Principal Solutions Engineer, Enterprise

Responsibilities

• Own technical strategy and execution for the company’s most complex, high-value enterprise opportunities, acting as the ultimate arbiter of the “technical win”
• Serve as a trusted advisor to executive stakeholders (CTOs, Heads of AI, Engineering leaders), guiding long-term AI/LLM adoption strategies
• Architect and lead end-to-end solution design, from discovery through pilots and productionization, across ambiguous and evolving customer requirements
• Drive cross-functional alignment across Sales, Product, and Engineering to unblock critical technical and business challenges
• Define and shape large, multi-phase Scopes of Work, translating ambiguous customer problems into scalable, production-ready solutions
• Lead high-impact customer engagements, including executive presentations, technical deep dives, and workshops
• Influence Scale’s product roadmap by synthesizing customer insights and advocating for high-leverage feature development
• Mentor and elevate other Solutions Engineers, establishing best practices across demos, pilots, and technical sales strategy
• Drive org-level initiatives that improve win rates, shorten sales cycles, and increase the scalability of the Solutions Engineering function

Requirements

• Deep technical background with significant experience in customer-facing engineering roles (pre-sales, forward-deployed, or post-sales) at enterprise scale
• Proven track record of owning and closing complex, multi-stakeholder technical deals with Fortune 500 or equivalent enterprises
• Strong systems thinking and architecture experience across cloud, data, and AI/ML systems
• Hands-on experience with programming languages such as Python, Java, or similar, with the ability to prototype and validate solutions when needed
• Experience operating as a senior technical advisor to executive stakeholders, with strong presence and credibility
• Demonstrated ability to navigate ambiguity, influence without authority, and drive alignment across diverse teams
• Exceptional communication skills, with the ability to translate between business, product, and technical audiences
• High degree of ownership, intellectual curiosity, and bias for action in fast-paced, ambiguous environments

Nice to Haves

• Deep experience with Generative AI / LLM applications in enterprise environments
• Background in forward-deployed engineering or building production-grade ML systems
• Experience in regulated industries such as financial services, insurance, or healthcare