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AI Engineer with 1+ years in Generative AI & RAG Systems
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Assessing your cultural and operational fit
AI/ML Engineer with 1+ year of production experience designing and deploying intelligent systems at scale. Expertise in Machine Learning, NLP, Large Language Models (LLMs), Generative AI, and RAG architectures. Skilled in building cloud-native systems, agentic AI pipelines, and high-performance APIs. Proven ability to deliver measurable business impact through automation, intelligent retrieval systems, and scalable AI deployments.
Vignan's Institute of Information Technology
B.Tech · Computer Science & Engineering
August 1, 2021 – June 30, 2025
BeyondScale
Associate Software Engineer
January 1, 2025 – Present
Hyderābād, Telangana, India
AI-Powered Grievance Classification System
June 1, 2026 – Present
Built a voice-based grievance system using LiveKit for real-time audio capture and structured data extraction with a QLORA fine-tuned LLM for classification. Designed a LangGraph multi-agent workflow for grievance routing, unique ID generation, and tracking.
Custom MCP Server (Model Context Protocol)
June 1, 2026 – Present
Developed a custom MCP server exposing REST endpoints for tool execution, enabling LLM agents to interact with external APIs. Containerized and deployed using Docker with CI/CD pipelines on AWS for scalable operations.
Text-to-SQL E-Commerce Chatbot
June 1, 2026 – Present
Built an LLM-powered chatbot to convert natural language queries into SQL using LangGraph and multi-step reasoning. Designed a multi-agent workflow with query planning, execution, and response synthesis, including guardrails for safe query generation.
Phishing Website Detection & Cybersecurity QA
June 1, 2026 – Present
Trained a phishing detection model using XGBoost with feature engineering on URL-based datasets. Developed a Streamlit interface and fine-tuned a domain-specific QA model using Hugging Face Transformers.
Machine Learning Specialization
Coursera
June 1, 2026 – Present
Python for Data Science and AI
Udemy
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from cybersecurity to grievance systems and e-commerce chatbots, indicates a broad interest in applying AI across various domains. Their involvement in a hackathon and conducting ML sessions suggests a collaborative and knowledge-sharing mindset. The focus on delivering measurable business impact aligns well with a results-oriented culture. The candidate's skills and project work are highly aligned with an AI Engineer role, demonstrating a strong cultural fit for an innovative and technically driven environment.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through their project work, tackling complex real-world challenges like email classification, multimodal RAG, and financial data extraction. Their experience in architecting serverless workflows and implementing CI/CD pipelines indicates a good understanding of operational best practices and a proactive approach to system reliability. The descriptions suggest an ability to work independently and deliver impactful solutions.