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Pranav Zagade
Junior Software Engineer specializing in full-stack and AI systems
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About
Built and shipped an LLM-powered support agent for Community Dreams Foundation that automated intake and Jira ticket creation using RAG, structured outputs, and strong production guardrails. Demonstrated practical production AI experience with 92% routing accuracy, 98% uptime, and a 31% improvement in first-response accuracy, plus hands-on work in observability, evals, idempotency, and failure handling.
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Key Strengths
- Shipped LLM support agent to production
- Automated support intake, classification, and Jira ticket routing
- 92% routing accuracy
- 98% uptime in production
- Improved first-response accuracy by 31%
- Strong guardrails for predictable agent behavior
- Designed multi-step agent workflows with tool calling and structured outputs
- Built evaluation, monitoring, and feedback loops for production agents
- Solved duplicate ticket creation with idempotency and deduplication
- Handled messy operational data with validation layers and safe fallbacks
- Refactored fragile SQL-based analytics pipeline into staged, validated workflows to improve reliability and debuggability
- Uses incremental rollout strategies (parallel pipeline runs, result comparisons) to manage migration risk and preserve data integrity
- API reliability practices in FastAPI (Pydantic validation, clear separation of layers, explicit error handling/status codes)
- Security implementation experience (JWT auth, role-based permissions, row-level security)
- Identifies and mitigates silent data pipeline failure modes via validation gates to prevent bad data propagation
- Reduced backend module size ~80% through incremental refactoring, improving maintainability and reliability
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