AI Software Engineering and Business Intelligence Instructor

Build end-to-end AI applications using LLM prompting, RAG, agentic tools, and multimodality. Orchestrate LLM workflows with function/tool schemas, conversational memory, and error handling. Design and tune retrieval pipelines for accuracy and citation. Ship demo-to-production artifacts with clear READMEs, reproducible environments, logs, and metrics. Proficiency in Python 3.10+ and ecosystem: LangChain, vector stores, FastAPI/Streamlit, pytest, Git/GitHub. Data modeling and warehousing expertise: star/snowflake schemas, dimensional modeling. Experience with transformation and orchestration tools like dbt and Airflow/Prefect. Familiarity with distributed processing using Spark/PySpark and Delta Lake/Iceberg. Experience with streaming and CDC via Kafka/Kinesis/Pub/Sub and Debezium. DevOps for data: Git/GitHub CI/CD, Docker, Terraform. Knowledge of security and compliance: IAM/RBAC, encryption, HIPAA/GDPR. Power BI analytics engineering: data preparation, semantic modeling with DAX, Power BI Service deployment, 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 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. Passion for teaching and creating pathways for underrepresented communities in tech. Collaborative, detail-oriented, and growth-minded with strong mentoring and interpersonal skills.

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