The opportunity
WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence.
What you'll do
Lead and empower a team of highly skilled solutions architects, fostering: their technical growth and career development across complex enterprise AI engagements
Drive the successful adoption and deployment of WRITER's generative AI: platform by overseeing key pre-sales technical engagements, including use case discovery, proof-of-concept execution, and value realization for strategic customers
Partner closely with sales leadership and go-to-market teams to develop: strategic account plans, define compelling technical value propositions, and accelerate pipeline growth for WRITER's solutions
Act as an executive technical sponsor for WRITER’s most strategic accounts,: building strong relationships with C-level stakeholders and becoming their trusted advisor in AI strategy and implementation
Influence WRITER's product roadmap by gathering critical market insights and: customer feedback, ensuring our platform continuously addresses evolving enterprise AI needs
Architect robust, scalable, and secure AI solutions for diverse enterprise: environments, integrating WRITER's platform with complex customer data ecosystems and existing technical stacks
What they're looking for
- Transform how we facilitate customer evaluations and proofs of concept,: implementing best practices and scalable processes that demonstrate clear ROI and accelerate time-to-value for our clients
- A minimum of 8 years of experience in a customer-facing technical role, with: at least 4 years in a management capacity leading a pre-sales or solutions architecture team focused on enterprise software, cloud, or AI solutions
- Proven expertise in leading and scaling a solutions architecture or sales: engineering organization within a high-growth, fast-paced technology company, ideally blending startup agility with enterprise best practices
- Deep technical proficiency in generative AI, large language models (LLMs),: machine learning, and cloud-native architectures (AWS, Azure, GCP), coupled with hands-on experience in Python or similar scripting languages
