AI Engineer with less than a year in LLM orchestration & backend development
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Highly motivated engineering student with 9 months of experience as an SDE and Data Analyst Intern. Proficient in Python, FastAPI, and various AI/ML frameworks. Successfully delivered projects involving multi-agent LLM workflows, RAG backend development, and data analysis to drive actionable insights. Eager to leverage strong technical skills and a passion for AI in a challenging software engineering role.
Birla Institute of Technology & Science Pilani, Hyderabad Campus
B.E. in Civil Engineering · Civil Engineering
August 1, 2022 – July 1, 2026
MS Junior College
Class XII
N/A – May 31, 2021
All Saints High School
Class X
N/A – May 31, 2019
Questt.ai
SDE Intern
July 1, 2025 – December 1, 2025
India
GMR Varalakshmi Foundation
Data Analyst Intern
May 1, 2024 – July 1, 2024
India
Financial-Analyst-Agent
June 24, 2026 – Present
Architected and developed a full-stack AI financial analyst agent using FastAPI, LangChain, and GPT-4o, enabling natural language querying of P&L data across 10+ global regions, reducing analyst report generation time by ~70%. Built secure OTP-based passwordless auth with bcrypt hashing and JWT tokens, reducing login friction by ~50% while supporting 2 role-based tiers. Orchestrated multi-agent LLM workflow (LangChain, LangSmith) with real-time streaming via async WebSocket pipeline. Implemented financial intelligence engine computing YoY growth indices, budget vs actual variances, and hierarchical profitability metrics (EBITDA, EBIT, PAT).
View ProjectEnterprise Document Intelligence Platform
June 24, 2026 – Present
Architected an async RAG backend to process PDFs, using Celery & Redis to handle high-concurrency workloads without blocking the API. Reduced LLM operational costs by 40% through Redis Semantic Caching, serving repeated queries directly from memory. Implemented a unified PostgreSQL (pgvector) database to manage high-dimensional vector embeddings alongside relational application data.
View ProjectAI Onboarding Agent
June 24, 2026 – Present
Built a multi-agent AI onboarding system using LangGraph and GPT-4o to detect user blockers and deliver real-time nudges via WebSocket. Engineered a LangGraph state machine orchestrating 4 AI agents: Diagnosis, Coach, Action Taker, and Escalation with deterministic routing logic. Designed an event-driven pipeline with FastAPI and Redis Streams to ingest user behavior events asynchronously and trigger AI diagnostic workflows.
View ProjectCultural Fit Analysis
The candidate's project diversity, ranging from financial analysis agents to document intelligence platforms and onboarding systems, indicates a broad interest in applying AI across different domains. Their involvement in leadership roles in student organizations suggests proactiveness and a collaborative spirit. The skills listed and projects undertaken align well with the target role of an AI Engineer, demonstrating a strong passion and aptitude for the field despite their current academic major. This breadth and initiative suggest a good cultural fit for an innovative and fast-paced environment.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex project architectures and optimization efforts. Their experience in leading and coordinating events suggests good organizational and teamwork capabilities. The focus on delivering measurable results in projects indicates a results-oriented approach. The candidate's ability to articulate technical details clearly in project descriptions suggests good communication skills, which are crucial for operational fit in a senior role.