Hyderabad, Telangana, India
I turn complex technical challenges into scalable solutions that drive millions in business value. Senior Software Engineer with 6+ years building enterprise systems at Salesforce and Arcesium. Recently pivoting into AI/GenAI development, currently leading Agentforce Sales Coach—combining cutting-edge AI with sales technology to revolutionize how teams achieve their goals. What sets me apart: - Architected systems scaling from 3.5M to 15M records, unlocking multimillion-dollar deals - Built end-to-end On-Demand Computation and Contributing Records features for sales milestone tracking. - Now pioneering AI video analysis POCs using Gemini models for non-verbal cue detection - Consistently reduced operational overhead by 40-70% through intelligent automation Technical Evolution: Strong foundation in Java, Python, JavaScript, enterprise systems—now expanding into LLMs, GenAI, and RAG technologies From financial trading systems to sales platforms, I build solutions that matter. Now excited to bring my enterprise engineering expertise into the AI revolution.
◦ Led end-to-end development of On-Demand Computation (enabling sales reps to view updated milestone progress at their convenience) and Contributing Records Calculation (providing transparency into the records contributing to milestone progress). Also implemented Tracking and Dedupe Handling within milestone computation, collaborating with cross-functional teams and presenting design solutions at key forums. ◦ Designed and implemented the next generation Milestone Computation Model to scale the computation capacity from 3.5M to 15M records per run, facilitating a key multimillion dollar deal with our largest client, AWS. ◦ Developed the Measure Builder UI, Connect APIs, underlying data model, to provide sales managers with a tool for defining sales goals.
. Developed functionality to support amendments in all blotters (EOD trade files with daily trade activities by executing brokers), ensuring accuracy and eliminating the risk of sending incorrect data. . Optimized the trade aggregation process, resulting in a 40% reduction in memory usage. . Automated blotter configuration setup, accelerating new client onboarding and reducing setup time by 70% for the development team.
Member at Vision Intelligence Lab MNIT Jaipur Anomaly Detector ◦ Developed a Deep Learning Model for Anomaly Detection in Surveillance Videos using Capsule Network and Res3D. ◦ Data set: UCF-Crime [covers 13 real world anomalies]. ◦ Training Accuracy - 90.20%, Validation Accuracy - 85.06%
◦ Developed a REST API for Column Sensitivity Prediction that predicts the sensitivity of database columns based on their data and metadata. ◦ Performance tested Sandbox-Console (a database-to-data lake migration platform) using Apache JMeter.