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Akash Shanmuganathan
Mid-level GenAI & Data Engineer specializing in agentic AI systems and AWS Bedrock
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At onedata, built and deployed an LLM-powered, multi-agent analytics platform on AWS Bedrock that lets users create Amazon QuickSight dashboards through natural-language conversation, cutting dashboard build time from ~30 minutes to ~5 minutes. Strong in production concerns (observability, token/cost tracking, model tradeoffs) and in bridging business + technical work, owning pre-sales pitching through delivery with an engineering management background focused on AI product management.
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Key Strengths
- Built and deployed LLM-powered analytics platform enabling natural-language QuickSight dashboard creation
- Reduced dashboard creation time from ~30 minutes to ~5 minutes via conversational workflow
- Hands-free conversational AI implementation; adapted architecture from WebRTC to Socket.IO and back as production readiness changed
- Cost optimization through model selection (switched from Claude to Amazon-native models) while maintaining accuracy via multi-agent design
- Production-grade observability: AgentCore tracker, CloudWatch, and custom metrics with a monitoring dashboard
- End-to-end delivery from pre-sales discovery and pitching through production build; pitched 4 ideas with 2 moving forward
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