Anil Pradhan

Automated Image Quality & Integrity Validation — Built fast preprocessing validation to screen for blur and image anomalies before triggering downstream AI models, preventing wasted compute.

Fine-Tuned YOLO11n Component Detector — Trained a custom YOLO11n model to accurately detect and localize electronic components and micro-passives across complex circuit boards.

Vector-Based Blueprint Matching — Leveraged visual embeddings and FAISS vector indexing to rapidly match target boards against verified golden reference specifications.

Multi-Agent Visual Evidence Aggregation — Implemented an orchestrated multi-agent workflow combining specialized visual agents to cross-verify markings, labels, and physical structures.

Real-Time Telemetry & Progress Updates — Implemented Server-Sent Events (SSE) to push live pipeline execution milestones and inspection diagnostics directly to the user dashboard.

Automated Audit Reporting & Governance — Engineered an automated report generator producing tamper-evident audit summaries with explainable root-cause verdicts.

Agent 0 Orchestrator & Self-Healing Pipeline — Built the orchestrator for a 6-stage AI pipeline, coordinating task collection, extraction, deduplication, quality checks, prioritization, and scheduling across 5 data sources.

Lifecycle & State Management (14–18s) — Implemented the pipeline lifecycle and state management to handle stage execution and recovery, completing the full workflow in around 14–18 seconds.

Fast Task Deduplication & Traceability — Created a fast string-matching algorithm that merges duplicate tasks across tools in ~3 seconds while keeping full links back to original sources.

7-Dimension Quality & Explainable Priority — Built an automated checker that scores task quality across 7 checks, plus a weighted priority system that explains exactly why a task is ranked high or low.

Calendar-Aware Dynamic Daily Planner — Created a smart daily planner that protects scheduled meetings, adds short breaks between deep work, and fits prioritized tasks into available free hours.

Reliable LLM Integration & Instant P1 Copilot — Built a reliable LLM client with fallback mechanisms to survive API failures, plus real-time P1 task injection through the AI copilot to instantly move urgent incidents to the #1 priority.

LangGraph Multi-Agent Orchestration (~60% Speedup) — Engineered a compiled LangGraph DAG coordinating 4 concurrent agents (Resume Auditor, Market Scraper, Roadmap Generator, LinkedIn Optimizer) with shared state, cutting analysis latency from 4 minutes to ~60 seconds.

WebSocket 7-Phase FSM Mock Interview Engine — Developed a real-time interactive technical interview engine over WebSockets with stateful FSM transitions, Monaco code editor integration, and resume-personalized dynamic questioning.

RAG Skill-Gap Curriculum Engine — Implemented vector similarity search to index learning resources and generate personalized, step-by-step career transition roadmaps tailored to identified skill deficits.

Resilient Multi-Provider LLM Failover Layer — Architected a zero-downtime routing gateway with automatic fallback across Groq, NVIDIA NIM, and Cerebras, ensuring continuous uptime during rate limits and API outages.

High-Throughput Backend & Session Persistence — Built an asynchronous FastAPI backend backed by PostgreSQL (SQLAlchemy 2.0) for low-latency profile ingestion and interview state isolation.

Automated Testing & Containerized CI/CD (113 Tests) — Authored a comprehensive 113-test Pytest test suite with Docker containerization, ONNX runtime optimization, and automated GitHub Actions deployment pipelines.