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Principal Solutions Architect
- New York, New York, United States
- New York, New York, United States
About
Role Summary QumulusAIis seeking a Solution Architect to help scale a high-velocitysales motionfor AI infrastructure. You will partner with Sales and channel partners as the technical lead across discovery, solution design, demonstrations, proof-of-concepts (POCs), security reviews, andthe technicalclose. This role requires strong technical depth, crisp communication, and the ability to manage multiple deals in parallel while creating repeatable technical sales assets that reduce cycle time and improve win rate.
This is a customer-facing role with travel up to50%to support onsite workshops, partner enablement, and key field events.
Key Responsibilities Strategic Technical Discovery & Architecture
Lead complex technicaldiscoveryand define scalable GPU and platform architectures aligned to customer business outcomes.
Set technical success criteria, architecture standards, and partner with Sales on executive-level account strategy.
Own high-impact demos and POCs with clear performance, cost, and risk outcomes.
Guidebenchmarking, surface tradeoffs, and influence technical and executive decision-makers.
Technical Close, Risk & Governance
Resolve critical technical objections and guide customers from evaluation to production.
Lead security and compliance discussions; shape technical scope for proposals, SOWs, and RFPs.
Define partner technical motions, reference architectures, and evaluation standards.
Act as senior technical escalation for partner-led deals and complex opportunities.
Establish repeatablearchitectures, POC frameworks, and technical sales best practices.
Translate field learnings into improved processes, enablement, and clean delivery handoffs.
Qualifications Experience & Background
6–10+ years in customer-facing technical roles (Principal/Senior Solutions Architect, Sales Engineer, Systems Engineer, or Technical Consultant) supporting infrastructure, cloud, HPC, or AI/ML platforms.
Proven experience working with largeenterpriseor strategic customers in complex, multi-stakeholder environments.
Bachelor’s orMaster’s degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent practical experience).
Willingness to travel up to 50%.
Technical Expertise
Deep understanding of IaaS, cloud-native and on-prem HPC/GPU architectures, and the requirements for running AI/HPC workloads at scale.
Strong hands‑on experience with Linux, networking, security fundamentals, and performance troubleshooting.
Expertisewith GPUs and AI/MLcomputestacks, including training vs. inference, distributed workloads, and common frameworks and tooling.
Experience designing andoperatingdistributed systems, including:
High-performance networking (TCP/IP, RDMA, InfiniBand, cluster networking)
Parallel/distributed storage systems and data pipelines
HPC schedulers and workloads (e.g.,Slurm, PBS, MPI)
Observability, hardwarehealthand performance telemetry
Proficiencywith containers and orchestration (Docker, Kubernetes) and model or workload deployment patterns.
Scripting and automation skills (Python, shell/bash) and infrastructure automation using tools such as Terraform and Ansible.
Business & Pre-Sales Acumen
Strong consultative technical selling skills with disciplined discovery and structured problem-solving.
Experience leading technical evaluations, POCs, and enterprise security and compliance reviews.
Ability to manage multiple concurrent engagements with clear ownership and follow-through.
Demonstrated success enabling and co-selling with channel partners (SI/MSP/reseller).
Leadership & Core Competencies
Principal-level judgment with the ability to connect deep technical decisions to measurable business outcomes.
Strategic thinker and technical storyteller, capable of influencing both practitioners and executive stakeholders.
High ownership, strong cross-functional collaboration with Sales, Product, Engineering, and Operations.
Ability to produce high-quality technical content (architectures, white papers, reference designs) thatscalesacross teams.
Startup mindset: biased toward action, adaptable, and comfortable tackling ambiguous, high-impact challenges.
Strong documentation habits and integrity in handling confidential customer information.
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Languages
- English
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