Software Engineer with 1+ years in AI & LLM development, Python, and C++.
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Assessing your cultural and operational fit
Software engineer with strong experience in algorithmic problem-solving, code review, and evaluating LLM-generated outputs for correctness and reasoning. Proficient in Python and C++, with hands-on experience debugging complex systems, validating model-generated code, and contributing to production-grade and open-source codebases.
Malla Reddy University
B.Tech · Computer Science, AI&ML
August 1, 2022 – June 30, 2026
Bluestock FinTech
Software Development Intern
January 1, 2026 – Present
India
Human AI Labs
Student Lead Member Intern
November 1, 2023 – February 1, 2025
India
LLM Code Evaluation & Bug Detection Framework
January 1, 2025 – June 1, 2025
Built an automated framework to evaluate LLM-generated code across 150+ coding problems, detecting logical flaws, inefficiencies, and incorrect explanations. Improved identification of incorrect solutions by 35% compared to manual review. Implemented executable validation and edge-case testing pipelines using pytest, enabling reproducible assessment of AI-generated programming outputs.
View ProjectCode Review & Refactor Initiative
August 1, 2024 – December 1, 2024
Reviewed and refactored core modules in an open-source Python project (5k+ stars), fixing edge-case bugs and increasing test coverage by 20%. Conducted production-grade code reviews, focusing on readability, correctness, and long-term maintainability.
AWS Cloud Partinitor Certification
AWS
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's involvement in open-source projects and leading student engineering teams indicates a collaborative and proactive approach. Their diverse project experience, ranging from LLM evaluation to full-stack development, suggests adaptability and a willingness to explore different technical domains. The emphasis on clean code, test coverage, and problem-solving aligns well with a culture that values quality and continuous improvement. The remote work experience also points to self-discipline and effective communication in distributed settings.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership potential through their 'Student Lead Member Intern' role, coordinating a team of 6-10 engineers. Their experience with code reviews, enforcing clean code standards, and using Agile/Scrum principles (as listed in CS Fundamentals) suggests a good operational fit for structured development environments. The focus on measurable outcomes (e.g., 30% productivity improvement, 30-40% execution time reduction) indicates a results-oriented mindset. Collaboration through pull requests and code reviews highlights teamwork and communication skills.