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Akshara Bhukya
Mid-level AI/ML Engineer specializing in Generative AI and RAG systems
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About
LLM/RAG engineer who has built and shipped production assistants, including a RAG-based teaching assistant (Marvel AI) using LangChain/LlamaIndex/ChromaDB with OpenAI embeddings and Redis vector search, achieving ~30% accuracy gains and ~35% latency reduction. Also deployed FastAPI services on Google Cloud Run with observability and prompt-level monitoring, and partnered with non-technical ops stakeholders to deliver an internal policy-document RAG assistant.
Experience
Education
Key Strengths
- Built and deployed production RAG teaching assistant (Marvel AI) end-to-end
- Improved answer accuracy ~30% via retrieval enhancements (chunking + knowledge-graph signals + vector search tuning)
- Reduced response latency ~35% through embedding optimization and vector-layer caching
- Production deployment on FastAPI + Google Cloud Run with observability (Cloud Log Explorer) and prompt monitoring (LangSmith)
- Strong approach to agent/workflow evaluation with explicit metrics (accuracy, latency, hallucination rate) and iterative testing
- Hands-on container orchestration for AI services (Docker, Kubernetes) including scaling and rolling updates
- Effective collaboration with non-technical stakeholders using demos and feedback loops to shape retrieval pipeline
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