Solutions Engineer, Enterprise AI

Sainapse Inc

$120K — $140K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years in solutions engineering or technical consulting roles
  • Strong coding fluency, particularly with APIs for building prototypes
  • Excellent communication skills for engaging technical teams and business leaders
  • Experience with enterprise systems (e.g., Salesforce, SAP, Oracle)
  • Solid understanding of AI application limits and implementation risks.

Responsibilities

  • Understand customer workflows and operational goals to tailor solutions
  • Design architectures and create credible demos for clients
  • Define proof-of-concept datasets and evaluation criteria
  • Lead technical evaluations and coordinate with internal experts
  • Link tech capabilities to measurable customer value
  • Transform field insights into reference architectures and product direction.

Benefits

  • Opportunity for professional growth in a rapidly evolving AI field
  • Travel opportunities for direct customer engagement
  • Flexible remote work options based on role requirements
  • Potential for equity participation in the company
  • Collaborative and innovative team culture.
Full Job Description
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.

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