Bharadwaja Thota

About

Full-stack and AI product engineer focused on data instrumentation and tracking-plan automation. They built an end-to-end publish architecture plus an MCP/agent workflow that turns PRDs, Figma files, and meeting transcripts into tracking plans and implementation-ready code, reportedly shrinking work from 4-5 days to minutes. They also show strong judgment around productionizing LLM systems, with tool-centric prompt design, backend guardrails, and human-in-the-loop controls for high-risk actions.

Key Strengths

• Owned end-to-end full-stack publish flow for tracking plans
• Strong frontend architecture for complex async UX
• Designed async job-based backend APIs for long-running workflows
• Deep TypeScript and GraphQL/Apollo implementation experience
• Built AI-powered tracking plan generation and review workflows
• Developed MCP server exposing backend capabilities as agent tools
• Advanced prompt engineering via tool descriptions and schemas
• Built agentic systems with 22 tools and LangGraph ReAct loops
• Practical LLM reliability focus with normalized errors and low-temperature controls
• Production monitoring using Splunk dashboards and failure tracing
• Improved system safety by moving UI validation gates into backend service
• Strong judgment on AI automation vs human-in-the-loop for high-blast-radius actions
• Initiated and shipped a net-new MCP platform in an ambiguous environment
• Delivered major workflow compression from 4-5 days to ~5-10 minutes
• Contributed to team recognition: 2nd out of 50 teams in org

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