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Akshay Wakhare

@akshaywakhare

I build AI-powered search, automation, and scalable backend platforms.

India
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What I'm looking for

I'm looking to build high-impact AI and backend products, especially systems that automate complex workflows, improve search and customer experiences, and scale reliably in production.

At Prodigal, I build autonomous LLM products that turn incoming emails into intent-aware Databricks queries and human-readable summaries. I also created AI-driven QA workflows that automate transcript-based scorecards and collections call summaries.

Previously at Amazon, I improved Amazon.in ad-ranking logic with an INR 15 Cr revenue impact and built a bank-partner simulator and self-guided API wizard that saved more than 85 SDE weeks annually. I also architected an organization-wide serverless third-party data ingestion framework that eliminated 48 weeks of manual refresh work each year.

I've built secure partner-access systems, led zero-downtime AWS infrastructure migrations, and mentored interns and new hires while conducting 25+ technical interviews.

My earlier experience at HERE Technologies and Goldman Sachs includes Kubernetes deployments, Redis-based performance improvements, and digitizing account onboarding from seven days to 30 minutes. I work across Java, TypeScript, Python, SQL, AWS, distributed systems, and LLM-powered applications.

Experience

Work history, roles, and key accomplishments

Prodigal logoPR
Current

Product Engineer

Mar 2026 - Present (5 months)

Engineered an autonomous LLM Agent for email query processing and routing, and spearheaded an AI-driven QA tool for automated agent scorecard completion. Designed a natural-language search feature and re-engineered background task processing using Celery and Redis.

Education

Degrees, certifications, and relevant coursework

Birla Institute of Technology and Science, Pilani logoBP

Birla Institute of Technology and Science, Pilani

Bachelor of Engineering, Computer Science

2019 - 2023

Grade: 8.45/10

Pursued a Bachelor of Engineering in Computer Science with a minor in Finance, achieving a CGPA of 8.45/10.

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