Sushil Kumar G.

Software Engineer

Pittsburgh, PA, United States1 yr 8 mos experience
AI EnabledAI ML Practitioner

Key Highlights

  • Pioneered multi-agent reasoning system reducing hallucination rates by 40%.
  • Engineered AI copilot automating PRD-to-execution lifecycle, winning 1st Prize.
  • Architected cloud pipeline ensuring 99.9% data freshness for 10,000+ listings.
Stackforce AI infers this person is a SaaS-focused engineer with expertise in AI, data engineering, and scalable systems.

Contact

Skills

Core Skills

Distributed SystemsBackend ScalabilityMachine LearningComputer VisionCloud Data PipelineSearch Engine OptimizationGeospatial AlgorithmsDatabase Optimization

Other Skills

DockerDistributed Systems & Backend ScalabilityDevOpsAWS LambdaEventBridgeRESTful APIsReact.jsNode.jsPostgreSQLJavaGoogle Maps Geometry APICI/CDAgentic AI & LLM Orchestration (LangGraph / RAG)Cloud-Native DevOps & CI/CD MasteryHigh-Precision Geospatial & Data Engineering

About

Great engineering isn't just about solving a complex problem; it’s about building systems that empower others to solve theirs. I believe the best software is born at the intersection of rigorous architecture and a collaborative spirit—where **Agentic AI, Distributed Systems, and Full-Stack Engineering** meet to create something more resilient than the sum of its parts. I’ve had the privilege of working alongside brilliant teams to bridge the gap between academic research and production-grade tools. Whether mentoring a cohort of 600+ students or architecting cloud pipelines to maintain 99.9% data freshness, my focus is on being a **high-leverage teammate** who ships reliable, scalable code. ### Collaborative Highlights *Agentic AI Orchestration: Pioneered a collaborative system utilizing **LangGraph** to orchestrate multi-agent reasoning, reducing research "hallucination" rates by 40%. * Award-Winning Innovation: Contributed to the **1st Prize win at SHE Innovates 2026** by engineering "Plan2Ship," an AI copilot that automated the PRD-to-execution lifecycle, reducing manual overhead by 85%. * Scalable Architecture: Architected an automated cloud data pipeline synchronizing 10,000+ daily listings, ensuring seamless availability for an EC2-hosted platform. * Performance Optimization: Reduced search latency by 40% (under 200ms), significantly improving the user experience across 40,000+ listings. ### Technical Engine * Agentic AI & ML: Generative AI, LangGraph, LangChain, RAG, LLMs, Transformers, PyTorch, Scikit-learn, NLP. * Backend & Distributed Systems: Python, Go, Java, C++, TypeScript, Microservices, RESTful APIs, FastAPI, gRPC, Kafka, Hadoop. * Cloud & DevOps: AWS (EC2, S3, Lambda, SageMaker), GCP, Docker, Kubernetes, CI/CD, Linux/Unix. * Data Engineering: PostgreSQL, MongoDB, MySQL, Cassandra, Vector Databases, ETL, Elasticsearch. * Frontend: React.js, Next.js, Redux, Tailwind CSS, Node.js. ### Beyond the Code When I’m not at the terminal, I apply the same logic to competitive mathematics, having ranked 3rd nationally in a high-stakes competition testing advanced calculus and linear algebra. **The Open Door:** I’m eager to connect with engineering leaders and founders building the next generation of scalable, autonomous infrastructure. If you're looking for a dedicated teammate who values both technical excellence and collective growth, I’d love to chat.

Experience

1 yr 8 mos
Total Experience
1 yr 8 mos
Average Tenure
1 yr 8 mos
Current Experience

Northbridge

Software Engineer Intern

Jul 2025Oct 2025 · 3 mos · Pittsburgh, Pennsylvania, United States · Remote

  • Architected an automated cloud data pipeline using AWS Lambda and EventBridge to synchronize 10,000+ daily listings from external RESTful APIs, maintaining 99.9% data freshness on an EC2-hosted platform.
  • Engineered a high-performance search engine utilizing React.js and Node.js, optimizing PostgreSQL indexing and frontend rendering to reduce search latency by 40% (under 200ms) across 40,000+ listings.
  • Refactored core backend services to integrate CI/CD workflows and launch 3+ business-critical features, resulting in a 70% increase in user satisfaction and significantly improved codebase maintainability.
  • Implemented a comprehensive automated testing suite across the full stack using Jest and PyTest, achieving 85% test coverage and reducing production deployment regressions by 30%.
DockerDevOpsCloud Data PipelineSearch Engine Optimization

University of pittsburgh school of computing and information

3 roles

Course Facilitator TA

May 2025Present · 1 yr

  • TA for courses Bayesian Data Analysis and Cloud Computing
DockerDistributed Systems & Backend ScalabilityDistributed SystemsBackend Scalability

Graduate Resarch Assistant

Oct 2024Present · 1 yr 7 mos

  • Conducting research under Dr. Pengfei Zhou on computer vision and machine learning algorithms for analyzing food intake data.
  • Developed real-time food volume and calorie content analysis using visual and vibration sensor data.
  • Collaborated on assessing dietary restrictions through meta glasses for disease tracking based on food intake.
DockerDistributed Systems & Backend ScalabilityMachine LearningComputer Vision

Graduate Teaching Assistant

Sep 2024Present · 1 yr 8 mos

  • Grader TA in Two Computer Science Department: Namely: CS007 and CS445 for data structures and intermediate java programming concepts.
DockerDistributed Systems & Backend Scalability

Mahyco

Software Engineer Intern

May 2023Jul 2023 · 2 mos · Delhi, India · Remote

  • Engineered a high-performance spatial overlap detection algorithm using Java and Google Maps Geometry API, identifying and merging redundant field polygons with 98% precision to ensure production-grade data integrity.
  • Built a field-tagging optimization engine that eliminated 25% of data redundancy in PostgreSQL, reducing monthly cloud storage and API costs by 15%; integrated automated database migration scripts into the CI/CD pipeline to ensure safe, zero-downtime schema updates.
  • Deployed advanced geospatial features to a production environment serving 2 Million+ active farmers by synchronizing real-time revisions through RESTful APIs, utilizing Dockerized microservices to maintain high availability during feature rollouts.
  • Refactored backend spatial queries using R-tree indexing, slashing proximity search latency by 60% and enhancing mobile application responsiveness; established an automated regression testing suite using GitHub Actions to prevent performance degradation in subsequent builds.
DockerJavaGeospatial AlgorithmsDatabase Optimization

Education

University of Pittsburgh School of Computing and Information

Master of Science - MS — Computer and Information Sciences

Jul 2024May 2026

Carnegie Mellon University

Master's degree — Distributed Systems

Aug 2025Dec 2025

Indraprastha Institute of Information Technology, Delhi

Bachelor of Technology - BTech — Computer Science

Jan 2020Jan 2024

Kiit World School

12 class CBSE — science

Jan 2018Jan 2019

Kiit World School

10 class -CBSE

Jan 2016Jan 2017

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