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Mahima Mannava
Junior Software Engineer specializing in AI, LLM systems, and full-stack development
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About
AI/full-stack engineer who built a computer-usage agent end to end, including a split local/cloud architecture that used a vision LLM to drive real Chrome workflows while avoiding bot detection. Stands out for combining product-minded systems design, rigorous evals, and prompt iteration to achieve sub-2-second latency and a 20% reduction in automation failures in an early-stage environment.
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Key Strengths
- End-to-end ownership of AI/full-stack product features
- Designed split-execution browser automation architecture to bypass bot detection
- Improved automation reliability with 20% reduction in failure rate
- Built sub-2-second planning loop for AI-driven browser workflows
- Strong TypeScript API and async contract design
- Production-grade session isolation and retry handling
- Deep expertise in prompt iteration using production failure traces
- Built dual-mode RAG systems for speed and deep research use cases
- Implemented grounded structured-output pipelines with Pydantic
- Designed guardrails for low-confidence retrieval, PII detection, and hallucination prevention
- Strong evaluation mindset with session-level metrics and regression detection
- Created 300+ correctness tests for LLM behavior at Scale AI
- Thrives in ambiguous early-stage environments and sets process from first principles
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