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Sai Byrraju
Entry-Level Software Engineer specializing in full-stack and AI platforms
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About
Built an AI-based voice interviewer platform at 7C Lingo to automate early-stage candidate screening, owning the full lifecycle from architecture through deployment and weekly production iterations. Implemented a TypeScript/Next.js recruiter dashboard with a Flask/Postgres backend and AWS S3, plus modular services for transcription/analytics/session management using state-driven async workflows. Also created an internal Whisper-powered transcription and editing tool that evolved into a collaborative, versioned, live-transcription system.
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Key Strengths
- Owned and shipped an AI voice interviewer platform end-to-end (architecture, full-stack build, deployment, iteration)
- Rapid MVP delivery (~2 months) with weekly production iterations based on user feedback
- Strong judgment balancing quality vs speed (candidate experience, data integrity, trust as non-negotiables)
- Designed scalable architecture for data-heavy recruiter dashboards using SSR to reduce client-side fetch complexity
- Built internal transcription/editing tool that replaced manual workflows; iterated to add diarization, autosave, collaboration, and live transcription
- Effective stakeholder alignment in ambiguous environments by framing priorities around impact and risk
- End-to-end ownership (backend + frontend) of an AI interviewer platform
- Designed scalable backend architecture (Flask monolith with PostgreSQL/Supabase) and built dashboard/session REST APIs
- Handled large-file and long-running transcription workloads by staging uploads in cloud storage before Cloud Run processing
- Containerized and deployed Python services to Kubernetes; split workloads into multiple services/pods (processing, API, live transcription)
- Implemented CI with GitHub Actions/GitLab CI to build/test Docker images and push versioned images to registries (e.g., ECR)
- Planned and executed an incremental migration running old/new systems in parallel with monitoring of error rates and latency
- Practical GitOps workflow: PR-based infra/config changes with automated promotion to environments
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