Sumit Garg

Senior Software Engineer

Hyderabad, Telangana, India6 yrs 11 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Architected systems scaling from 3.5M to 15M records.
Reduced operational overhead by 40-70% through automation.
Pioneering AI video analysis for non-verbal cue detection.

Stackforce AI infers this person is a SaaS and AI-focused software engineer with expertise in scalable systems.

Contact

sumit.garg@salesforce.com LinkedIn

Skills

Core Skills

Software DevelopmentSystem ArchitectureSystem OptimizationMachine LearningComputer VisionApi Development

Other Skills

AI AgentsAlgorithmsAnomaly DetectionArtificial Intelligence (AI)AutomationBlotter ConfigurationCC++CSSCapsule NetworkCascading Style Sheets (CSS)Connect APIsContributing Records CalculationDatabasesDeep Learning

About

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.

Experience

6 yrs 11 mos

Total Experience

3 yrs 5 mos

Average Tenure

4 yrs 9 mos

Current Experience

Salesforce

2 roles

Senior Memeber of Technical Staff

Promoted

Aug 2024 – Present · 1 yr 10 mos · Hyderabad, Telangana, India · On-site

Member Of Technical Staff

Aug 2021 – Jul 2024 · 2 yrs 11 mos · Hyderabad, Telangana, India · On-site

◦ 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.

On-Demand ComputationContributing Records CalculationMilestone Computation ModelMeasure Builder UIConnect APIsSoftware Development+1

Arcesium

Software Development Engineer

Jun 2019 – Aug 2021 · 2 yrs 2 mos · Hyderabad, Telangana, India · On-site

. 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.

Blotter ConfigurationTrade AggregationAutomationSoftware DevelopmentSystem Optimization

Malaviya national institute of technology jaipur

Member

Jul 2018 – May 2019 · 10 mos · Jaipur, Rajasthan, India · On-site

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%

Deep LearningAnomaly DetectionCapsule NetworkMachine LearningComputer Vision

Walmartlabs india

Software Developer Intern

May 2018 – Jul 2018 · 2 mos · Bengaluru Area, India · On-site

◦ 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.

REST APIPerformance TestingSoftware DevelopmentAPI Development