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AI Engineer with less than a year in Natural Language Processing & Generative AI.
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Assessing your cultural and operational fit
AI Engineer/Data Scientist with 2+ years of experience in developing and deploying machine learning models, specializing in natural language processing, Generative AI and Large Language Models (LLMs). Hands-on expertise in multiagent orchestration, reasoning workflows and enterprise AI solution development using LangGraph and Vertex AI (GDA). Proficient in Python, SQL, with expertise in prompt engineering, LLM-powered applications, and low-code platforms for rapid prototyping. Adept at optimizing applications for scalability, usability, and performance, with hands-on experience in version control using Git.
Jawaharlal Nehru Technological University, Sultanpur
Bachelor of Computer Science · Computer Science
January 1, 2020 – January 1, 2023
HYPERTHREAD SOLUTION PRIVATE LIMITED
AI ENGINEER
March 1, 2026 – Present
India
Pranathi Software Services
Data Scientist
November 1, 2023 – February 1, 2026
India
Natural Language to RPA Workflow Generator
March 1, 2026 – Present
Architected and developed an Agentic AI-driven Natural Language system to RPA Workflow Generator using LangGraph, FastAPI, and Google Gemini models to convert user instructions into executable automation workflow. Developed a 9-node multi-agent workflow orchestration system that automates intent decomposition, activity matching, parameter collection, workflow compilation, validation, and automated VB.NET/XAML workflow generation. Implemented ChromaDB-based RAG pipelines with semantic retrieval and workflow reasoning to intelligently map automation activities and reduce disambiguation. Engineered intelligent parameter inquiry and auto-fill mechanisms using LLM-based field classification, upstream data propagation, validation rules, and cloud-context resolution to minimize user interaction. Developed real-time SSE streaming APIs, session management, and interactive Angular-based workflow visualization interfaces for dynamic workflow planning and execution tracking. Implemented automated workflow validation, issue routing, and regex-based VB.NET linting pipelines to ensure workflow correctness and reduce compiler failures. Integrated Google Vertex AI Gemini models with cassette-based replay/record infrastructure for deterministic testing, prompt optimization, and low-latency workflow generation. Designed a modular, microservice-oriented AI execution pipeline with a scalable API architecture.
MoM – Minutes of Meeting Generator
November 1, 2023 – February 1, 2026
Developed an LLM-powered application to generate meeting agendas, summaries, and action items. Optimized GPT-40 model prompts for generating structured meeting summaries. Utilized the Whisper model for speech-to-text conversion and processed transcription data for analysis. Designed and deployed a Django-based application for meeting minutes generation, ensuring rapid prototyping and efficient delivery. Ensured high-quality development standards through testing and debugging.
Government ID Parser
November 1, 2023 – February 1, 2026
Engineered a parser to extract, validate, and structure information from government ID documents. Implemented OCR pipelines using EasyOCR and Tesseract for high-accuracy text extraction. Applied NLP techniques (tokenization, text normalization, regex-based entity extraction) to structure raw text. Trained and fine-tuned NER models using Spacy and NLTK for domain-specific entity extraction. Optimized OCR and NLP pipelines for scalability and performance.
AI-Powered SEO & SMM Automation Tool
November 1, 2023 – February 1, 2026
Built an AI-driven SEO and Social Media Marketing automation platform using LLMs and agent-based workflows for competitor analysis, content generation, and automated publishing. Integrated website analysis, Google Places APIs, and web search pipelines to extract business insights, identify competitors, and analyze keyword strategies. Implemented Apify-based competitor intelligence pipelines to analyze 1-3 months of social media posts, hashtags, engagement metrics, and content trends. Automated generation of monthly content calendars with AI-generated captions, hashtags, posting schedules, and engagement-focused campaign ideas. Automated generation of SEO content, social media captions, hashtags, and monthly content calendars using competitor insights and trend analysis. Integrated Google generative AI models and publishing workflows for creating and posting AI-generated creatives, reels, blogs, and marketing content to Instagram, Facebook, and WordPress.
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong alignment with an AI Engineer role, showcasing diverse applications of AI from document parsing and RPA workflow generation to SEO/SMM automation and meeting summarization. The breadth of technologies used (Python, various AI/ML libraries, web frameworks, databases, cloud platforms) indicates adaptability and a willingness to learn and apply new tools. The focus on practical, real-world problems suggests a product-oriented mindset. The experience with both data science and AI engineering roles indicates a versatile profile suitable for dynamic environments.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong problem-solving aptitude and an ability to architect complex AI systems. The focus on end-to-end solutions, from data processing to deployment and optimization, suggests a practical and results-oriented approach. The experience with multi-agent systems and workflow orchestration implies good organizational and system-thinking skills. However, without direct interview data, specific soft skills like teamwork, leadership, or adaptability cannot be fully assessed.