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Software Engineer with less than a year in Backend Development & AI/ML.
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B.Tech Computer Science student with experience in full-stack and backend development. Skilled in Java, Node.js, Python, and SQL, with strong knowledge of data structures. Built scalable applications including a production-ready RAG AI system, and eager to contribute to real-world projects as part of a collaborative engineering team.
Keshav Memorial Institute of Technology (KMIT)
B.Tech · Computer Science & Engineering
August 1, 2022 – June 30, 2026
IFS / KMIT
Teaching Assistant – Data Structures & Algorithms (JavaScript)
April 1, 2024 – July 1, 2024
Hyderābād, Telangana, India
AI Doubt Solver – Hybrid RAG System
August 1, 2023 – May 1, 2024
Architected and built a production-grade full-stack AI application end-to-end: frontend query interface, Express.js REST API layer, Hugging Face embedding service, and Pinecone vector store retrieval. Designed modular backend architecture for ingestion, retrieval, reranking, and LLM response generation. Implemented an automated PDF chunking and embedding pipeline, reducing manual data preparation effort to zero for new knowledge-base additions. Integrated Groq's Llama 3.3 API with prompt engineering to produce grounded, context-aware responses, demonstrating proficiency in third-party LLM API integration.
RockStream – Music Streaming Database System
January 1, 2023 – June 1, 2023
Designed and implemented a fully normalized relational database schema (3NF) for a music streaming platform covering users, artists, albums, songs, playlists, and ratings. Enforced data integrity with primary keys, foreign keys, UNIQUE constraints, and CHECK constraints; optimized read performance with indexes and views to reduce query latency. Authored complex analytical SQL queries using JOINS, GROUP BY, HAVING, subqueries, and window functions to power recommendation and reporting features.
CS50 Introduction to Databases with SQL
Harvard University (edX)
June 1, 2026 – Present
Software Engineering Virtual Experience (REST APIs, Kafka, H2, Backend Integration)
JPMorgan Chase (Forage)
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's personal projects demonstrate initiative and a proactive learning attitude, which aligns well with a growth-oriented culture. The diversity of projects (AI, database system) and technologies used indicates adaptability and a broad interest in different areas of software engineering. The teaching assistant role also suggests a willingness to contribute to a team's learning and development. However, the lack of professional team project experience limits the assessment of collaboration in a corporate setting.
Soft Skills & Operational Fit
The candidate's experience as a Teaching Assistant suggests good communication and mentoring skills, which are valuable for team collaboration and knowledge sharing. Project descriptions indicate an ability to work independently on complex tasks and a structured approach to problem-solving. The Agile methodology listed in skills suggests familiarity with iterative development processes.