Python Engineer with 1+ years in GenAI & RAG
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Backend Engineer specializing in Python, GenAI, RAG, and Workflow automation. Experienced in designing and developing internal AI-driven applications integrating LLMs via frameworks such as LangChain, LangGraph, MCP and deploying scalable backend systems on virtual machines using Docker and Nginx.
Vishwakarma Institute Of Technology, Pune
Bachelor of Technology · Computer Science Engineering
August 1, 2021 – June 30, 2025
Gruve.ai
SDE-I
June 1, 2025 – Present
Pune, Maharashtra, India
Reddit Intel
February 1, 2026 – March 31, 2026
Synthesized an internal system to ingest and index Reddit discussions for domain-specific technical intelligence. Engineered a distributed AI platform using React.js, FastAPI, MongoDB, Redis, Celery, and LLM APIs. Devised RAG pipelines using LangChain integrating enterprise knowledge bases outcoming standard insights. Containerized services on Docker-based VM infrastructure behind Nginx, enabling structured export workflows (CSV/Excel).
Udemy x HappyFox Automation
October 1, 2025 – January 31, 2026
Weaved a Python-based automated license provisioning system that intercepts HappyFox Helpdesk tickets and dynamically assigns Udemy Business seats. Instituted an automated engagement monitoring mechanism to detect inactivity and revoke licenses after 7 days. Streamlined ticket resolution workflows, reducing manual intervention and decreasing license provisioning time by 95 percent.
AIMine
August 1, 2025 – December 31, 2025
Spearheaded RAG evaluation and observability pipelines using Comet Opik, enabling end-to-end tracing of LLM. Facilitated ingestion of chatbot contact submissions into HubSpot CRM via APIs pivoting AIMine as source. Instrumented observability across the LLM pipeline to support performance analysis, benchmarking for LLMs. Devised data synchronization workflows between the chatbot interface and CRM systems to streamline lead tracking and operational visibility.
Cultural Fit Analysis
The candidate's projects showcase a strong interest in AI, automation, and distributed systems, which aligns well with a modern tech-driven culture. The diversity of projects (Reddit Intel, AIMine, Udemy x HappyFox Automation) indicates adaptability and a broad technical curiosity. The focus on practical, problem-solving applications suggests a results-oriented mindset. The academic background combined with immediate industry experience (even if future-dated) points to a driven individual.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and a focus on efficiency (e.g., reducing manual intervention, streamlining workflows). The academic projects demonstrate initiative and the ability to deliver functional systems. The SDE-I role at Gruve.ai suggests an ability to work in a professional, enterprise-grade environment. However, without direct assessment data on soft skills, this remains an inference.