You will serve as the founding design hire, establishing UX/UI practices and design standards for AI-driven client solutions. You will lead user discovery, create intuitive interfaces, and partner with product managers and engineers to deliver high-quality, production-ready AI products.
You will serve as a technical partner to OpenAI, building industry-specific AI experiences and leading workshops for customers. You will also translate complex business problems into actionable technical solutions and scale successful patterns into reusable assets.
The GTM Forward Deployed Engineer will partner with the sales team to qualify opportunities, translate business goals into technical architectures, and build proofs of concept. They are responsible for authoring statements of work and codifying the company's deal-shaping process into repeatable playbooks.
The Lead Forward Deployed Engineer is responsible for overseeing delivery quality, technical direction, and team development across a portfolio of client accounts. They act as a field leader to ensure project success, manage client expectations, and maintain high technical standards.
The Senior Forward Deployed Engineer will lead complex technical delivery for high-stakes client engagements, owning architecture and end-to-end solution quality. They will also mentor team members and act as a senior technical voice to build and maintain client trust.
Build and lead Eliza's healthcare vertical from the ground up, focusing on AI solutions for claims accuracy and decision velocity. This involves shaping and selling solutions to senior healthcare executives and owning the full engagement arc from scoping to delivery.
The Forward Deployed Engineer translates complex business needs into scalable AI solutions by embedding with client teams. They are responsible for the technical design, prototyping, and deployment of custom AI systems and LLM integrations.
The AI Product Manager acts as the technical bridge between business development and engineering to scope and deliver AI solutions for clients. They own the end-to-end product lifecycle, from use case discovery and prioritization to production launch and outcome measurement.
The lead will identify and map enterprise workflows to translate them into high-impact AI build plans. They act as the primary bridge between business executives and technical engineering teams to ensure measurable ROI.
