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AI Research Engineer with less than a year in LLMs, RAG, and machine learning pipelines
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Assessing your cultural and operational fit
AI-focused Python Developer with hands-on experience building intelligent systems using LLMs, Retrieval-Augmented Generation (RAG), and machine learning pipelines. Skilled in designing scalable Python-based backend services, RESTful APIs, and data processing workflows using SQL/NoSQL databases. Experienced in developing production-ready AI applications with strong emphasis on performance, reliability, and modular system design.
Indian Institute of Information Technology, Sri City
B.Tech · Electronics and Communication Engineering
August 1, 2022 – June 30, 2026
Defence Research and Development Organisation (DRDO)
AI/ML Research Intern
May 1, 2025 – July 1, 2025
Visakhapatnam, Andhra Pradesh, India
Autonomous Multi-Agent Financial Close Orchestrator
June 24, 2026 – Present
Engineered a network of 10+ specialized AI agents using Python and LangChain to automate the monthly accounting cycle for 8 companies, effectively removing 80% of the manual effort required for workflow execution. Designed context-aware prompts and a shared memory architecture (via Redis) to enable multi-step reasoning, allowing agents to retain context and pass data autonomously during complex task execution. Built document ingestion pipelines to process unstructured contracts and structured financial records, injecting context into LLMs to automatically resolve budget variances over 10% or $50,000. Integrated AI logic into a production-ready FastAPI backend, developing REST APIs to connect the agentic workflow to a PostgreSQL database and feed results into a real-time stakeholder dashboard.
View ProjectEmotion Wave: AI Speech Engine
June 24, 2026 – Present
Developed an AI-driven TTS system converting text into emotionally expressive speech using NLP techniques, achieving 85-90% classification consistency. Engineered dynamic voice modulation (pitch, rate, volume) with intensity-based scaling, reducing robotic tone by 30%. Built a FastAPI backend enabling real-time text-to-audio generation with <1.5s latency and scalable API design. Integrated dual TTS engines (gTTS & pyttsx3) supporting 9 emotion classes and validated on 100+ diverse inputs.
View ProjectRAG Document QA Chatbot
June 24, 2026 – Present
Built a production-style Retrieval-Augmented Generation (RAG) document QA system using Python, LLMs, and FAISS/Chroma for semantic search. Implemented document chunking and embedding pipelines, improving retrieval relevance and reducing hallucinations. Designed modular backend for ingestion, indexing, retrieval, and LLM-based answer generation, with performance tuning using top-k recall and faithfulness metrics.
View ProjectCultural Fit Analysis
The candidate's projects showcase a diverse range of applications for AI, from financial automation to speech synthesis and object detection, indicating adaptability and a broad interest in AI domains. The target role of 'AI Research Engineer' aligns well with the candidate's demonstrated research and development capabilities, particularly in optimizing models and building production-ready systems. The personal projects and internship reflect initiative and a drive for practical application of AI concepts.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong problem-solving aptitude and an ability to design modular, scalable systems. The psychometric test score (285/500) suggests potential areas for development in logical reasoning, work attitude, stress handling, or team collaboration, which could impact operational fit. However, the detailed project work implies a proactive and results-oriented approach.