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Agentic AI Developer (Enterprise AI Tech Lead)
Agentic AI Developer at Scholastic who built an enterprise MCP platform used weekly by 350+ engineers across 23 tools.
IndiaAgentic AI Developer (Enterprise AI Tech Lead) at Scholastic
Tech lead for Scholastic's org-wide agentic intelligence platform, an automated interface across 23 engineering and security tools used weekly by 350+ engineers. Designed RBAC-scoped MCP servers, reduced MTTI by 70%, and cut cross-tool incident lookup latency to under 1.8s.
MCPMulti agent orchestrationMastraLangGraphJSON RPCRBACDatadogQualysSonarQubeJiraGemini FlashSemantic Caching (GPTCache)LLM As A JudgeEvaluation Frameworks
Technical owner of a financial document-intelligence platform for 7 years, directing a 15-person team. Tripled ingestion throughput, reached 94% structural extraction accuracy, and improved multi-hop question accuracy by 40%.
CNNOCRYOLOQwen2 VLDonutLang ChainPgvectorNL To SQLPostgreSQLActive LearningData AnnotationMobileNetV3EfficientNetV2RetinaNetCalamariGenerative Transformer OCR
Developed a CNN-based system for cross-view matching between ground-level and overhead imagery. Built a Siamese CNN model for matching building images with Google Street View counterparts and designed an object detection-driven model for automated layout extraction from PDF forms.
CNNSiamese NetworksObject DetectionLayout ExtractionComputer Vision
Built the first probabilistic slope stability framework for opencast mining using photogrammetric 3D pit geometry. Developed 3D reconstruction-based numerical modelling pipelines and machine learning models for coal quality prediction.
Photogrammetry3D ReconstructionMonte Carlo SimulationsRandom FieldsregressionClassificationPLsRandom ForestXGBoostSVMSMOTEPoint Cloud ProcessingComputer Vision
PhD research in computer vision and probabilistic modelling for risk assessment.
Dual degree program in Mining and Safety Engineering.
Profile sourced from Himalayas.