Embedded AI Engineer

Required Skills & Experience

1 to 3 years of experience in software engineering, automation, data, analytics, or applied AI. \n\nHands-on experience building AI agents, RAG applications, copilots, or AI-powered automations. \n\nStrong Python skills and working knowledge of SQL. \n\nAbility to embed within a business function, learn its operations, and serve as its dedicated AI resource. \n\nExperience gathering requirements from business users and translating their needs into deployable solutions. \n\nAbility to own projects from discovery through development, testing, deployment, and adoption. \n\nStrong communication skills with technical and non-technical stakeholders.

Nice to Have Skills & Experience

Azure, Snowflake, or other cloud and data platform experience. \n\nExperience training users and driving adoption of AI tools. \n\nPersonal AI projects demonstrating meaningful hands-on development. \n\nTelecommunications, broadband, fiber, or infrastructure experience. \n\nConstruction opening: Experience with construction operations, project scheduling, field operations, permitting, forecasting, GIS, or reporting. \n\nSupply Chain, Administrative Services & Legal opening: Experience with procurement, inventory, logistics, vendor management, administrative workflows, contracts, or document processing.

Job Description

Job Overview \n\nThe Embedded AI Engineer will serve as the dedicated AI partner for an assigned business vertical. This person will work directly alongside business users to learn their operations, identify opportunities, and build practical AI solutions tailored to their workflows. \n\nThis is not a pure AI/LLM/NLP engineering role. It requires a hands-on builder who can embed within a non-technical team, earn stakeholder trust, and develop AI agents, RAG applications, copilots, and workflow automations from concept through deployment. The role will begin with an approximately 50/50 balance between stakeholder engagement and development before shifting toward 75% hands-on building. \n\n \n\nDay to Day \n\nEmbed within the assigned vertical and learn its workflows, systems, challenges, and priorities. \n\nBuild relationships with business users and identify high-value AI and automation opportunities. \n\nDevelop and deploy AI agents, RAG solutions, copilots, prompts, and workflow automations. \n\nOwn solutions from initial discovery through testing, deployment, and ongoing improvement. \n\nTrain users on delivered solutions and support broader AI adoption. \n\nGather feedback and measure the effectiveness of deployed tools. \n\nPartner with central AI and data teams while maintaining ownership of solutions for the assigned vertical.