PranavSingh Patil

AI Systems Engineer focused on building scalable, production-grade intelligent systems spanning LLM orchestration, distributed backend infrastructure, async processing pipelines, and applied AI workflows. Experienced in translating AI research concepts into reliable software systems using FastAPI, Azure cloud services, PostgreSQL, queue-driven architectures, and modern AI tooling. Passionate about engineering robust AI products that combine strong systems design, infrastructure reliability, and practical real-world impact.

AI Engineer Intern at TheGrowthVector (2026-05 – Present)

• AI Backend Systems: Engineered scalable AI backends (FastAPI, PostgreSQL) and multi-agent workflows, including a production NLP-to-SQL retrieval system using OpenAI APIs and PowerPlatforms.
• Asynchronous Pipelines: Built distributed job-processing orchestration (Celery, Redis, Azure Service Bus) with PostgreSQL-backed persistence and resilient retry mechanisms for long-running AI workloads.
• Performance Optimization: Resolved production queue-lock failures (MessageLockLostError) and minimized execution latency by redesigning worker acknowledgment flows and implementing adaptive queue-routing logic.
• Cloud & DevOps: Managed Azure cloud infrastructure, secure app configurations, secrets management, and GitHub Actions CI/CD workflows for seamless deployment and production debugging.

AI Intern at Nikqik Tech. (2026-01 – 2026-03)

• Designed and implemented an end-to-end Retrieval-Augmented Generation (RAG) pipeline for an enterprise meeting intelligence system, spanning transcript ingestion, parsing, retrieval, and LLM inference.
• Built a custom.vvt transcript parser and preprocessing pipeline to convert raw meeting recordings into structured, timestamp-aligned text for downstream NLP tasks.
• Prototyped an MCP server and client plugins using the MCP SDK to orchestrate model execution and plugin-based extensions across backend and client layers.
• Developed backend APIs and services in Python and JavaScript; integrated MongoDB for storage and configured secure cloud resources, app registration, and API permission flows on Azure.

Bachelor of Engineering in Computer – Imperial College of Engineering and Research, Pune University (2021-12 – 2025-06)