Leader, AI Hyperspecialist Solutions Engineer (Central US)

Meet The Team

The AI Hyperspecialist Solutions Engineering leader directs a team of solutions engineers who partner with sales, customers, and product teams to design and implement AI-powered solutions. This role requires deep technical credibility in AI/ML combined with strong people leadership, ensuring the team effectively translates customer needs into technical solutions while driving revenue and customer success.

Your Impact

Team Leadership: Manage, coach, and develop a team of solutions engineers/architects; conduct 1:1s, performance reviews, and skill development plans

Pre-Sales Support: Oversee technical discovery, solution design, demos, and proof-of-concepts (POCs) for prospective customers evaluating AI products

Customer Enablement: Guide the team in helping customers integrate AI/ML APIs, models, or platforms into their existing systems

Technical Strategy: Develop reusable solution architectures, demo environments, and best practices for common AI use cases (e.g., RAG, agents, fine-tuning, automation)

Cross-functional Collaboration: Partner closely with Sales, Product, Engineering, and Customer Success to align technical solutions with business goals and feed customer feedback into the product roadmap

Escalation Management: Serve as an escalation point for complex technical objections or implementation blockers during the sales cycle

Enablement & Training: Build technical training materials and certifications for the solutions engineering team and broader sales org

Process & Metrics: Track team performance metrics (POC win rate, time-to-value, deal velocity) and continuously improve pre-sales processes

Hiring: Recruit and interview candidates with strong technical and communication skills

Minimum Qualifications

Bachelor's degree in Computer Science, Engineering, or related technical field

5+ years in solutions engineering, sales engineering, or technical consulting, with 2+ years in a leadership role

Strong understanding of AI/ML concepts LLMs, embeddings, RAG, model APIs, prompt engineering

Experience with cloud platforms (AWS, GCP, Azure) and integration technologies (APIs, SDKs, webhooks)

Proven ability to communicate technical concepts to both technical and non-technical/executive audiences

Track record of supporting complex enterprise sales cycles

Preferred Qualifications

Hands-on experience building demos or POCs using LLM APIs (OpenAI, Anthropic, etc.) or ML frameworks

Background in customer-facing technical roles at a SaaS or AI/ML company

Familiarity with vector databases, agentic frameworks, or MLOps tooling

Experience presenting at conferences, webinars, or customer events

Prior experience in a specific target industry (e.g., enterprise software, fintech, healthcare)