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Aashna Kunkolienker
Junior AI Engineer specializing in agentic workflows and ML platforms
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About
Building a production LLM/agent system for a leading US dental provider that extracts rules from payer handbooks/portals and EDI 271 responses to validate and improve patient cost estimates. Combines GCP stack (BigQuery, GKE, Cloud Run, Pub/Sub, Vertex AI) with strong agent reliability practices (observability, validator agents, grounding, PII/hallucination guardrails, confidence scoring) and has led non-technical customer stakeholders on enterprise ServiceNow↔Aha sync and AI-powered enterprise search/summarization.
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Key Strengths
- Built production LLM system to extract rules and validate dental procedure cost estimates using multiple payer data sources
- Strong focus on reliability: validator agents, observability, grounding, PII/hallucination guardrails, and confidence scoring with manual-review flagging
- Pragmatic solution design via constraints-first approach (latency/compute/error tolerance; agent vs traditional solution decisioning)
- Experience scaling containerized AI services on GKE with autoscaling and CI/CD
- Designed and delivered enterprise data ingestion/sync pipelines (full + incremental) integrating ServiceNow and Aha!
- Led customer calls and translated technical architecture to non-technical stakeholders
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