Generative AI Engineer with less than a year in LLM solutions, RAG pipelines & Python
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Assessing your cultural and operational fit
Computer Science graduate (CGPA: 8.09) with strong Python, LLM, RAG, Prompt Engineering, and API development skills. Passionate about building AI-powered applications and intelligent solutions. Seeking a Generative AI Engineer role at Polluxa to develop LLM-based solutions, design RAG pipelines, integrate AI workflows, and collaborate on innovative generative AI applications.
Aditya College of Engineering
B.Tech · Computer Science & Engineering
August 1, 2021 – June 30, 2025
Sri Chaitanya Junior College
Intermediate (MPC)
June 1, 2019 – May 31, 2021
Z.P High School, Devalacheruvu
SSC
June 1, 2018 – May 31, 2019
IBM SkillsBuild
AI & Machine Learning Intern
September 1, 2025 – June 1, 2026
India
Deep Learning Diagnostic Platform for Heart Sound Classification
January 1, 2025 – December 1, 2025
• Built an AI-powered web application using Python to classify heart sounds as Normal or Abnormal. • Designed an end-to-end AI pipeline: data ingestion → Python preprocessing → deep learning model → REST API → result delivery. • Integrated the trained AI model into a Django backend via REST API – similar to LLM-based solution integration. • Used Python scripts for audio feature extraction (MFCCs) – analogous to embedding generation in RAG pipelines. • Deployed the AI application and optimised model performance through iterative testing and tuning. • User uploads a heart sound file → system processes via AI model → instantly returns Normal or Abnormal result.
Multiple sports awards (Throwball, Cricket, Handball)
school and college level
June 1, 2026 – Present
NPTEL Silver Medal
Cloud Computing
September 1, 2025 – Present
ALL INDIA NCAT Certification
Unknown
September 1, 2025 – Present
AI & ML Internship Certification
IBM SkillsBuild
September 1, 2025 – Present
Project Expo – ACE TECHZION 2k23
Paper Presentation - Konnect 2k23
January 1, 2023 – Present
Cultural Fit Analysis
The candidate's academic project and internship experience demonstrate a strong interest and foundational knowledge in AI/ML, particularly in areas relevant to Generative AI. The mention of collaboration in the internship and project work suggests a team-oriented approach. The diversity of skills and project types (deep learning, LLM concepts) indicates adaptability and a willingness to explore different facets of AI, which could contribute positively to cultural fit in an innovative environment. However, the candidate is still early in their career, and the breadth of experience is limited to academic and internship settings.
Soft Skills & Operational Fit
The candidate lists problem-solving, analytical thinking, team collaboration, and communication as soft skills. The project and internship descriptions suggest an ability to work through technical challenges and collaborate, which aligns with operational fit for a Generative AI Engineer role. However, without direct observation or further assessment, the depth of these soft skills cannot be fully validated.