Technical GTM Intern

Novita AI is an AI & Agent Cloud platform for builders.

We provide high-performance Model APIs, dedicated inference infrastructure, and Agent Sandbox environments that help developers and enterprises build, deploy, and scale production AI applications.

Our customers range from fast-growing AI startups to teams building coding agents, AI assistants, and large-scale inference products.

We’re looking for a Technical GTM Intern who is excited about both technology and customers.

This is not a traditional sales internship. You’ll work directly with technical founders, engineers, and AI teams to understand what they are building, help them evaluate and adopt Novita AI, and support them as they move from experimentation into production.

You’ll operate at the intersection of technical discovery, customer engineering, and go-to-market. One day you may help a customer understand an inference performance issue; another day you may help scope a production workload, coordinate a quota increase, or identify how an account can expand.

You do not need previous sales experience. We care much more about technical curiosity, communication ability, ownership, and your ability to learn quickly.

• Work directly with AI startups, developers, and technical teams evaluating Novita AI.

• Understand customer workloads, including model usage, latency, throughput, concurrency, reliability, and sandbox requirements.

• Help customers get started with Novita’s Model APIs, dedicated inference endpoints, and Agent Sandbox.

• Partner with Forward Deployed Engineers to troubleshoot technical issues and remove blockers to production adoption.

• Support customer conversations around usage, quotas, capacity, pricing, and production rollout.

• Research and identify promising AI companies, developers, and emerging use cases.

• Track customer adoption and identify opportunities for workloads to grow.

• Build lightweight demos, scripts, or technical examples when useful to move a customer forward.

• Gather product and competitive insights from customer conversations.

• Work closely with engineering, product, and GTM teams across the US and Asia.

As you ramp up, you may independently own smaller customer relationships from initial conversation through technical evaluation, production adoption, and expansion.

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Data Science, AI/ML, or another technical field.

• Strong interest in AI products, developer tools, or cloud infrastructure.

• Comfortable communicating with engineers and learning technical systems quickly.

• Basic understanding of APIs, LLMs, and modern AI applications.

• Some programming experience, ideally with Python or another general-purpose language.

• Strong written and verbal communication skills.

• High ownership and willingness to follow problems through to resolution.

• Comfortable operating in a fast-moving startup environment.

• Available approximately 20 hours/week during the academic term or full-time during summer.

• Experience building AI or software side projects.

• Experience using LLM APIs or developer platforms.

• Familiarity with inference concepts such as tokens, latency, throughput, caching, rate limits, or concurrency.

• Hackathon, startup, developer community, or open-source experience.

• Previous customer-facing, consulting, teaching, or leadership experience.

• Interest in startups, product, sales, or business development.

• Professional working proficiency in Mandarin Chinese.

You may be a strong fit if you enjoy:

• Understanding how technology works.

• Talking to people and figuring out what they actually need.

• Debugging why something isn’t working.

• Helping customers successfully launch products.

• Moving quickly between technical and business problems.

• Thinking about how a technical workload can grow into a meaningful customer relationship.

This role is especially well suited for technical students who enjoy building things but don’t necessarily want their entire career to be limited to writing code.