Help & Supportcareers@gravityer.com
Full Stack Engineer with less than a year in AI/ML & Cloud technologies
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Full-stack engineer with 7 months of internship experience in developing scalable microservices, building production-ready RAG pipelines using LangChain, and deploying RESTful APIs. Proficient in Node.js, Express.js, React.js, Next.js, and Spring Boot, with strong skills in AI/Machine Learning and database management. Eager to apply technical depth and problem-solving abilities to innovative software development challenges.
Teegala Krishna Reddy Engineering College
Bachelor of Technology · Electronics and Communication Engineering
October 1, 2023 – April 1, 2026
Govt. Polytechnic Jogipet
Diploma · Electronics and Communication Engineering
November 1, 2020 – June 1, 2023
Piazza Consulting Group
Software Developer Intern
February 1, 2026 – April 1, 2026
India
Togeno
SDE Intern
January 1, 2026 – February 1, 2026
India
Marvedge
Backend Intern
July 1, 2025 – September 1, 2025
India
TalentFlow - Hackathon-to-Hiring Automation System
June 5, 2026 – Present
Designed and implemented an automated hiring pipeline to analyse GitHub repositories using LLMs (Claude, Ollama), generating code summaries and evaluating candidates against predefined technical criteria, reducing manual screening effort by ~50%. Developed a React.js dashboard for resume parsing, candidate ranking, and automated email workflows; processed 50+ candidate submissions and improved shortlisting efficiency with ~80% alignment to manual evaluation.
View ProjectPersonal AI Assistant - RAG-Based LLM Pipeline
June 5, 2026 – Present
Built a Retrieval-Augmented Generation (RAG) system using LangChain, indexing 50+ personal knowledge documents into a vector database to enable context-aware and accurate responses. Developed an end-to-end pipeline for data ingestion, chunking, embedding, and semantic search, improving answer relevance by ~40% compared to baseline LLM responses without retrieval.
View ProjectCultural Fit Analysis
The candidate's diverse project portfolio, including an automated hiring system and a personal AI assistant, demonstrates initiative and a passion for applying technology to solve practical problems. Their involvement in a college hackathon and mentoring peers indicates a collaborative spirit and a willingness to contribute beyond individual tasks. The breadth of technologies explored (Python, Java, JavaScript, various frameworks, AI/ML tools) suggests adaptability and a continuous learning mindset, which aligns well with dynamic, innovation-driven environments.
Soft Skills & Operational Fit
The candidate's project descriptions and internship experiences indicate strong problem-solving abilities, a proactive approach to learning new technologies (e.g., LLMs, RAG), and a results-oriented mindset, as evidenced by quantifiable achievements (e.g., reducing API response time, improving shortlisting efficiency). The hackathon win and mentoring experience suggest leadership potential and teamwork skills.