part: figuring out what each tool actually is, what it can do, how it handles data, and how risky it is. You'll own that research and enrichment system end to end - the LLM-backed agents, the prompts and context that drive them, the evals that keep them honest, and the cost and latency of running them at scale.

This is an engineering role, not a research one. You'll ship production TypeScript, and you'll be measured on the accuracy, cost, and reliability of the intelligence the product depends on.

What you'll work on

The multi-agent researcher system: LLM-backed agents that research each tool across topics like platform, data policy, AI models, and agentic capabilities, and return structured, evidence-backed classifications.

Evals and quality: design eval sets, measure classification accuracy and hallucination, and turn prompt changes into regression-tested, reviewable diffs instead of guesswork.

Grounding and trust: cite evidence, resolve contradictions between AI output and validated data, and drive down hallucination on the fields that matter.

Model routing and cost/latency: choose and route across providers, tune concurrency and caching, and keep the pipeline fast and affordable as volume grows.

Structured outputs, tool/function calling, and the schemas and validation that make model output safe to persist.

Deep observability into the pipeline - spans, traces, and metrics for every model call.

The same systems work as our senior role, aimed at someone earlier in their career who gets real work done in a hard codebase with agentic tools. Systems programming has a reputation for being locked behind ten years of experience. We don't fully buy that. Someone with solid fundamentals, real curiosity about how machines work, and deep control of agentic coding tools can contribute here much sooner - as long as they have the judgment to check what the tools hand back. That judgment matters more here than almost anywhere: the agent runs as root and SYSTEM, and the codebase forbids unwrap, panic, and unchecked indexing, so you can't ship code you don't actually understand.

What you'll work on

Real pieces of the sensor across macOS and Windows: inventory, telemetry, the policy enforcement path, installers, and the integrations that hook into AI coding tools and browser extensions.

Moving through unfamiliar OS APIs quickly with agentic tools, then checking the result against the docs, the tests, and a real machine.

Small tools and tests that make the codebase easier for everyone to work in.

Tech you'll work with

The work is low-level systems development in Rust, close to the operating system across Windows, macOS, and Linux - memory, processes, files, and the OS internals that expose them. Alongside that, you'll lean hard on agentic coding tools; deep fluency with at least one is central to how we work, not a bonus. Expect to range across the stack - OS internals, AI tooling internals, CI, and a fair amount of reverse engineering - and to learn the parts you don't know yet.

We are looking for a skilled Software Developer with strong hardware knowledge to join our team developing production test solutions for optical transceivers and networking products. Our team builds the software and test infrastructure used on production lines to validate our optical and interconnect products. The work combines instrument automation, low-level software development, and direct control of custom hardware. You will work with optical instruments such as power meters, variable optical attenuators, and laser sources, as well as custom test boards used to control and communicate with the device under test (DUT).

This is a hands-on, technically deep role that spans the entire development lifecycle-from hardware bring-up and debugging to validation, deployment, and production support. As a technical focal point, you will work at the intersection of hardware and software, collaborating with electrical, hardware, thermal, mechanical, and software engineers to deliver robust and scalable test solutions across multiple production lines and products.

What Youll Be Doing:

Design and develop production test systems for optical transceivers, networking hardware, and interconnect products.

Develop software that controls optical test instruments, custom test boards, and other hardware components.

Write low-level drivers and hardware-control software in C and C++, and integrate native code with higher-level C# applications through DLL wrappers.

Read and interpret electrical schematics, block diagrams, datasheets, timing requirements, and hardware specifications.

Lead hardware bring-up, validation, and deployment of test solutions in production environments.

Debug complex hardware-software integration issues using oscilloscopes, logic analyzers, software tools, and hardware communication interfaces such as I2C, SPI, and UART.

Investigate failures, identify root causes, and implement reliable corrective solutions.

Collaborate with cross-functional teams to translate hardware requirements into software interfaces and automated test procedures.

Take technical ownership of projects from initial concept and prototype development through production release and ongoing support.

Improve test coverage, system reliability, maintainability, and scalability across multiple products and production lines.

A sensor runs on every customer machine, takes inventory of the software and AI tools in use, sends that back over an encrypted channel, and enforces policy locally. It runs as a service on Windows and a daemon on macOS, with the access and the responsibility that come with running as SYSTEM and root. This role owns the hard parts of it.

What you'll work on

The sensor itself: software inventory, secure telemetry, and on-device policy enforcement, on both Windows and macOS.

Real OS work. On macOS that means Launch Services, Spotlight, IOKit, the Security framework, and Open Directory. On Windows it means services, ETW, WMI, the registry, and WinSock.

The policy enforcement point: evaluating rules over events (including AI-tool use and browser extensions) against a policy engine, and talking to the backend that makes the decisions.

Encrypted logging and telemetry, crash handling and symbolication, and the recovery path that keeps the agent running and hard to tamper with.

Signed installers and macOS configuration profiles.

Tech you'll work with

The work is low-level systems development in Rust, close to the operating system across Windows, macOS, and Linux - memory, processes, files, and the OS internals that expose them. Alongside that, you'll lean hard on agentic coding tools; deep fluency with at least one is central to how we work, not a bonus. Expect to range across the stack - OS internals, AI tooling internals, CI, and a fair amount of reverse engineering - and to learn the parts you don't know yet.