Consulting Pre-Sales Systems Engineer, Strategics - NYC
Everpure · New York, New York; Newark, New Jersey
- Junior
- Full-time
- $171,500 – $257,600
- Posted 2026-10-28
- Confirmed live on 29 October 2026
Job description
Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem.
This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us.
THE ROLE:
Everpure is hiring a Consulting Pre-Sales Systems Engineer to be the senior technical lead on a portfolio of the world’s largest and most strategic financial institutions: global banks, asset managers and payment networks. The CSE owns the technical strategy for each account, earns the trust of architects, platform owners and technology executives, and orchestrates product specialists, professional services and partners to win multi-year, multi-million dollar platform decisions. This seat sits at the center of the decisions the largest financial institutions are making right now: how to build AI infrastructure on data they cannot move, how to modernize data platforms without adding operational risk, and how to meet rising resilience and regulatory expectations at lower cost. The CSE shapes those decisions directly, works with senior account teams, and has visibility with Everpure leadership across sales, product and engineering.
The right person is as comfortable whiteboarding data architecture with a bank’s chief architect as they are leading a competitive bake-off or answering a 200-line RFI with precision.
WHAT YOU'LL DO
• Build and maintain the technical account plan: the customer’s architecture, their constraints and roadmap, where Everpure is deployed today, where the whitespace is, and which plays we run next.
• Become the go-to technical counterpart for infrastructure architects, storage and platform engineering leaders, and technology executives.
• Lead the technical side of complex pursuits from discovery through decision, including solution design, sizing, RFI and RFP responses, proofs of concept, lab evaluations and head-to-head competitive bake-offs.
• Help customers design the container, storage and data layer for AI at scale: GPU cluster storage, inference and cache offload, retrieval and analytics pipelines, and governed data in place.
• Run motions around Kubernetes and OpenShift data services, virtualization transitions, NVMe over TCP and Ethernet block, object storage, and cyber resilience.
• Pull in the right specialists, professional services and partner engineers at the right moment, keep them aligned on one plan, and hold the technical workstreams to owners, dates and a clear definition of done.
• Partner with the GAM on account planning, forecast and pipeline hygiene.
• Represent the requirements of the most demanding financial institutions back to product management, and help shape roadmap priorities with specific, evidence-based input.
WHAT YOU BRING
• Ten or more years in enterprise infrastructure, with at least five in a customer-facing presales, solutions architecture or field engineering role.
• Direct experience covering large financial services institutions is strongly expected.
• Hands-on command of enterprise block, file and object storage, data protection and replication, and how they behave under real production load.
• Working fluency across virtualization, Kubernetes and container platforms (OpenShift in particular), networking for storage (Ethernet, NVMe over TCP, RDMA, Fibre Channel), and at least one major public cloud.
• Strong Executive communication skills
• A track record of winning technical evaluations against established storage and infrastructure vendors, and of building displacement cases that survive customer scrutiny.
• Familiarity with analytics and lakehouse platforms, data governance and data discovery, and how data placement decisions affect cost, compliance and AI readiness strongly preferred
• Exposure to GPU infrastructure and AI workloads, such as NVIDIA DGX and SuperPOD reference architectures, GPUDirect Storage, inference serving frameworks (vLLM, NVIDIA Dynamo, llm-d) and the storage patterns behind training, inference and retrieval is a plus
• Relevant certifications a plus (Kubernetes, Red Hat, cloud, NVIDIA or major storage platforms) preferred
• Prior experience with Everpure FlashArray, FlashBlade or Portworx, from either the vendor or customer side, is a plus but not required.
#LI-REMOTE
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Salary ranges are determined based on role, level and location. For positions open to candidates in multiple geographical locations, the base salary range is reflective of the labor market across the applicable locations.
This role may be eligible for incentive pay and/or equity.
There is no application deadline and we accept applications on an ongoing basis
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