The IEEE WIE Distinguished Volunteer and Mentor series highlights a dedicated WIE volunteer who is well known for their notable contributions to IEEE WIE.

In this issue, we feature Purvi Joshi, 2026 IEEE WIE Global Tech Marathon Lead and Data Engineering Manager at AWS

IEEE WIE: How has your experience with IEEE WIE shaped your career and personal growth?

Joshi: “Leadership and Career: Organizing the Global AI Tech Marathon gave me the opportunity to influence and lead folks beyond my own work organization. This strengthened my professional profile and experience.
Mentorship: Teaching AI prompt engineering to a global audience of eager learners felt like a genuine act of giving back to society, democratizing access to AI skills.
Community: Partnering with WIE grew my network and passion for inclusion.”

IEEE WIE: What innovative projects or initiatives are you currently working on that you believe will make a significant impact?

Joshi: “Global AI Tech Marathon (IEEE WIE partnership) — I hold a leading, critical role architecting a multi-session initiative delivering AI prompt engineering for SQL, JavaScript, Bash, and Python training globally. With 112 registrations, the marathon spans the USA and IEEE Region 10 — from South Korea and Japan to New Zealand, and India and Pakistan — across 60+ sections including Australia, China, Singapore, Malaysia, the Philippines, Vietnam, Indonesia, and Bangladesh.”

IEEE WIE: Can you share a moment when you overcame a significant challenge in your professional journey and what you learned from it?

Joshi: “Challenge: Launching the Global AI Tech Marathon meant coordinating volunteers, judging criteria, and planning for continuous engagement of 112 participants across the USA and IEEE Region 10, spanning time zones from Japan to New Zealand to Pakistan — with no existing playbook to follow.

  • What I did: I designed the entire evaluation infrastructure myself — tiered SQL/Python challenges, an 8-criteria scoring rubric, and interactive scoreboards — then trained volunteers to apply it consistently across sessions, cultures, and skill levels.
  • What I learned: Leading at scale means building, not just doing the work — creating a framework others can execute reliably without me present for every decision.
    Lasting impact: This now serves as the operating model for future marathon cycles – extending my influence beyond a single event.”

IEEE WIE: How do you stay updated with the latest trends and advancements in your field?

Joshi: “Staying current in a fast-moving field:

  • Active research engagement: Co-authoring and presenting an IEEE paper on RAG systems at TIC-2026 keeps me grounded in cutting-edge AI research. I review journal publications which helps me learn of new advancements.
  • Teaching as learning: Building AI prompt engineering and SQL/Python content for the Global AI Tech Marathon forces me to deeply understand concepts well enough to explain them to beginners — which sharpens my own grasp. At AWS I continue to up skill my team with new AI advancements and improve developer efficiency.
  • Community immersion: Participating in WiDS Puget Sound and IEEE WiE events exposes me to diverse perspectives and emerging applications across industries, beyond my day-to-day work.
    Applied practice: Tech Consulting work with Startups such as StocksDojo lets me test AI/data techniques in real-world business contexts, bridging theory and practice.”

IEEE WIE: What role do you think mentorship plays in the success of young professionals, and how do you approach mentoring others?

Joshi: “”Mentorship bridges raw potential and realized success. Young professionals often have strong technical skills but lack guidance to navigate organizations and translate work into visible impact.
My approach:

  • Teach through building: I create structured challenges and evaluation frameworks for the Global AI Tech Marathon, so mentees learn by doing — reflecting my critical role in program design.
  • Turn work into narrative: I coach mentees to document impact continuously, translating accomplishments into data-backed stories leadership can act on.
  • Lead beyond my organization: I guide people well outside my immediate team or company, believing mentorship shouldn’t be bound by organizational lines.”