Jobs at WEKA

The Senior Sales Engineer will partner with customers to solve data challenges, educate them on WEKA's solutions, and provide technical support.

The Regional Sales Manager will manage enterprise-level accounts, develop sales strategies, and collaborate with partners to drive customer adoption and sales, focusing on WEKA's adaptive storage technology.

Own full-cycle recruiting for multiple technical roles, from intake through offer close. Build proactive talent pipelines, partner with hiring managers on target profiles, advise on market trends and compensation, and deliver strong candidate experiences. Maintain accurate ATS data and use recruiting analytics to identify bottlenecks. The role requires recruiting expertise in software companies, particularly for difficult-to-fill technical positions, with autonomy in a fast-growing environment.

Provides senior technical support for enterprise infrastructure customers, troubleshooting hardware, networking, distributed storage, cloud, and performance issues. Acts as the primary liaison between customers, account teams, partners, and Engineering; manages support cases, monitors systems, documents solutions, and communicates product feedback. Requires Linux and networking expertise, Python and Bash automation, on-call availability, and occasional regional or international travel.

Lead global revenue operations across Sales, Marketing, Customer Success, Finance, and channel teams. Own forecasting, territory planning, pipeline management, compensation, quote-to-cash processes, GTM systems, data governance, dashboards, and KPI visibility. Partner with executives and the board while supporting complex third-party hardware configuration and quoting. Build and manage a high-performing global operations team and optimize scalable go-to-market execution.

Owns end-to-end delivery of complex customer infrastructure builds lasting 90–120 days. Coordinates customers, OEMs, infrastructure partners, integrators, and internal teams; manages schedules, scope, risks, dependencies, budgets, change control, phased acceptance, and operational handoffs. Leads executive communications, resolves blockers, improves professional services methodologies, mentors engagement managers, and supports customer growth opportunities.

Operate and optimize WEKA data platform deployments for AI hyperscaler customers. Responsibilities include monitoring, upgrades, capacity management, tenant onboarding, storage and networking configuration, Kubernetes and GPU infrastructure support, performance benchmarking, incident escalation, runbook development, and automation using Python, Bash, and Ansible. The role requires strong Linux, storage, networking, cloud, and customer-facing infrastructure administration experience.

Owns end-to-end post-sales technical support for federal and special-program customers in secure, classified, and air-gapped environments. Diagnoses issues across Linux, compute, GPUs, networking, storage, cloud, and applications; collects and sanitizes diagnostics; manages escalations; maintains hardened deployments; supports hardware replacement; writes knowledge-base content; and provides customer and pre-sales support. The role includes on-call rotations, secure-facility work, and regional and domestic travel.

Own complex customer escalations across applications, GPUs, compute, networking, storage, cloud, and the WEKA Data Platform. Diagnose root causes, develop permanent fixes, provide engineering-ready defect reports, author technical advisories and knowledge-base content, improve tooling and support processes, mentor engineers, deliver training, and participate in 24/7 on-call coverage. Serve as the subject matter expert for NVIDIA Cloud Partner and DGX Cloud environments, collaborating with NVIDIA and customer engineering teams.

Own WEKA’s editorial programming across its website, YouTube, LinkedIn, newsletters, podcast, and online communities. Build and manage the editorial calendar, develop technical thought leadership, direct contract writers, repurpose content across formats, improve production workflows with AI, and use performance analytics to optimize audience growth, engagement, search visibility, and LLM citations. Collaborate with social, web, SEO, creative, communications, and customer advocacy teams while maintaining high editorial and brand standards.

Own product marketing for WEKA’s AI inference business, defining positioning, messaging, use cases, competitive differentiation, and economic value. Partner with Product, Engineering, Sales, customers, and cloud providers to validate market opportunities, recruit design partners, create proof and content, launch capabilities, and build repeatable sales enablement. The role requires deep understanding of AI infrastructure and inference economics, strong storytelling, and hands-on execution in an evolving early-stage market.

Own WEKA’s OEM alliance portfolio across North America, managing strategic relationships with partners including Dell, AMD, HPE, Cisco, Hitachi, Lenovo, and Supermicro. Develop joint go-to-market strategies, enable partner sales teams, build executive alignment, generate pipeline, support co-selling, and represent WEKA at industry events. The role focuses on positioning WEKA’s AI infrastructure and storage platform across partner ecosystems while creating integrated customer opportunities.

The Senior Product Manager will define and manage the roadmap for WEKA appliances, liaise with ecosystem partners, and ensure product delivery while maintaining market insights and collaboration with sales and engineering teams.

Own the AMG product roadmap for NeuralMesh: define KV-cache/prefix-cache offload, memory tiering, and integrations with inference engines and orchestration. Translate GPU/memory/network tradeoffs into product requirements, validate benchmarks with enterprise customers and GPU-cloud partners, partner with NVIDIA for certifications, and support sales with technical positioning to reduce cost-per-token and improve inference SLAs at scale.

Lead and own end-to-end LLM inference infrastructure, direct a small engineering squad, design and deliver high-throughput low-latency serving systems, remain hands-on (Python/C++/CUDA), solve inference-scale problems (KV caching, RDMA, NVMe, multi-tier GPU memory), and mentor engineers.

Lead alliance strategy across enterprise AI infrastructure, manage partnerships, define solution architectures, and drive GTM enablement while representing the company in industry events.