Solutions Architect, SF

present of AI; San Francisco (CA); Sur place; USD 120 000 - 180 000; Plein temps

Résumé du poste

Exa in San Francisco is seeking a mid-level Customer & Solutions engineer to own the technical presales for our AI search API. You will code demos, run proofs of concept end-to-end, and perform discovery calls, design evaluations, and competitive argumentation.

You will bridge engineers and executives, pairing hands-on engineering with presales to demonstrate value, shape evaluations, and ensure clean handoffs to the product and engineering teams after a deal closes.

Qualifications

• Strong candidate combines hands-on engineering with several years of presales work.
• Ability to build demos and run proofs of concept end-to-end.
• Experience speaking to both engineers and executives.

Responsabilités

• Code demos and build reference prototypes for prospects.
• Run discovery calls and design evaluations.
• Present technical cases and compete against rivals.
• Handoff to engineering after deals close.

Connaissances

Hands-on coding

Demo & proof-of-concept

Presales experience

Technical communication

Outils

APIs

Demonstrations

Description du poste

Customer & Solutions · San Francisco, California · FullTime · Mid level

This role is the technical half of a sales team for a search API aimed at AI builders. It asks for someone who can code well enough to build demos and run proofs of concept end to end, and who can also run discovery calls, design evaluations, and argue the technical case against rivals. A strong candidate pairs hands on engineering with a few years of presales work at a developer or AI focused company, and can talk to both engineers and executives.

How it fits the AI era

The product itself serves AI models and agents, so the work sits close to how AI systems find and use information. Much of the demo and prototype building can be sped up with AI coding tools, which shifts the value toward judgment about what to show, how to design a fair evaluation, and how to read a customer's real problem. The human parts are the discovery conversation, the competitive argument, and the clean handoff to engineering after a deal closes.

How it builds AI experience

A person here would gain direct practice building with large language models, retrieval, and agents, since the job is to prove search quality on customer problems. They would learn to design and run evaluations that compare quality, latency, and cost, which is useful experience for anyone moving deeper into applied AI. Building sample apps and reference architectures for prospects is a practical way to grow that skill before or during the role.

Worth showing

• Hands on coding
• Demo and prototype building
• LLM and retrieval work

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Exa

Exa is an applied AI lab that builds a search engine and API for AI models and agents, per the company.