Jobs at Cadre AI

As an AI Consultant, you will lead AI strategy engagements, develop comprehensive roadmaps, and foster long-term relationships with clients, ensuring on-time delivery and project success.

The Marketing Director will lead brand strategy, demand generation, and community efforts, establishing Cadre as a premium AI transformation firm and executing various marketing initiatives.

The Senior AI Engineer builds complex backend AI modules, optimizes retrieval systems, manages deployments, and develops internal tools at Cadre AI.

Own the full sales cycle for AI strategy engagements: prospecting, qualifying, running discovery, managing pipeline in HubSpot, and closing $75K net new monthly. Execute consultative sales, collaborate with delivery teams, and provide market feedback to leadership.

Support client engagements through research, transcript processing, synthesis, and production of decks and deliverables using AI tools. Manage scheduling, ClickUp task tracking, cross-team handoffs, and follow-ups to ensure consultants are prepared and engagements run smoothly.

Manage pod operations for AI consulting engagements: onboard clients, build and maintain ClickUp infrastructure, run daily/weekly rhythms, track workloads, surface blockers, maintain task hygiene, lead client communication and meeting logistics, produce weekly recaps, and support monthly operating reviews.

The Forward Deployed AI Engineer at Cadre AI builds production AI systems, directly collaborates with clients to identify opportunities, and manages end-to-end project delivery from architecture to execution.

Triage AI opportunities, shape technical solutions, write precise SOWs and internal handovers, identify reuse vs. new engineering, and coordinate sales and engineering to deliver scoped AI engagements (5–10 concurrently, 30–45 day cycles). Ensure delivery-ready documentation and flawless handoffs to implementation teams.

Build and deploy production LLM systems: backend AI modules, RAG pipelines, agentic workflows, and scalable infrastructure. Own end-to-end delivery, optimize retrieval accuracy and latency, implement IaC and containerized deployments, write tests and observability, and abstract reusable internal tools to accelerate future client work.

The Senior AI Engineer will design, build, and optimize production AI systems, focusing on backend modules, retrieval infrastructure, and deployment processes. Responsibilities include working on complex client requirements, ensuring accuracy in data retrieval, and maintaining production systems, all while contributing to internal tools to enhance future projects.

Lead end-to-end AI transformation for a portfolio of 5–10 clients: define AI roadmaps, own delivery and P&L, manage client relationships and account growth, lead a cross-functional pod (≈5), drive adoption, run discovery/scoping/proposals, and ensure measurable business impact using AI, automation, and modern LLM capabilities.