Customer Solutions Engineer – HPC & Cloud

Customer Solutions Engineer – HPC & Cloud

Location: Dallas, TX
Type: Direct Hire
Compensation: $170,000 – $240,000 base salary + bonus

Overview

GTN is seeking a Customer Solutions Engineer to support strategic HPC and cloud customers across advanced computing environments. This role will serve as a trusted technical advisor, helping clients design, deploy, optimize, and scale compute-intensive workloads, including large-scale AI/ML training and inference, advanced scientific simulations, and data-driven research platforms.

This position sits at the intersection of engineering, sales, product, and customer success. The Customer Solutions Engineer will act as the technical voice of the customer internally while representing GTN’s technical capabilities externally. This is a high-impact role for someone who enjoys solving complex technical problems, partnering closely with customers, and building long-term strategic relationships.

Key Responsibilities

Customer Advisory

• Serve as the primary technical point of contact for key and strategic customers.
• Troubleshoot complex HPC, cloud, infrastructure, and AI/ML workload challenges.
• Guide customers on compute performance optimization for ML training, inference, simulation, and other GPU-intensive workloads.
• Support seamless platform integration, scalability, reliability, and performance across customer environments.

Sales & Growth Support

• Partner with sales teams to identify growth opportunities within strategic accounts.
• Promote new platform capabilities and help customers understand how those capabilities solve business and technical challenges.
• Deliver compelling technical presentations, solution walkthroughs, architecture discussions, and product demos.
• Support pre-sales and post-sales technical engagement throughout the customer lifecycle.

Product Collaboration

• Act as a bridge between customers and internal product teams.
• Capture customer feedback, surface feature requests, and communicate technical pain points.
• Help ensure product roadmap decisions reflect real-world customer needs and platform usage patterns.
• Partner with engineering and product teams to improve platform usability, performance, and customer outcomes.

Stakeholder Engagement

• Engage with internal and external stakeholders to drive alignment around technical solutions.
• Help remove blockers for strategic accounts by coordinating across sales, product, engineering, support, and customer teams.
• Navigate technical tradeoffs and guide customers toward scalable, practical solutions.
• Build trust with technical leaders, business stakeholders, and executive sponsors.

Documentation & Enablement

• Contribute to technical documentation, reference architectures, implementation guides, and best-practice materials.
• Develop reusable customer-facing assets that improve onboarding, deployment, and long-term platform adoption.
• Share lessons learned across internal teams to improve customer support, solution delivery, and platform enablement.

Required Qualifications

• 5–10+ years of experience in roles such as Cloud Solutions Architect, Technical Account Manager, Customer Engineer, Solutions Engineer, Sales Engineer, or similar customer-facing technical positions.
• Hands-on experience with cloud, infrastructure, HPC, or GPU-based computing environments.
• Proficiency with Infrastructure as Code tools such as Terraform and Ansible.
• Experience with Kubernetes and Python programming.
• Strong understanding of GPU and HPC computing concepts, including ML training, inference workloads, and relevant technologies such as CUDA, OpenCL, or MPI.
• Ability to troubleshoot complex technical issues across infrastructure, platform, and workload layers.
• Strong customer-facing communication skills with the ability to build trust and foster long-term technical relationships.
• Ability to explain complex technical concepts clearly to both technical and non-technical audiences.
• Comfortable working cross-functionally with sales, product, engineering, support, and customer stakeholders.

Preferred Qualifications

• Hands-on experience with HPC and ML orchestration frameworks such as Slurm, Kubeflow, or MPI.
• Experience with deep learning frameworks such as PyTorch or TensorFlow.
• Familiarity with major cloud providers such as AWS, Azure, or GCP.
• Experience with NVIDIA hardware, GPU clusters, or accelerated computing environments.
• Strong project management skills with the ability to prioritize and deliver across multiple strategic accounts.
• Experience mentoring technical team members or contributing to team growth.
• Proven success navigating stakeholder negotiation, technical escalations, and cross-functional collaboration.

Ideal Candidate Profile

The ideal candidate is a highly technical, customer-facing engineer who can operate comfortably across HPC, cloud, GPU infrastructure, and AI/ML workloads. This person should be able to earn credibility with technical teams, partner effectively with sales and product, and help strategic customers solve complex computing challenges at scale.

The right candidate will bring a customer-first mindset, strong technical depth, and the ability to translate complex platform capabilities into practical solutions that drive customer success.