# Parv Dave > Software Engineer Location: San Francisco Bay Area, United States Profile: https://flows.cv/parv I am a Software Developer at C3 AI, specializing in building enterprise-grade agentic AI systems. My work focuses on bridging the gap between complex data and actionable insights, specifically through Retrieval-Augmented Generation (RAG) and large-scale LLM integration. Throughout my career—from my time as a Specialist Programmer at Infosys to my research at Arizona State University—I have focused on driving measurable efficiency. Whether it was reducing client onboarding time by 40% at State Street or cutting enterprise compute costs by 25% via Kubernetes optimization, I thrive on solving the "impossible" problems that impact the bottom line. Core Tech Stack: Backend: Java (Spring Boot), Python, C++, GraphQL, Node.js Frontend: React.js, TypeScript, Angular, Redux AI/ML: OpenAI & Gemini LLMs, RAG, TensorFlow, LSTM/Forecasting Cloud/DevOps: AWS, Docker, Kubernetes, Azure Pipelines ## Work Experience ### Software Engineer @ C3 AI Jan 2024 – Present | Redwood City, California, United States Supply Chain Engineering Team - Order Allocation feature - Currently working on building an enterprise-grade agentic AI system that combines Retrieval-Augmented Generation (RAG) with OpenAI and Gemini LLMs to power context-aware, multi-step reasoning over large-scale enterprise data. - Designed and scaled distributed backend microservices in Python/TypeScript to power the C3 AI Supply Chain Suite, implementing multi-tenant RBAC, compliance logging, and workload isolation. - Maintained reliable operations of production Kubernetes inference workloads through autoscaling strategies and GPU scheduling optimization, reducing compute costs by 25% while sustaining latency below 200ms. - Implemented GraphQL APIs with TypeScript and Apollo Client for schema-driven type safety, eliminating REST endpoint duplication across forecasting and operational dashboards built in React. - Optimized React components using hooks (useReducer, useCallback, custom hooks), reducing code complexity by 20% and improving rendering performance across 15+ production modules supporting live operational views. ### Technical Associate @ State Street Jan 2024 – Jan 2024 | Boston, Massachusetts, United States ### Research Assistant @ ASU Laboratory for Energy And Power Solutions (LEAPS) Jan 2022 – Jan 2024 | Tempe, Arizona, United States - Built and deployed LSTM / DARTs / Keras forecasting models for energy microgrids; improved RMSE by 20% through hyperparameter tuning and feature engineering. - Automated MLOps lifecycle with Docker, Azure Pipelines, GitHub Actions, and model-drift monitoring; reduced manual retraining cycles by 35%. - Architected an energy optimization microservice that interfaced with IOT smart meters and DER devices through REST APIs, cutting energy costs by 22% for pilot households. ### Software Engineer Intern @ State Street Jan 2023 – Jan 2023 | Boston, Massachusetts, United States - Worked for Charles River as an SDE Intern to develop a real-time market data handler using multithreading in Java to process data for equities and FIX trading. - Developed RESTful APIs in Spring Boot to onboard new clients into Charles River’s FIX system, integrating Azure AD SSO + RBAC policies, cutting onboarding time by 40%. - Created a React-based dashboard to monitor 10K+ FIX protocol agreements with real-time validation workflows and exception alerts, reducing manual verification time by 50%. ### Software Engineer @ Samsung R&D Institute India - Bangalore Jan 2022 – Jan 2022 | Bengaluru, Karnataka, India Engineer at Samsung Research Institute Banglore (SRIB) ### Full Stack Developer (Specialist Programmer) @ Infosys Jan 2021 – Jan 2022 | Hyderabad, Telangana, India • Worked on the Infosys Knowledge Studio (IKS) application, which allows users to visualize raw data in a graphical interface and runs a semantic queries on a BERT-based NLP model for text classification. • Migrated legacy batch processing systems to a Kafka-based streaming platform, processing over thousands of transactions monthly with 99.99% uptime. • Containerized applications over Azure Cloud using Docker and Kubernetes, resulting in a 50% decrease in deployment time and a 20% reduction in infrastructure costs. ### Intern @ Bhaskaracharya Institute For Space Applications and Geo-Informatics Jan 2021 – Jan 2021 - Developed different end-to-end APIs using serverless for Product Life cycle management systems using Agile. Worked with Write Anywhere File Layout core team on External Cache (EC) module to improve the read performance. - Integrated entire Microservices environment using services of AWS: SNS and SQS. Tracked specific module’s robustness for maintaining of 2 Real Estate Company Clients in Gujarat. - Participated in Agile development of project timelines, system flow diagrams, documentation, testing. Making Systems Development Life Cycle efficient and increased usability of the product. ### Problem Setter @ HackerEarth Jan 2020 – Jan 2020 Successfully curated coding problems based on data structures and algorithms for different coding contests and hiring events on HackerEarth. ### Student Developer @ Crio.Do Jan 2020 – Jan 2020 1) Created pre-install scripts to run system checks, and completed the installation and configuration of Servers. 2) Implemented the core logic of the portfolio manager and published it as a library. 3) Refactored code to add support for multiple stock quote services. 4) Improved application stability and performance ### Subject Matter Expert @ Chegg Inc. Jan 2019 – Jan 2020 Working as a Computer Science SME at Chegg India. ## Education ### Master of Science - MS in Computer Software Engineering Arizona State University ### Bachelor of Engineering - BE in Computer Engineering G H Patel College of Engineering & Technology ### high school VP & RPTP Science College, Vallabh Vidyanagar ## Contact & Social - LinkedIn: https://linkedin.com/in/parvd --- Source: https://flows.cv/parv JSON Resume: https://flows.cv/parv/resume.json Last updated: 2026-03-29