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Required Product Manager - Storage Networking Platform
The Role
This is a rare opportunity to:
Have a direct impact on AI performance and GPU efficiency at scale
Combine deep technical thinking with product ownership
Own product decisions that influence real-world system behavior
As a Product Manager, you will define how next-generation AI workloads interact with high-performance storage and networking systems.
This is a deep-tech product role at the core of our platform, where your decisions directly impact performance, scalability, and efficiency across large-scale AI environments.
Youll operate at the intersection of product, distributed systems, and hardware-aware infrastructure - shaping how modern data platforms are built and optimized.
What You'll Do:
Define and execute product strategy for our platform and infrastructure layer
Own the product roadmap - balancing innovation, performance, and customer needs
Work closely with engineering to design and deliver high-performance capabilities
Translate complex technical challenges into clear product decisions and priorities
Partner with customers and internal teams to understand real-world use cases and constraints
Stay ahead of trends in storage, networking, and distributed systems
Collaborate with top engineers, architects, and customers solving cutting-edge challenges.

As Global Privacy & Compliance Counsel, you will serve as the in-house owner and go-to expert for all privacy and compliance matters.

This is a highly cross-functional role, working as part of the Legal & Compliance team, closely with Sales, Product, R&D, CS & Security teams.

The role is designed for someone who can operate independently, proactively identify gaps, extract and organize knowledge across teams, and translate complex privacy/data, compliance and regulatory requirements into practical solutions that support business execution and accelerate deals.

The position requires an in-house and business-oriented mindset, strong ownership, and the ability to lead initiatives end to end.

This role offers a unique opportunity to shape and lead privacy and compliance frameworks in a fast-growing global organization, with real impact on business outcomes, customer trust, and long-term scalability.

Key Responsibilities:
Own and manage the companys global privacy and compliance framework, including policies, templates, processes, and ongoing updates
Serve as an expert on all privacy/date compliance requirements, and regulatory framework
Review, draft, and negotiate privacy-related agreements with customers and vendors
Work closely with Product, R&D, Data, R&D, CS & Security teams to understand data flows and systems
Provide day-to-day privacy and regulatory compliance support to Sales and customer-facing teams
Enable faster deal execution by offering pragmatic, risk-aware solutions
Support negotiations with customers and partners on privacy and data protection topics
Drive the organization toward increased compliance maturity and long-term readiness
Build scalable processes that support growth while maintaining strong compliance standards

Required Software Engineer - Verification and Reliability
The Mission
We are building NeuralMesh- the worlds first intelligent, adaptive mesh storage system. To ensure our platform is unbreakable for the worlds largest AI and GPU clusters, we don't just "test" our code. We build an adversarial distributed system as complex and sophisticated as the product itself.
We are moving away from traditional QA automation. We are building a high-octane engineering force that treats reliability as a high-end software problem. We need "Quality Hackers" who want to build the technology that proves bugs don't exist.
In this role as a Software Engineer in Test (SET), you are a developer first. You will join a high-impact team of engineers who write production-grade code to build a massive-scale validation ecosystem. Your job is to act as "The Breaker"-designing the infrastructure, chaos experiments, and AI-driven tools that push our platform to its theoretical limits.
What Youll Build:
Adversarial Engineering: Design and implement Python-based distributed frameworks capable of orchestrating millions of concurrent IO operations to hunt down race conditions and memory leaks.
AI-Augmented Validation: Be at the forefront of the AI-Native transformation. You will leverage LLMs and Generative AI to automate complex scenario generation, build intelligent agents for root-cause analysis, and multiply your engineering velocity.
Simulation & Chaos: Build the "Entropy Engine." You will develop tools that inject real-world failures - latency, packet loss, and hardware crashes - to prove the resilience of our Raft and RDMA implementations.
Deep-System Observability: Move beyond "Pass/Fail." You will build telemetry pipelines to track P99 latency and jitter, providing critical architectural feedback to the Core Kernel teams.
Collaborative Architecture: You will operate with the same rigorous standards as the Core R&D team: design docs, production-grade code reviews, and high-level architectural planning.

We are looking for a hands-on, business-minded AI Engineer to join our Data & AI Team.
This role is for someone who has already built and shipped real AI products in a company environment. You will work as an integral part of the Data & AI Team, partnering directly with business stakeholders to identify high-impact opportunities, translate business needs into technical solutions, and build AI products that automate internal processes and create immediate value.
The ideal candidate is a builder. You should be comfortable working with LLMs, AI agents, automation workflows, APIs, data pipelines, data warehouses, and internal company systems. You should also be comfortable taking ownership, asking sharp business questions, and moving ideas from concept to production.
Our Data Team has already built internal AI products at our company. Now we are looking for someone who can help take us to the next level.
What Were Looking For
The right person has built with AI in a real company environment and knows how to turn business needs into practical internal products. They should be comfortable working with stakeholders, understanding how teams operate, and identifying where AI can create meaningful value.
Because this role sits inside the Data & AI Team, they also need to be strong with data. That means working confidently with company data, data warehouses, pipelines, APIs, and the technical building blocks that make AI products reliable and useful.
This role is for someone hands-on, curious, and hungry to build. Someone who can combine AI, data, and business context to help us move faster, automate smarter, and turn ideas into measurable business wins.
What Youll Do
Build end-to-end internal AI products, automations, agents, and workflows that solve real business problems across our company.
Work directly with business stakeholders to understand pain points, define requirements, and turn ideas into scalable AI-driven solutions.
Design, prototype, test, deploy, and maintain production AI products using LLMs, AI agents, APIs, automation frameworks, and internal company data.
Work hands-on with data tools and infrastructure, including Snowflake, ETLs, data pipelines, APIs, AI tools, and internal servers.
Identify high-impact manual processes and turn them into automated AI-driven business wins.
Evaluate new AI tools, frameworks, and agentic workflows, and apply them where they can improve productivity, decision-making, or business operations.
Help shape internal AI development best practices around reliability, usability, security, documentation, maintainability, and production readiness.

Required Senior Software Engineer, Filesystem
What you'll be doing:
The filesystem group is a high-powered team responsible for implementing algorithms at scales of 100s of PBs. The team also manages the core filesystem components, including blocks and metadata management, snapshots, RAID logic, object-store tiering, unique cloud disaster recovery features, and more. And most importantly, they skillfully handle the most delicate part of the solution - our customers data.
As a Senior Software Engineer, youll:
Design and develop distributed file system components to support data management features such as snapshots, replication, tiering, and advanced data reduction algorithms;
Participate in the design, architecture, and implementation of next-generation storage architecture;
Assist in technically managing initial storage implementations including proofs-of-concept;
Diagnose bottlenecks and implement clean and performant solutions to achieve unbeatable performance;
Design algorithms and data structures to make sure customer data is safe and coherent across our solution in a wide variety of failure modes; and
Constantly revisit the architecture, algorithms, and methodologies to improve productivity, reliability, and maintainability.

Required Senior Software Engineer, Control
As a Senior Software Engineer, youll:
You will be responsible for building the "brain" of our main product, which is a distributed file system -the layer that manages orchestration, metadata, cluster membership, and implements complex logic required to manage hundreds of thousands of nodes, for cluster scaling, automated failover, zero-downtime rolling upgrades and "self-healing" to detect and remediate hardware failures or network partitions.
Design, implement, unit test, and maintain services that coordinate and the cluster
Optimize Performance: Work with complex data structures like spanning trees or LSM-Trees, concurrency control mechanisms (MVCC) to improve speed and efficiency.
Collaborate closely with cross-functional teams to translate backend capabilities into real-world impact.

We are seeking a Senior Engineer for our Labs (on premise) Team member, working with a team of engineers, who manage our physical labs. You'll support the infrastructure for our servers, both HW and SW wise. This role offers an exciting opportunity to take a significant part of ensuring optimal testing environments for our enterprise-grade storage solutions.
Requirements:
- Hands-on work in a data center environment: racking, cabling, replacing hardware components, and troubleshooting server failures
- Design and implement infrastructure to allocate, configure and troubleshoot servers
- Daily operational support for servers, switches, and lab infrastructure
- Building and maintaining Linux images for servers and lab environments
- Working with a mix of modern and legacy systems in a lab environment
- Supporting VMware-based infrastructure and virtualization environments
- Work with multiple teams on gathering requirements and coordinating changes
- Define and implement infrastructure monitoring strategies using modern observability tools
- Drive infrastructure modernization initiatives and best practices adoption
- Establish and maintain documentation for lab processes, infrastructure, and operational procedures
- Perform capacity planning and resource allocation for lab environments
- Working closely with procurement, vendors, and external technicians
- Participating in on-call rotation (small team, occasional incidents)
Occasional travel to the US (1-2 times a year).

Required Performance Engineer
About the role;
Were building a next-generation platform for validating large-scale distributed systems. Our goal is to continuously ensure the correctness, performance, and resilience of the Data Platform across every layer of the stack.
As a Senior Software Engineer, youll work hands-on on the systems and frameworks that test, stress, and validate complex distributed infrastructure under real-world conditions. Youll help design and build automated environments that simulate scale, concurrency, and failure scenarios, and youll contribute to evolving how we ensure reliability and correctness in modern infrastructure systems.
This role is ideal for engineers with a strong distributed systems background who enjoy deep technical problem-solving, working close to the system, and building tools that improve quality, stability, and confidence at scale.
What Youll Do:
Design and implement core components of a distributed testing infrastructure and quality platform.
Build automated frameworks to validate functionality, performance, and resilience at scale.
Collaborate closely with infrastructure, storage, and platform teams to ensure quality is built into the development lifecycle.
Contribute to improving tooling, test coverage, and engineering best practices across the organization.