Avinash Amudala

• Built a production AI Test Automation platform converting telecom PRDs into executable regression plans using LLMs + hybrid retrieval (FAISS IVF + BM25 + reciprocal rank fusion), serving 4 internal engineering teams.
• Designed semantic search pipeline over 12K+ internal documents with FAISS HNSW indexing, achieving sub-200ms p95 query latency across the internal corpus.
• Implemented quality guardrails: hallucination detection via citation verification (95%+ evidence grounding rate), coverage scoring against PRD requirements, and automatic regression flagging.
• Built LLM-powered diagnostics UI + FastAPI backend for root cause analysis, surfacing regression insights and generating vendor-specific CLI commands for Nokia SR OS and third-party platforms.
• Deployed services with FastAPI, Docker, and Kubernetes; CI/CD via GitHub Actions with 98%+ pipeline pass rate across 3 environments.
• Created ATS Intelligence: real-time anomaly detection engine for 5G test logs using statistical baselines + z-score detection over 500K+ daily log events.
• Built log ingestion, scoring, and summarization pipelines producing actionable diagnostics for SRE teams, reducing mean-time-to-identify from ~45 min to ~12 min.

• Built a search-driven Transfer Credit Equivalency platform using Apache Solr, Node/Express, GraphQL, and React, serving 15K+ student queries per semester.
• Designed and deployed REST + GraphQL APIs with optimized Solr indexing and query pipelines, improving search relevance by 30% (measured via NDCG@10).
• Developed campus eServices web applications (Angular, React, Java, PHP) with SSO auth integration, used by 20K+ students and staff.
• Integrated AWS Lambda, S3, and Cognito for event-driven document processing workflows, handling 8K+ document uploads per month.
• Shipped 12 production features end-to-end across 3 release cycles, from UI to API to data layer to deployment.

• Engineered high-throughput backend services in C++ and Python for LTE/NR telecom protocol stacks, reducing packet processing latency by 20% (measured via internal perf benchmarks).
• Designed telemetry pipelines and internal service APIs supporting real-time KPI monitoring for 3GPP L2/L3 layers across 50+ base station configurations.
• Built CI/CD automation with Jenkins and Ansible, cutting release cycles from 4 days to 3 days (25% reduction) and achieving 99.2% deployment success rate.
• Collaborated on fault tolerance and network topology orchestration for distributed RAN systems spanning multi-vendor environments.

PROXIMA: Proxy Metric Intelligence for Reliable A/B Testing

Preprint — stat.ME (arXiv submission pending) · 2025

An IoT-Model for Monitoring Irrigated Crops Using WSN

IEEE ICESC 2022 · 2022