OpenAI
Solutions Engineer, Digital Natives (Strategics)
About this role
OpenAI seeks an experienced Solutions Engineer to partner with enterprise Digital Native customers, helping them develop AI strategies and implement high-value use cases using OpenAI's products. You'll combine technical expertise with business acumen to guide customers through evaluation and adoption while serving as their trusted advisor on security, architecture, and product capabilities.
What you'll do
- Provide pre-sales technical expertise and demonstrations to Digital Native prospects and customers
- Build prototypes and lead proof-of-concept projects to validate AI use cases and business value
- Develop architecture recommendations and technical guidance tailored to customer needs
- Create documentation, guides, and resources addressing common technical questions
- Gather customer feedback and represent customer needs to internal product and engineering teams
- Support security and compliance discussions, escalating complex requirements to appropriate teams
What they're looking for
- Technical pre-sales and enterprise sales experience
- Python or JavaScript programming
- Cloud and network architecture knowledge
- Generative AI and machine learning prototyping
- IT security and enterprise architecture understanding
- Executive presentation and communication abilities
- B2B SaaS product knowledge
- Complex problem-solving and ownership mindset
Benefits
- Hybrid work model (3 days per week in San Francisco office)
- Relocation assistance for new employees
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OpenAI
OpenAI builds AI infrastructure and products, including large-scale data center campuses for AI computing and generative AI applications for enterprise customers. The company is hiring civil engineers, project engineers, electrical design engineers, data center R&D engineers, and AI deployment engineers to expand its infrastructure capabilities and help customers deploy AI solutions.
View all jobs at OpenAILikely interview questions
- Walk us through a time you identified and scoped a high-value AI or ML use case for an enterprise customer. How did you validate it and what was the business impact?
- Describe your experience building or demonstrating prototypes of generative AI or ML solutions. What tools and frameworks have you used, and how did you communicate technical limitations to non-technical stakeholders?