Delta Faucet Company is seeking to transform everyday experiences with water through innovative products and exceptional service by building intelligent copilots that power decision-making across retail and ecommerce
Requirements
- Proficiency in Python and SQL with experience building APIs, workflows, or automation pipelines
- Hands-on experience in either Databricks Lakehouse (Delta Lake, Unity Catalog, Lakeflow Jobs, Model Serving, Vector Search) or Microsoft Copilot Studio and Power Platform (Power Automate, Power Apps, Dataverse, Graph connectors)
- Familiarity with LLMOps practices (e.g., MLflow, prompt evaluation, observability dashboards) and implementing responsible AI guardrails (data access controls, PII handling, bias mitigation)
- Demonstrated ability to ship at least one production-ready agentic or RAG (retrieval-augmented generation) solution, or equivalent evidence through open-source projects, internal pilots, or demos
- Experience with AI-driven agents, Databricks Lakehouse, and Microsoft Copilot ecosystem
- Knowledge of retail/consumer goods analytics and experience with data engineering, software engineering, or applied AI/ML
- Experience with cloud-based platforms and technologies such as Microsoft 365, Teams, Excel, Power BI
Responsibilities
- Design and deploy multi-agent workflows using Copilot Studio, LangChain, and Databricks Agent Bricks
- Implement retrieval-augmented generation (RAG) pipelines using Delta Lake, Unity Catalog, and Databricks Vector Search
- Build custom Copilot connectors and plugins (Graph APIs, Power Automate actions) to expose governed Delta data in Teams, Outlook, and Power BI
- Architect pipelines that connect transactional, inventory, and ERP feeds into real-time copilots with <2s response targets
- Orchestrate workflows across Microsoft Fabric, Dynamics 365, and Databricks Lakehouse (Bronze/Silver/Gold layers)
- Manage agent lifecycle using MLflow 3.0 for experiment tracking, prompt registry, evaluation, and tracing
- Enforce governance guardrails: Unity Catalog (row/column-level security, lineage, audit logging), Microsoft Purview (DLP, sensitivity labels), and responsible AI practices (guardrails, human-in-loop)
Other
- Bachelor's degree in Computer Science, Data Science, Engineering, or a related quantitative field
- 4-6 years of professional experience in software engineering, data engineering, or applied AI/ML
- Ability to work in a fast-paced environment and adapt to changing priorities
- Excellent communication and collaboration skills
- Ability to mentor and coach analytics peers
