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Mrudula Devaguptapu
Mid-level Software Engineer specializing in AI and backend systems
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AI/automation-focused implementation engineer who has owned customer-facing LLM deployments end-to-end, spanning support automation, lead outreach, and messy document-processing workflows. Stands out for combining hands-on technical depth in Python/OpenAI/RAG systems with measurable business impact, including cutting support resolution time from 24 hours to 6 hours and reducing manual outreach work by 60%.
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Key Strengths
- Owned end-to-end AI support automation deployment from discovery through post-launch stabilization
- Built LLM/RAG-based support workflows with confidence-based escalation to human agents
- Strong stakeholder management with regular demos, check-ins, and rollout documentation
- Improved help desk resolution time from 24 hours to 6 hours
- Increased AI response accuracy from 65% to 85%
- Designed production agentic workflow for lead outreach using function-calling and internal data grounding
- Reduced manual outreach effort from 24 hours/week to 8 hours/week
- Reduced deployment cycle for new automations from 5 days to 2 days through modular workflow design
- Debugged non-deterministic production AI issues across retrieval, indexing, prompts, and orchestration layers
- Implemented robust document-processing workflows for messy inputs using OCR, validation, and fallback/error handling
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