Director of Solutions Engineering, Enterprise West

Decagon Decagon · Vertical AI · San Francisco, CA · Sales

Director of Solutions Engineering for a conversational AI platform, focusing on pre-sales technical leadership, team management, and driving enterprise adoption of AI solutions. This role involves engaging with complex enterprises, designing technical strategies, and collaborating with sales, product, and engineering teams.

What you'd actually do

  1. Hire, mentor, and manage a team of Solutions Engineers, providing technical guidance, coaching, and career development.
  2. Establish and operationalize best practices for pre-sales solutioning, proof-of-concepts, and technical validation.
  3. Partner with Sales leadership to co-develop go-to-market strategies and align technical execution with business goals.
  4. Engage directly with a select portfolio of enterprise prospects and customers, guiding them through discovery, solution design, and ROI validation.
  5. Ensure your team delivers compelling demonstrations, prototypes, and solution engineers tailored to customer needs.

Skills

Required

  • 7+ years of experience in pre-sales technical roles such as Solutions Architect, Sales Engineer, or equivalent.
  • 3+ years of experience managing or leading pre-sales/solutions engineering teams.
  • Proven success working with large enterprise customers and navigating complex buying cycles.
  • Strong technical proficiency with enterprise AI deployments, API integrations, and production system architectures.
  • Excellent communication skills, with the ability to engage executives, business stakeholders, and technical teams with equal credibility.
  • A collaborative, organizational mindset with a track record of building scalable teams and processes.
  • Ability to thrive in fast-moving, high-growth environments with significant ambiguity.
  • Strong executive presence and consultative skills, capable of establishing trust and credibility with senior leaders.

Nice to have

  • Experience in AI/Generative AI pre-sales engineering or enterprise deployments.
  • Familiarity with enterprise architecture design, developer tooling, SDKs, and integration patterns.
  • Background in software engineering or systems engineering, enabling you to dive deeply into technical discussions.
  • Experience integrating telephony infrastructure or other complex enterprise systems.
  • Knowledge of LLM architecture, prompt engineering, evaluation, and AI-powered solution design.
  • Thought leadership experience through conferences, webinars, or published technical content.

What the JD emphasized

  • enterprise AI deployments
  • AI/Generative AI pre-sales engineering
  • LLM architecture, prompt engineering, evaluation, and AI-powered solution design

Other signals

  • AI-native platform
  • AI agents
  • enterprise AI adoption patterns