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We are seeking an Analytics Functionality Analyst to join our Analytics engineering group. In this role, you will serve as a crucial partner to the Product Manager, facilitating the translation of complex analytics into actionable steps for functional software delivery. This hybrid position combines robust analytical skills with a keen understanding of engineering processes, allowing the Product Manager to focus on the strategic “what” and “why,” while you ensure clarity on the operational “how.” What you’ll do: Feature Translation: Convert high-level analytical concepts and product features into clear, functionally defined user stories that capture algorithmic and statistical nuances for the engineering team. Collaboration with Engineering Teams: Work closely with developers and data scientists to assess feature feasibility, identify edge cases, and establish thorough testing and validation criteria within the engineering environment. Customer Engagement: Participate in technical discussions with customers, especially when deep modeling insights or analytics expertise are required, to gather feedback that informs engineering decisions. Documentation Authority: Own the documentation of analytics functionality, positioning yourself as the internal authority on modeling logic and assumptions, thereby ensuring consistency and clarity across engineering projects. Support Engineering Testing: Drive the testing and validation of implemented models and features, ensuring they function as expected from an analytics perspective and contributing to overall product quality.

Position Intro:
Earnix is the premier provider of mission-critical, cloud-based intelligent decisioning across pricing, rating, underwriting, and product personalization. These fully-integrated solutions provide ultra-fast ROI and are designed to transform how global insurers and banks are run by unlocking value across all facets of the business. Earnix has been innovating for insurers and banks since 2001 with customers in over 35 countries across six continents and offices in the Americas, Europe, Asia Pacific, and Israel.

Were looking for a Customer Success Manager to work closely with our top Enterprise clients. The ideal candidate will have a background in digital marketing, data and customer success, and enjoys working directly with clients to help solve business problems and provide data-driven outcomes. This role will also serve as a product expert to help drive customer adoption and retention, generating insights and creative ideas for solutions.
This role will report to the Team Manager, Client Services.
Why is this role so crucial ?
The Customer Success Manage Enterprise is a key player on the Enterprise Team collaborating with a variety of internal cross-functional teams and serving as a trusted advisor to our clients by working in a consultative manner. The CSM's ability to create relationships with the largest Enterprise clients , and help them extract real business value using our solutions is essential to keeping clients engaged for years.

we are transforming how organizations build, run, and scale AI and accelerated compute workflows with NeuralMesh, our intelligent, adaptive mesh storage system. Unlike traditional data infrastructures, which become more fragile as compute environments grow and performance demands increase, NeuralMesh becomes faster, stronger, and more efficient as it scales - providing a flexible, adaptable foundation for enterprise and agentic AI innovation that maximizes GPU utilization, accelerates time to first token, and lowers the cost of innovation.
we are a growth-stage company backed by world-class venture capital investors and AI infrastructure industry leaders. Our technology, purpose-built for AI, has garnered over 140 patents and is trusted by more than 30% of Fortune 50 enterprises, as well as the worlds leading hyperscalers, neoclouds, and AI innovators. Our team is customer-obsessed and works accountably, boldly, and collaboratively to ensure customer success. If we sound like your kind of people, join us!
About the role
At our company, 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 company 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.

we are transforming how organizations build, run, and scale AI and accelerated compute workflows with NeuralMesh, our intelligent, adaptive mesh storage system. Unlike traditional data infrastructures, which become more fragile as compute environments grow and performance demands increase, NeuralMesh becomes faster, stronger, and more efficient as it scales, providing a flexible, adaptable foundation for enterprise and agentic AI innovation that maximizes GPU utilization, accelerates time to first token, and lowers the cost of innovation.
we are a growth-stage company backed by world-class venture capital investors and AI infrastructure industry leaders. Our technology, purpose-built for AI, has garnered over 140 patents and is trusted by more than 30% of Fortune 50 enterprises, as well as the worlds leading hyperscalers, neoclouds, and AI innovators. Our team is customer-obsessed and works accountably, boldly, and collaboratively to ensure their success. If we sound like your kind of people, join us!
About the role:
Our Automation Engineers are part of a team of highly skilled Python programmers that are responsible for creating test coverage for all system functionalities and configurations. This is a challenging but crucial engineering task since the testing of a feature in storage can be more complex than its actual implementation. Together with the team, you will be responsible for the products reliability and stability, which is a core requirement of any enterprise storage product and is vital to its success.
As a QA Automation Engineer, youll:
Create detailed, well-structured test plans and test cases;
Implement automated distributed tests in Python;
Gain an in-depth understanding of a complex, clustered system and be able to accurately analyze failures in those systems;
Collaborate with the R&D team in order to identify and analyze problems, as well as verify and test solutions; and
Become a storage expert who understands the terminology, protocols, configurations, architecture, and practicalities in the frontier of storage technology.

We're seeking a hands-on Compensation & Benefits Manager to join our team! This will report to the Team Manager, Compensation & Benefits.
Why is this role so important?
The Compensation & Benefits Manager leads the design and execution of core compensation programs across the employee lifecycle, with a strong focus on annual merit, bonus, and equity cycles. The role owns end-to-end compensation processes, maintains salary structures and benchmarking practices, and partners closely with HR and business leaders to support consistent, data-driven compensation decisions.
Operating in a dynamic, global environment, the role provides trusted guidance on complex and sensitive compensation matters and balances hands-on execution with thoughtful design to ensure alignment with market practice and business needs.

We seek a motivated and experienced Affiliate Manager (B2C) to join our B2C marketing team. The ideal candidate will be responsible for developing and managing our affiliate marketing programs for our various B2C products, building strong relationships with partners, and driving growth through strategic initiatives. This role requires a proactive individual with a deep understanding of affiliate marketing strategies and a proven track record of delivering results
So, what will you be doing all day?
Develop and Manage Affiliate Programs: Create, implement, and oversee affiliate marketing strategies to increase traffic, leads, and revenue.
Recruit and Onboard Affiliates: Identify, approach, and onboard new affiliate partners that align with our various brands and business objectives.
Performance Analysis: Monitor and analyze affiliate performance metrics, generating reports and insights to inform strategic decisions and improve ROI.
Optimize Campaigns: Continuously assess and optimize affiliate campaigns for maximum effectiveness and profitability.
Collaborate with Internal Teams: Work closely with the marketing, management, and product teams to align affiliate strategies with overall company goals.
Stay Updated on Industry Trends: Keep abreast of the latest trends and best practices in affiliate marketing and incorporate relevant strategies into campaigns

we are transforming how organizations build, run, and scale AI and accelerated compute workflows with NeuralMesh, our intelligent, adaptive mesh storage system. Unlike traditional data infrastructures, which become more fragile as compute environments grow and performance demands increase, NeuralMesh becomes faster, stronger, and more efficient as it scales, providing a flexible, adaptable foundation for enterprise and agentic AI innovation that maximizes GPU utilization, accelerates time to first token, and lowers the cost of innovation.
we are a growth-stage company backed by world-class venture capital investors and AI infrastructure industry leaders. Our technology, purpose-built for AI, has garnered over 140 patents and is trusted by more than 30% of Fortune 50 enterprises, as well as the worlds leading hyperscalers, neoclouds, and AI innovators. Our team is customer-obsessed and works accountably, boldly, and collaboratively to ensure their success. If we sound like your kind of people, join us!
About The Position
At our company, we dont just "test" software; we push the boundaries of high-performance distributed systems. We are looking for a Group Lead for System Quality Engineering-someone who views quality as a complex engineering challenge, not a checkbox.
You will lead a group of 20 world-class SW engineers and Team Leads. Your mission is to build the "adversarial" engineering force that ensures our platform remains resilient, performant, and unbreakable under the worlds most demanding data workloads. We want a leader who treats testing as a performance art and a systems science, likely coming from a background in Backend Engineering, SRE, or highly technical System Verification.
Key Responsibilities:
Architect the "Breaking" Strategy: Design the end-to-end strategy for validating a massive-scale distributed file system. This isn't just about coverage; it's about finding the architectural breaking points.
Lead a High-Caliber Engineering Group: Manage and mentor a team of "Quality Hackers." You will set the technical bar, promote a culture of engineering excellence, and move away from traditional "manual-first" mindsets.
Deep-Tech Collaboration: Work as a peer to the Product and Core Development leads. Youll influence the product roadmap by identifying systemic risks early in the design phase.
Evolve the Automation Ecosystem: Partner with Infrastructure teams to build sophisticated, automated test environments that simulate chaotic, real-world customer environments at scale.
Field-to-Core Feedback Loop: Bridge the gap between how our product is used in the field and how we stress-test it in the lab, ensuring our company excels in the most extreme AI and HPC use cases.
Data-Driven Reliability: Define and track high-signal metrics (System Recovery Time, Latency P99s under stress, Mean Time to Detection) to provide a transparent view of product health.