CADDi
Bleeding Edge Ai Engineer
You will be on the bleeding edge of AI, helping transform manufacturers and innovating as you go. Not only will you be helping customers, but you will be the chief pathfinder for our product and technology teams as you discover repeatable solutions for US manufacturers. Own solution architecture and delivery end-to-end: from discovery and scoping to POC, testing, and handover. Code and ship integrations in Python/TypeScript/Rust, build APIs and integrations, and stand up data pipelines. Partner cross-functionally with Sales (technical scoping, demos), Product (field feedback and reusability), and Customer teams (enablement and runbooks). Write clear technical documents: architecture diagrams, SOW estimates, test plans, and ops runbooks. 0?1 focus: move from first customer conversation to production quickly; create reusable accelerators for later 1?N scale. This is not a coordination/program role. Hands-on development: design, prototype, and build data/AI features and integrations; write services and orchestration code. Customer discovery and value engineering: elicit requirements, map data sources, define measurable success criteria. Solution demos and technical workshops: iterate quickly on POCs to prove value. Productionize: harden data flows, instrument logging/metrics, add tests, security controls, and deployment pipelines. Pre-sales technical support: shape SOWs, right-size scope and estimates, and de-risk delivery.
You will be on the bleeding edge of AI, helping transform manufacturers and innovating as you go. Not only will you be helping customers, but you will be the chief pathfinder for our product and technology teams as you discover repeatable solutions for US manufacturers. Own solution architecture and delivery end-to-end: from discovery and scoping to POC, testing, and handover. Code and ship integrations in Python/TypeScript/Rust, build APIs and integrations, and stand up data pipelines. Partner cross-functionally with Sales (technical scoping, demos), Product (field feedback and reusability), and Customer teams (enablement and runbooks). Write clear technical documents: architecture diagrams, SOW estimates, test plans, and ops runbooks. 0?1 focus: move from first customer conversation to production quickly; create reusable accelerators for later 1?N scale. This is not a coordination/program role. Hands-on development: design, prototype, and build data/AI features and integrations; write services and orchestration code. Customer discovery and value engineering: elicit requirements, map data sources, define measurable success criteria. Solution demos and technical workshops: iterate quickly on POCs to prove value. Productionize: harden data flows, instrument logging/metrics, add tests, security controls, and deployment pipelines. Pre-sales technical support: shape SOWs, right-size scope and estimates, and de-risk delivery.