Public Sector Solutions Engineer, SLED
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Public Sector Solutions Engineer, SLED (AI SaaS): Collaborate with state, local-government, and education customers to demonstrate ’s AI-powered search and streamline workflows with an accent on custom demos, technical POCs, and security discussions. Focus on navigating complex multi-stakeholder deal cycles, building ROI reports, and overcoming technical objections.
Location: Remote (must be based in Austin, TX)
Salary: $110,000 - $235,000 OTE annually
Company
is the Work AI platform that powers intelligent search, AI assistants, and scalable AI agents across enterprises with over 100 SaaS connectors.
What you will do
- Partner with Account Executives to navigate complex deal cycles with C-level executives in public sector
- Build relationships with key decision makers and create custom demos based on customer needs
- Run technical POC cycles and lead customer-facing discovery calls
- Lead security conversations and develop ROI/business justification reports
- Work cross-functionally with product and engineering teams as the voice of the customer
Requirements
- Must be based in Austin, TX
- 3-5+ years of sales engineering or solution consulting in SaaS with public sector focus (state, local, education)
- Bachelor's degree in CS or related field
- Experience partnering with AEs on enterprise technical deal cycles
- Consultative approach to solving business challenges and overcoming technical/security objections
- Familiarity with cloud environments (GCP, AWS, Azure) and proficiency in Python or Java
Culture & Benefits
- Comprehensive benefits: medical, vision, dental coverage, generous time-off, 401k
- Home office stipend, annual education and wellness stipends
- Vibrant culture with regular events and daily healthy lunches
- Commitment to diversity and inclusion
Hiring process
- AI-focused exercise or discussion to assess AI fluency in the role
- Standard interview process evaluating technical skills, experience, and fit
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