S
Scale AI
Staff Solutions Engineer (Enterprise)
Skills
PythonProduct StrategyJavaMachine LearningAISales Strategy
2 months ago
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Important information
Contract type:
Permanent
Salary:
$180,000 – $225,000 / year
Location:
New York, NY, USA
Work mode:
Onsite
Published on:
20 August 2026
What they need
- Staff Solutions Engineers are trusted advisors to both customers and internal stakeholders, owning the most complex and high-impact opportunities
- They partner closely with Sales, Product, and Engineering leadership to drive technical strategy, secure executive alignment, and deliver differentiated solutions that win and expand strategic accounts
- Beyond individual deals, they influence product direction, define best practices, and elevate the capabilities of the broader Solutions Engineering organization
- 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
Benefits
- Health & Wellbeing: Our holistic approach to supporting Scaliens includes comprehensive health coverage, dental and vision insurance, mental healthcare services, and more. PTO policies and accommodating schedules ensure you’ll get time off when you need it to relax and recharge. Note that our offerings may vary by region as we strive to respond to the unique needs of Scaliens around the globe.
- Personal & Career Growth: Continuously learn and grow through annual learning & development stipend, attending leadership breakfasts, manager training, speaker series, and joining an ERG.
- Building Scale Community: We welcome guests to our offices, and you can expect to see Scalien families and friends around. Join local happy hours, and accept invites to game nights, book clubs, and many other employee-led community events.
- Parental Support: Balancing work and family is essential, and Scale understands the importance of having adequate leave policies in place to promote a healthy home and work life.- Strong systems thinking and architecture experience across cloud, data, and AI/ML systems
- Proven track record of owning and closing complex, multi-stakeholder technical deals with Fortune 500 or equivalent enterprises
- Demonstrated ability to navigate ambiguity, influence without authority, and drive alignment across diverse teams
- Experience operating as a senior technical advisor to executive stakeholders, with strong presence and credibility
- 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
- Hands-on experience with programming languages such as Python, Java, or similar, with the ability to prototype and validate solutions when needed
- Deep technical background with significant experience in customer-facing engineering roles (pre-sales, forward-deployed, or post-sales) at enterprise scale
- Experience in regulated industries such as financial services, insurance, or healthcare
- Background in forward-deployed engineering or building production-grade ML systems
- Deep experience with Generative AI / LLM applications in enterprise environments
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