Solutions Engineer, Enterprise AI

Posted Yesterday
Hiring Remotely in San Francisco, CA, USA
In-Office or Remote
120K-140K Annually
Entry level
Artificial Intelligence • Machine Learning • Software • Automation
The Role
Own presales discovery, solution architecture, technical demos, prototypes, proof-of-concept definition, technical evaluations, RFP responses, and security questionnaires for enterprise AI customers. Translate customer workflows and technical requirements into validated architectures and measurable business value, manage implementation risks, and provide accurate delivery handoffs. Convert field insights into reusable reference architectures, demos, and product improvements.
Summary Generated by Built In
Solutions Engineer, Enterprise AI

San Francisco on-site preferred; remote is acceptable · Full-time · Travel required

Base salary: $120,000–$140,000 USD annually. Equity: 0.05–0.1%. This role does not include commission. U.S. citizenship required. Visa sponsorship is not available.

Make enterprise AI credible

You will help customers understand what Sainapse can do, how it fits their environment, and what evidence they need to move forward. Own presales discovery, solution architecture, demos, and technical validation, then create a clean handoff to delivery.

What you will own
  • Understand customer workflows, data, integrations, security requirements, and operational goals.

  • Design customer-specific architectures and build credible demos and lightweight prototypes.

  • Define proof-of-concept datasets, scoring, acceptance criteria, scope, and dependencies with Forward Deployment.

  • Lead technical evaluations, RFP responses, and security questionnaires with the right internal experts.

  • Connect technical capabilities to measurable operational value and clearly distinguish validated capabilities from open questions.

  • Turn field learning into reference architectures, reusable demos, and better product decisions.

What you bring
  • Experience in solutions engineering, technical consulting, architecture, or customer-facing delivery.

  • Enough coding fluency to work with APIs, inspect logs, and build useful prototypes.

  • Clear communication with technical teams and business stakeholders.

  • Familiarity with enterprise systems such as Salesforce, ServiceNow, Freshworks, Zendesk, SAP, or Oracle.

  • Sound judgment about promises, validation, implementation risk, and the practical limits of agentic AI.

What success looks like

Evaluations move faster because the right questions are answered with evidence. Strong-fit opportunities gain technical confidence, poor-fit opportunities are disqualified early, and delivery receives an accurate account of commitments and dependencies.

About Sainapse

Sainapse builds agent-first software for customer operations, helping teams resolve work across the systems they already use. Our production work spans customer support and document and order workflows, with configurable autonomy and human review. We are also building account intelligence that connects customer signals.

We are a small team with broad ownership. We value first-principles thinking, direct communication, thoughtful use of AI, and evidence of customer impact. You will work closely with the founders and our product, engineering, and delivery teams.

Skills Required

  • Experience in solutions engineering, technical consulting, architecture, or customer-facing delivery
  • Coding fluency sufficient to work with APIs, inspect logs, and build useful prototypes
  • Clear communication with technical teams and business stakeholders
  • Familiarity with enterprise systems such as Salesforce, ServiceNow, Freshworks, Zendesk, SAP, or Oracle
  • Sound judgment regarding promises, validation, implementation risk, and the practical limits of agentic AI
  • U.S. citizenship
  • Ability to travel for the role
  • San Francisco on-site work preference; remote work is acceptable
Am I A Good Fit?
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The Company
17 Employees
Year Founded: 2017

What We Do

Sainapse is an agentic AI platform for customer support that resolves most queries autonomously, while routing true edge cases to human experts. It connects data, workflows, and policies into a single intelligence layer on top of existing systems.

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