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Shiva Adusumilli
Mid-level Software Engineer specializing in AI agents, backend systems, and data engineering
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About
Amazon engineer who built a production AI agent platform (Python/AWS Strands on Bedrock) that lets teams create tool-using, multi-agent workflows—e.g., agents that auto-triage and resolve customer support tickets by reading internal documentation and collaborating with a research agent. Previously worked in Deloitte on IAM using Ping Identity/Ping DaVinci orchestration, and applies orchestration thinking plus structured evaluation (LLM-as-judge, surveys, automated tests) to improve agent reliability.
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Key Strengths
- Built and deployed an internal AI agent platform enabling other teams to create and run agents
- Implemented multi-agent (agent-to-agent) collaboration patterns for complex workflows (e.g., research agent supporting ticket-resolution agent)
- Integrated MCP/tooling so agents can invoke third-party tools via a standardized protocol
- Pragmatic model selection based on cost, latency, and token limits (used Claude 3.7 for 200k context needs)
- Designed reusable system-prompt templates to standardize agent behavior
- Established evaluation loops combining LLM-based scoring, manual team surveys, and automated scenario testing
- Strong stakeholder collaboration to define realistic question sets and validate performance on real customer tickets
- Identified limitations of SOP/runbook-only approaches and shifted to more adaptive, evidence-driven ticket understanding (logs/docs synthesis)
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