2025 - NOW

AI & Data Engineering

AAA / United States

Work across production AI workflows spanning backend APIs, asynchronous processing, retrieval, persistent data systems, evaluation and observability.

  • Translate ambiguous AI workflows into measurable engineering systems.
  • Build within production AI, retrieval, evaluation, asynchronous workflow, and data-system boundaries without exposing confidential implementation details.
  • Production AI
  • Evaluation
  • Retrieval
  • Async Processing
  • Data Systems

Previous

Data Engineering and Product Analytics

AdaIQ

Data engineering and product analytics work focused on turning product behavior into usable signals.

  • Structured product and operational data for analysis.
  • Connected analytics work to practical product questions.
  • Data Engineering
  • Product Analytics

Academic

Data Analytics Engineering

Northeastern

Graduate-level data analytics engineering foundation across data systems, analysis, and applied engineering workflows.

  • Built foundations across data analysis, data systems, and engineering methods.
  • Connected analytical reasoning to implementation-focused project work.
  • Data Analytics
  • Engineering Systems

Earlier

Enterprise Engineering and Data Systems

Cognizant

Enterprise engineering and data systems experience in structured delivery environments.

  • Worked within enterprise software delivery constraints.
  • Built practical grounding in maintainable engineering systems.
  • Enterprise Engineering
  • Data Systems