Customer Engineer

About NeuroSpark

NeuroSpark builds and operates a high-performance AI inference platform that helps enterprises run large language models faster, cheaper, and at scale. Inference infrastructure is the foundation the entire AI application layer runs on — every AI product ultimately depends on how fast, how reliably, and how affordably models can serve their users. Our vision is to make that layer so efficient that compute is never the reason a good AI product fails.

About the Role

NeuroSpark Inc operates an enterprise AI inference platform that helps customers run and scale production AI workloads through reliable, high-performance infrastructure. As a Customer Engineer, you will own the technical onboarding and solution-engineering experience for customers from initial integration through production launch and expansion.

You will work directly with customer engineering teams to understand their architecture, integrate NeuroSpark's APIs and infrastructure, troubleshoot deployment issues, and translate customer requirements into practical technical solutions. This role sits at the intersection of customers, Engineering, Product, and Account Management.

Responsibilities

· Own technical onboarding for new customers, from initial architecture discussions and API integration through production launch.

· Design and recommend integration approaches based on each customer's application architecture, cloud environment, traffic profile, and operational requirements.

· Guide customers through API usage, authentication, deployment, cloud infrastructure, and Kubernetes-based environments.

· Troubleshoot technical blockers across APIs, networking, cloud infrastructure, Kubernetes, model access, usage, and deployment workflows.

· Partner closely with NeuroSpark Engineering to investigate customer issues, drive resolution, and communicate technical findings clearly back to customers.

· Build solution examples, implementation guidance, technical documentation, and repeatable onboarding playbooks that improve time-to-production.

· Monitor onboarding progress and proactively identify risks, dependencies, or technical gaps that could delay customer launch or adoption.

· Translate recurring customer requirements and integration pain points into actionable Product and Engineering feedback.

· Support customer production launches, migrations, scaling events, and ongoing technical adoption as usage grows.

· Work with Account Management to identify technical opportunities for deeper platform adoption and account expansion.

Qualifications

· Hands-on experience integrating and supporting APIs in production environments.

· Strong working knowledge of cloud infrastructure and public cloud environments.

· Hands-on experience with Kubernetes, including deployment, configuration, and troubleshooting of containerized workloads.

· Strong technical problem-solving and debugging skills, with the ability to work through ambiguous customer issues.

· Ability to understand customer architecture and communicate effectively with software engineers, infrastructure teams, and technical leaders.

· Strong written and verbal communication skills and comfort working directly with customers.

· High ownership, responsiveness, and ability to operate effectively in a fast-moving startup environment.

· Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.

Nice to Have

· Experience with SQL and production data systems.

· Experience with GPU infrastructure or AI/ML infrastructure.

· Programming experience in Python and/or C++.

· Experience in Customer Engineering, Solutions Engineering, Forward Deployed Engineering, Solutions Architecture, or Technical Account Management.

· Experience supporting AI/ML, infrastructure, developer-platform, or enterprise technology customers.

· Familiarity with LLM APIs, inference systems, observability, or distributed systems.

What Success Looks Like

Customers move from evaluation to production quickly, technical blockers are resolved with clear ownership, and onboarding becomes increasingly repeatable as the company scales. You become a trusted technical partner to customer engineering teams while helping NeuroSpark improve the platform based on real production use cases.

Compensation

The expected base salary range for this position is $130,000-$150,000 USD per year. Actual compensation will depend on experience, role scope, and qualifications. The position may also include equity and company benefits.