AI Engineer with 1+ years in RAG & Multi-agent LLM systems
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AI/ML Engineer with hands-on production experience building RAG pipelines, multi-agent LLM systems, and computer vision solutions. Proficient in Python, PyTorch, and the modern LLM stack (LangChain, LangGraph, MCP). Passionate about turning research-grade AI into reliable, low-latency production systems.
MS Ramaiah Institute of Technology, Bangalore
B.E. · Information Science & Engineering
August 1, 2021 – June 30, 2025
Valiance Solutions
Data Scientist
May 1, 2025 – Present
Bengaluru, Karnataka, India
Multi-Agent Financial Research System
June 1, 2025 – Present
Engineered a 4-agent LangGraph system covering stock analysis, news retrieval, sentiment scoring, and risk assessment, delivering end-to-end investment research autonomously. Designed planner-driven workflows with shared state management, enabling agents to coordinate across tasks without manual intervention. Integrated MCP-based tool orchestration for real-time financial data retrieval and chart generation, making the system extensible to new data sources. Streamlit dashboard serving real-time AI-powered financial insights and auto-generated investment reports.
View ProjectAI YouTube Blog Generator
June 1, 2025 – Present
Extracted and cleaned YouTube transcripts via the YouTube Transcript API, feeding them into a LangGraph planning agent that outlines and streams a structured, publish-ready blog post in real time. Scraped official documentation for technologies detected in the video using web crawling, and surfaced relevant reference links alongside the blog so users can explore topics in depth. Enabled a Question and Answering interface over video content using LangGraph tool-calling agents, with persistent storage for all generated blogs. Orchestrated the full workflow - transcript extraction, planning, blog generation, doc scraping, and Q&A - as a multi-step LangGraph pipeline with reliable state management
Professional Machine Learning Engineer Certification
Unknown
June 1, 2026 – Present
Google Gen AI Leader Certification
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate initiative and a passion for applying AI in diverse domains (finance, content generation). The experience with both personal projects and a professional role indicates a proactive learning attitude and ability to adapt to different work environments. The breadth of skills and tools used suggests a willingness to explore and integrate new technologies, which aligns well with an innovative culture. The target role of AI Engineer is a strong fit for the candidate's demonstrated skills and interests.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-component systems, suggesting good problem-solving and architectural thinking. The focus on 'reliable, low-latency production systems' implies an understanding of operational considerations. However, without direct assessment data, specific soft skills like teamwork, leadership, or stress handling cannot be definitively evaluated.