About the job
Join Distyl AI as a Forward Deployed AI Architect
Distyl AI specializes in creating production-grade AI systems that streamline core operational workflows for Fortune 500 companies. Through our strategic alliance with OpenAI, cutting-edge software accelerators, and extensive enterprise AI knowledge, we deliver effective AI solutions with a rapid time-to-value—often within a quarter.
We have empowered Fortune 500 clients from various sectors, including insurance, consumer packaged goods, and non-profits. When you join our team, you'll assist companies in recognizing, developing, and achieving value from their Generative AI investments, frequently for the first time. Our approach is customer-focused, ensuring we work backward from the customer's challenges while being accountable for generating financial impact and enhancing the experiences of end-users.
Led by a team of accomplished leaders from prestigious companies like Palantir and Apple, Distyl is supported by notable investors including Lightspeed, Khosla, Coatue, Dell Technologies Capital, Nat Friedman (Former CEO of GitHub), and Brad Gerstner (Founder and CEO of Altimeter), alongside board members from over a dozen Fortune 500 firms.
Your Role
As a Forward Deployed AI Architect, you will play a crucial role in constructing AI systems within the most intricate enterprise environments globally. This position demands professionals who can fully oversee how intelligent systems are designed, integrated, secured, and managed in production, while being actively involved in the technical processes.
Key Attributes: Our ideal candidates are seasoned builders with the expertise to create and refine end-to-end AI systems across complex enterprise architectures. They serve as trusted technical partners to client engineering teams, security divisions, and operations, making informed architectural decisions that weigh capability against risk and operational practicality. Their authority is built on performance rather than title.
Key Responsibilities
Oversee the technical framework of AI systems deployed in client settings.
Define the integration of models, agents, data pipelines, APIs, and orchestration layers, ensuring effective operation within existing enterprise infrastructures while maintaining safety and reliability at scale. Focus on architectural patterns that ensure consistency, safety, and long-term adaptability across deployments.
Engage actively throughout the project lifecycle, from building reference implementations to evaluating and evolving systems.

