Description
Forward Deployment Engineer (Embedded AI / Systems Engineer)R&DWhy Join Us?Join the founding U.S. deployment team and embed directly with strategic enterprise clients. Bridge technology and business by architecting, coding, and operationalizing AI solutions in real-world production settings while shaping product direction from the field.Key ResponsibilitiesEmbed with customer teams (on-site or virtually), rapidly understand domain challenges, and design tailored AI/ML-driven solutionsLead end-to-end implementation: data ingestion, model integration, application logic, UI/UX, APIs, monitoring, and scalingCollaborate with customer stakeholders (technical and executive) to define roadmap, success metrics, and delivery plansIterate rapidly: prototype, test, learn, and refine in production settingsSurface lessons from client deployments back into our core platform—help shape product direction, SDKs, abstractions, and APIsAssist the sales / pre‑sales process: technical discovery, architecture reviews, proof‑of‑concept scoping, and proposalsEnsure reliability, observability, performance, security, and compliance in deployed systemsRequirements3–8+ years of professional software engineering experience (full stack, data, infrastructure, or ML systems)Experience building production systems: APIs, data pipelines, scalable services, frontend/backendsDemonstrated ability to work in ambiguous environments, integrating multiple systems and APIsExcellent communication skills: able to engage both engineers and non‑technical stakeholdersHighly autonomous, creative problem solver, comfortable working across layers (data ↔ app ↔ infra)Willingness to travel (20%–40%) to customer sitesPreferred QualificationsExperience in AI/ML, knowledge graphs, embeddings, LLMs, vector databasesBackground in regulated industries (finance, healthcare, government)#J-18808-Ljbffr
Description
Forward Deployment Engineer (Embedded AI / Systems Engineer)R&DWhy Join Us?Join the founding U.S. deployment team and embed directly with strategic enterprise clients. Bridge technology and business by architecting, coding, and operationalizing AI solutions in real-world production settings while shaping product direction from the field.Key ResponsibilitiesEmbed with customer teams (on-site or virtually), rapidly understand domain challenges, and design tailored AI/ML-driven solutionsLead end-to-end implementation: data ingestion, model integration, application logic, UI/UX, APIs, monitoring, and scalingCollaborate with customer stakeholders (technical and executive) to define roadmap, success metrics, and delivery plansIterate rapidly: prototype, test, learn, and refine in production settingsSurface lessons from client deployments back into our core platform—help shape product direction, SDKs, abstractions, and APIsAssist the sales / pre‑sales process: technical discovery, architecture reviews, proof‑of‑concept scoping, and proposalsEnsure reliability, observability, performance, security, and compliance in deployed systemsRequirements3–8+ years of professional software engineering experience (full stack, data, infrastructure, or ML systems)Experience building production systems: APIs, data pipelines, scalable services, frontend/backendsDemonstrated ability to work in ambiguous environments, integrating multiple systems and APIsExcellent communication skills: able to engage both engineers and non‑technical stakeholdersHighly autonomous, creative problem solver, comfortable working across layers (data ↔ app ↔ infra)Willingness to travel (20%–40%) to customer sitesPreferred QualificationsExperience in AI/ML, knowledge graphs, embeddings, LLMs, vector databasesBackground in regulated industries (finance, healthcare, government)#J-18808-Ljbffr
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