Sales Engineer, Applied AI
Sales Engineer builds and demonstrates AI automation POCs using no-code platforms for enterprise customers, advising on prompt engineering, LLMs, and agentic workflows. Partners with AEs; requires 3+ years AI/ML experience and customer-facing technical expertise.
What You’ll Do
- Strategic Solutioning: Partner with Account Executives to uncover high-value customer pains. Translate these into business requirements then into concrete AI automation designs using our platform.
- Build to Win: Design and configure compelling Proofs of Concept (POCs). Leverage our drag-and-drop workflow builders and collaboration AI toolsets to show customers their own data being processed in real-time.
- Applied AI Advisory: Act as a trusted advisor on “The Art of the Possible.” Educate customers on prompt engineering best practices, agentic workflows, and how to govern AI safely, without needing to discuss low-level model weights.
- Champion the User Experience: Push the boundaries of our no-code tools as the primary feedback loop to Product Management, helping refine the user interface and agent capabilities.
What You Bring
- Hybrid DNA: Technical chops of a software engineer and communication skills of a consultant. Comfortable in a Jupyter Notebook as in a boardroom.
- Applied AI Fluency: 3+ years of experience building or deploying AI/ML solutions. Understand functional application of LLMs, Prompt Engineering, practicalities of Generative AI, LLMs (GPT, Gemini, Anthropic), and RAG (Retrieval-Augmented Generation).
- Technical Storytelling: Proven track record in a customer-facing role (Solutions Consultant, Sales Engineer, or Business Analyst). Excel at simplifying complex AI concepts for non-technical stakeholders.
- Data Literacy: Comfortable working with unstructured data (documents, emails, chats) and extracting structured value from it.
- Sales Engineering Excellence: Proven track record in a customer-facing technical role (Sales Engineering, Solutions Architecture, or Forward Deployed Engineering). Map technical features to business value.
- Problem Solving: Love unstructured problems. Visualize AI pipeline for messy datasets (invoices, medical records, financial statements).
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or equivalent practical experience.
Compensation
For US-based roles: Base salary range $157,000 to $175,000 + commission, equity, and benefits. Actual pay may vary based on location, experience/skills, and impact.
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