AI Solution Engineer

About the job

Responsibilities

• Partner with sales teams to lead technical discovery and understand customer context, workflows, technology, data, and security requirements.
• Translate customer needs into practical solution designs using LLMs, APIs, RAG, tool calling, and agentic workflows.
• Recommend appropriate architecture patterns, configuration options, and implementation approaches.
• Advise customers on API integration, including authentication, rate limits, performance, and data flow.
• Help customers identify suitable LLM-based solutions versus conventional software or automation.
• Explain design trade-offs related to accuracy, grounding, security, privacy, latency, cost, and support.
• Develop demonstrations to validate customer use cases and show a path to implementation.
• Lead discussions on security posture, including data handling, encryption, access control, and compliance.
• Respond to customer security questionnaires and assist with risk assessments.
• Communicate how the platform aligns with enterprise security practices and regulatory requirements.
• Partner with sales, product, and engineering to shape solution proposals.
• Document recommended architectures, configurations, and onboarding plans.
• Identify and provide mitigation strategies for potential technical blockers.
• Collaborate with Product and Engineering teams to escalate issues, influence roadmaps, and share customer insights.
• Support Customer Success teams during the early post-sale phase for smooth technical handoff.
• Contribute to internal knowledge bases, FAQs, and solution playbooks.

Requirements

• Minimum of 3 years of experience in solutions consulting, sales engineering, solution architecture, or technical account management.
• Hands-on experience building, configuring, or evaluating generative AI solutions.
• Practical knowledge of leading AI platforms (e.g., ChatGPT, Claude, Gemini, Microsoft Copilot).
• Working knowledge of LLM APIs, prompt design, structured outputs, tool/function calling, RAG, embeddings, and retrieval techniques.
• Experience designing AI solutions that securely connect with enterprise applications and data sources.
• Understanding of LLM application performance, limitations, and improvement strategies (grounding, evaluation, oversight).
• Ability to explain AI concepts and architectural choices to diverse stakeholders.
• Experience designing or prototyping agentic workflows, including tools, connectors, or agent frameworks.
• Familiarity with emerging integration standards like Model Context Protocol.
• Experience with AI evaluation, guardrails, monitoring, or observability.
• Strong understanding of API concepts (RESTful design, authentication, error handling).
• Familiarity with scripting, JSON payloads, or light troubleshooting.
• Knowledge of SOC2, ISO 27001, GDPR, and enterprise security standards.
• Background working with SMBs or high-velocity sales teams.

Benefits

• Medical, dental, vision, life, and long-term disability coverage
• 401(k) plan
• Bonus opportunities
• Paid holidays
• Paid time off