Jobs at Cadre AI

Build and ship production-grade AI systems: backend AI modules, agentic workflows, and optimized RAG/retrieval pipelines. Own end-to-end delivery, deployment (IaC, Docker, Kubernetes), observability, testing, and internal tooling. Improve retrieval accuracy and latency, document reusable abstractions, and collaborate closely with strategists to deliver client-facing AI solutions.

Lead full-cycle recruiting for the U.S. and Colombia/Argentina markets with an outbound-first approach. Own ATS (Gem), optimize AI recruiting tools, run multi-channel sourcing campaigns, manage pipeline metrics and hiring strategy, and partner with hiring managers to fill technical roles rapidly and with high quality.

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.

Own the technical architecture and reusable component catalog underlying Cadre AI’s productized client solutions. Decompose engagements into configurable modules, establish taxonomy and versioning standards, prioritize productization based on reuse economics and margin, and provide final technical scope approval during pre-sales. Work hands-on in code with engineering to define abstraction boundaries, build AI application components, and prevent unnecessary bespoke development. Initially an individual contributor, the role grows into technical team leadership.

Lead and mentor a San Diego engineering team while staying hands-on building production LLM systems (RAG, agents, document processing). Drive architecture, evaluate models and tooling, own end-to-end delivery, collaborate with clients, and create reusable internal tooling and best practices to improve team performance and client outcomes.

Lead end-to-end AI strategy engagements: run discovery, design AI roadmaps, facilitate executive workshops, produce executive-grade deliverables, and convert projects into long-term retainers while managing scope, timelines, and client relationships.

Lead and grow a Colombia-based AI engineering team (3-5 engineers), own delivery across multiple client engagements, set technical architecture and standards, stay hands-on for high-stakes builds (agents, multi-step pipelines, integrations), partner on engineering strategy, and represent the team with clients and internal stakeholders to ensure quality, timely delivery, and scalable production AI systems.

Lead and mentor the Colombia engineering team while remaining hands-on building production LLM systems: agentic workflows, RAG/document pipelines, extraction, APIs, data pipelines, and cloud infrastructure. Drive architecture and technical direction, ship reliable production systems, evaluate models and tools, create reusable tooling, and represent technical decisions to clients. Own delivery outcomes and engineer growth.

Embed with clients to discover high-impact AI opportunities, design and build production LLM/RAG/agent systems, deploy secure cloud services, create evaluation and observability tooling, and scale repeatable playbooks while managing client relationships and mentoring junior engineers.