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Garv Goyal
Intern software engineer specializing in AI systems and full-stack development
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Full-stack/product-minded engineer with a strong infrastructure foundation who has built both cloud automation systems and an AI voice interview coach. Stands out for combining hands-on coding with pragmatic product thinking: they improved user trust through scorecard redesign, built resilient speech handling around flaky browser APIs, and delivered measurable backend performance gains during startup internships.
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Key Strengths
- Infrastructure-as-code automation for cloud networking
- Designed safe deployment and rollback logic for Azure network changes
- Built end-to-end AI voice interview product from onboarding to feedback
- Strong React/TypeScript and Node.js full-stack implementation
- Pragmatic API design; chose REST over GraphQL based on product needs
- Defensive engineering around unreliable browser speech APIs
- User-driven product iteration based on early feedback
- Turned opaque AI scores into actionable multi-dimension scorecards
- Proactive builder mentality in ambiguous startup environments
- Performance optimization with measurable impact
- Reduced FastAPI response time from 8 seconds to 4.5 seconds
- Improved deployment reliability and reduced memory footprint by 22%
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“Software engineer at Fannie Mae (~3 years) working on high-volume loan data pipelines using AWS (SQS/S3), Java listeners, Postgres, and Python/SQL-based data quality validation. Also built a chess data collection system (leveraging experience as an International Master) with robust retry/monitoring, schema-change handling, and idempotent backfills to prevent bad data from reaching downstream systems.”
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