The AI Security & DevOps Engineer will own the security standards for AI systems from prototype to production, including threat modeling and CI/CD gates. Additionally, this role will lead client security engagements, translating requirements into secure technical implementations and evidence packs.
You will own AI product builds from concept to production, managing client engagements and technical requirements. You are responsible for data engineering, system reliability, and serving as the primary technical contact for client stakeholders.
You will lead the development of a structured, searchable compliance system by mapping complex investment management agreements into computable rules. This involves defining semantic models, ensuring data traceability, and collaborating with legal and investment stakeholders to interpret guideline language.
Partner with client executives to identify high-leverage AI opportunities and translate business needs into actionable roadmaps. Collaborate with engineering teams to shape technical solutions and ensure successful implementation tied to business outcomes.
You will own the end-to-end development of AI products, from initial concept and requirement gathering through to production deployment. Additionally, you will serve as the primary technical contact for clients, managing data pipelines, system reliability, and performance metrics.
Design and ship end-to-end UI/UX for AI-native products, translating rough requirements into high-fidelity interfaces. Collaborate closely with engineers in fast build cycles to create scalable design patterns and information architecture for data-dense products.
The AI Product Manager translates strategy into usable products by owning client engagements from kickoff through iteration. They manage the product backlog, direct designers and engineers, and ensure high-quality AI output for enterprise clients.
