Kunal Shahi
@kunalshahi
I build governed multi-agent analytics systems, typed data layers, and durable AI infrastructure.
IndiaWhat I'm looking for
At Gobblecube.ai, I build Intelligent Analyst, a multi-agent system that plans business analysis and delivers chat answers, SQL-backed insights, or HTML reports. I helped make analytics safer through typed Measure and Dimension queries over semantic cubes, so raw SQL is never LLM-written.
I also build the platform behind production AI: Temporal-based durable execution, semantic caching, layered agent memory, evaluation workflows, and AWS Bedrock governance. Previously, I developed entity-linkage pipelines at Tresata.ai, Simulink automation at Jaguar Land Rover, and ML-based stock forecasting at UNSW.
Experience
Work history, roles, and key accomplishments
Applied AI Engineer
Gobblecube.ai
Mar 2025 - Present (1 year 6 months)
Built a multi-agent Intelligent Analyst for conversational analytics and autonomous reporting, and co-built the MCP semantic-cube service Wardenclyffe. Implemented Temporal.io durable execution, semantic caching, and layered agent memory, and deployed the BiFrost LLM gateway for AI governance.
Data Science Intern
Tresata.ai
Jun 2024 - Oct 2024 (4 months)
Built a probabilistic entity-linkage pipeline using Word2Vec and Levenshtein-adjusted cosine similarity, and implemented the Fellegi-Sunter framework with MLE-estimated probabilities for scoring.
Developed Matlab/Simulink automation to standardize project scaffolding across EV vehicle programs, and integrated GitLab CI for automatic library-change propagation.
Built an ARIMA and seasonal-decomposition stock forecaster with ACF/PACF lag selection and FFT periodicity detection, and engineered technical indicators to improve directional accuracy.
Education
Degrees, certifications, and relevant coursework
Indian Institute of Technology, Delhi
B.Tech, Electrical Engineering
2020 - 2024
Grade: 8/10
Activities and societies: JEE Advanced AIR 107 (2020, 200K candidates) | KVPY Fellow (IISc, 2019) | Top 1% NSEP + NSEA (2019).
Pursued a B.Tech in Electrical Engineering, achieving a CGPA of 8/10.
University of New South Wales
Research Internship, Machine Learning and Finance
2022 - 2022
Completed an ML and Finance Research Internship, building an ARIMA-based stock forecaster and engineering technical indicators.
Availability
Location
IndiaAuthorized to work in
Salary expectations
Skills
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