About the job
The Rapid & Rural Logistics (R2L) team is hiring a Sr. Business Intelligence Engineer to own our Conversational and Agentic AI roadmap. In this role, you will design and deploy LLM-powered agents and natural language interfaces that enable operators and business stakeholders to interact with data and trigger automated workflows in real time. You will be the technical expert building intelligent systems that don't just surface smart insights, but take action across R2L's fast-moving logistics ecosystem.
Responsibilities
- Own the end-to-end design, development, and deployment of conversational AI interfaces and agentic AI systems that serve R2L's operational and analytical needs
- Build and maintain LLM-powered agents capable of reasoning over structured and unstructured data, executing multi-step tasks, and integrating with internal tools and APIs
- Develop natural language querying capabilities that democratize data access across all levels of the organization — from frontline ops to senior leadership
- Architect agentic workflows for operational use cases such as automated XBR commentary generation, anomaly detection and escalation, route optimization insights, and delivery performance monitoring
- Partner with data engineers and scientists to ensure agents are grounded in reliable, high-quality data pipelines
- Define evaluation frameworks and guardrails to ensure AI agent outputs are accurate, safe, and trustworthy
- Collaborate with cross-functional stakeholders to identify automation opportunities and translate ambiguous business problems into scalable AI solutions
- Stay current on advancements in LLMs, agent frameworks (e.g., ReAct, tool-use, multi-agent orchestration), and retrieval-augmented generation (RAG) to continuously improve our AI capabilities
Qualifications
Minimum
1. 10+ years of professional or military experience
2. 5+ years of SQL experience
3. 1+ years of SQL, ETL or Oracle experience
4. 1+ years of processing large, multi-dimensional datasets from multiple sources experience
5. 1+ years of performing statistical analysis experience
6. 1+ years of developing automated reporting experience
7. Experience programming to extract, transform and clean large (multi-TB) data sets
8. Experience with theory and practice of design of experiments and statistical analysis of results
9. Experience with AWS technologies
10. Experience in scripting for automation (e.g. Python) and advanced SQL skills.
11. Experience with theory and practice of information retrieval, data science, machine learning and data mining
Preferred
- Experience working directly with business stakeholders to translate between data and business needs
- Experience managing, analyzing and communicating results to senior leadership