AI Software Engineering and Business Intelligence Instructor

Build end-to-end AI applications with LLM prompting, RAG, agentic tools, and multimodality. Orchestrate LLM workflows with function schemas, conversational memory, and error handling. Design and tune retrieval pipelines for ingestion, embedding, and retrieval. Ship demo-to-production artifacts with clear READMEs. Proficiency in Python 3.10+ and ecosystem (LangChain, vector stores, FastAPI/Streamlit, pytest, Git/GitHub). Data modeling and warehousing experience (star/snowflake schemas, dimensional modeling). Transformation and orchestration skills (dbt, Airflow/Prefect). Distributed processing knowledge (Spark/PySpark). Streaming and CDC experience (Kafka/Kinesis, Debezium). DevOps for data skills (Git/GitHub CI/CD, Docker, Terraform). Security and compliance implementation (IAM/RBAC, encryption, HIPAA/GDPR). Power BI analytics engineering (Power Query, DAX, Power BI Service, RLS). SQL for reporting and transformation, Excel for analysis. Python data analysis stack (pandas, NumPy). Version control and reproducible workflows (Git/GitHub). 1-3+ years teaching, mentoring, or training in technical subjects. Ability to clearly communicate complex AI concepts to diverse learners. Experience guiding learners through portfolio projects or capstones. Bachelor’s degree in Computer Science, AI, Software Engineering, or equivalent experience. 3+ years of professional experience in AI/ML or software engineering.

Lead instruction on LLMs, prompt engineering, RAG, agentic AI, and multimodal apps. Teach analytics engineering including SQL, Power Query, DAX, and Power BI Service. Mentor capstones and portfolios from scoping to demos. Serve as AI subject-matter expert and advise on curriculum. Coach fellow instructors on AI-native teaching practices. Provide feedback, office hours, and career coaching. Collaborate to improve labs, rubrics, and outcomes.