AI Software Engineering and Business Intelligence Instructor

Position: AI Software Engineering and Business Intelligence Instructor

Location: Remote

Reports To: Director, Alumni Technical Training

WHO WE’RE LOOKING FOR

Per Scholas seeks an AI Instructor who blends hands-on teaching with real-world AI solution building. You’re fluent in modern LLM stacks (prompting, RAG, agentic tools, multimodal), comfortable shipping demo-to-production apps (APIs, UIs, logging, guardrails), and equally at home in analytics engineering (SQL, Power Query, DAX, Power BI Service). You coach diverse adult learners with empathy, create inclusive classrooms, and turn complex topics into practical, job-ready skills. Bonus points for experience across AI Solutions Development, AI-Native Business Intelligence, and emerging tracks like AI Data Engineering, plus cloud familiarity (Azure/AWS), Git/GitHub workflows, and basic MLOps hygiene.

WHAT YOU’LL DO

• Lead engaging, lab-first instruction on LLMs, prompt engineering, RAG, agentic AI, and multimodal apps; guide learners to build working CLI/API/UI deliverables.
• Teach analytics engineering: SQL for reporting, Power Query for shaping, semantic modeling and DAX, and deployment to Power BI Service with refresh and security.
• Mentor capstones and portfolios end-to-end, from scoping and data sourcing to evaluation, guardrails, observability, and stakeholder-ready demos.
• Serve as AI subject-matter expert: advise on curriculum, align content to market demand and certifications (e.g., PL-300), and track emerging tools and patterns.
• Coach fellow instructors on AI-native teaching practices and classroom use of copilots while modeling ethical and responsible AI use.
• Provide timely feedback, office hours, and career coaching that translate projects into employer-ready narratives.
• Collaborate with staff to continuously improve labs, rubrics, and outcomes; uphold inclusive, high-expectation learning environments and program policies.

WHAT YOU’LL BRING TO US

Technical Expertise

• Build end-to-end AI applications that compose LLM prompting, Retrieval-Augmented Generation (RAG), agentic tool/function calling, multimodality (OCR to text), and basic evaluation/guardrails for production-minded delivery.
• Orchestrate LLM workflows with function/tool schemas, conversational memory, validation, moderation, and retry/timeout patterns; analyze traces and metrics to improve reliability.
• Design and tune retrieval pipelines: ingest, chunk, embed, index, and retrieve with citations; optimize chunk size, overlap, and top-k for accuracy; measure grounding and hallucination rates.
• Ship demo-to-production artifacts with clear READMEs: deliver CLI/API/UI, package code with configs and tests, and use reproducible environments, logs, and metrics for stakeholder-ready reporting.
• Python 3.10+ and ecosystem: LangChain, vector stores (Chroma; Pinecone preferred), FastAPI/Streamlit, pytest, Git/GitHub; model SDKs (OpenAI, Anthropic); OCR with Tesseract; local runtimes (e.g., Ollama).
• Data modeling and warehousing: Design star and snowflake schemas, conformed dimensions, SCD types, surrogate keys; apply Kimball-style dimensional modeling for analytics.
• Transformation and orchestration: Use dbt for modular SQL transforms, tests, and docs; schedule and monitor pipelines with Airflow or Prefect; implement lineage and SLAs.
•  Distributed processing: Use Spark/PySpark and Delta Lake/Iceberg for large-scale processing, optimizing joins, partitions, and file sizes.
• Streaming and CDC: Ingest event data via Kafka/Kinesis/Pub/Sub and Debezium; handle schemas with a registry; implement windowed aggregations and exactly-once patterns.
• DevOps for data: Ship pipelines with Git/GitHub CI/CD (GitHub Actions), Docker containers, and Terraform for infrastructure; manage secrets and environment promotion.
• Security and compliance: Implement IAM/RBAC, row and column-level security, encryption at rest and in transit, key management, and controls aligned to HIPAA and GDPR.
• Power BI analytics engineering: prepare data with Power Query; model governed semantic layers with relationships and DAX; publish to Service with scheduled/incremental refresh and workspace management; secure access via Row-Level Security.
• SQL for reporting and transformation plus Excel for analysis; craft KPI-driven, stakeholder-ready dashboards and narratives aligned to PL-300 expectations.
• Python data analysis stack (pandas, NumPy) for EDA, cleansing, and basic stats/regression to support BI and AI solution builds.
• Version control and reproducible workflows for analytics and code (Git/GitHub), including environment management.

 

Instructional Skills

• 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.

Professional & Personal Qualities

• 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.

Compensation 

For this role specifically, we are targeting a salary range of $80,000 - $85,000 where the difference in salary is typically determined by several factors, including geography in which the selected candidate resides, and alignment with qualifications and experience.

 

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