
AI Engineer with 1+ years in AI/ML & Backend Development
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Results-driven Software Engineer with 1.5 years of combined experience in backend development and Artificial Intelligence solutions. Strong expertise in Java, Spring Boot, and AI/ML technologies, with hands-on experience in building scalable systems, developing machine learning pipelines, designing RESTful APIs, and deploying data-driven applications. Passionate about solving complex real-world problems using intelligent architectures.
Vignan's Institute of Information Technology
Bachelor of Engineering (B.E.) · Electronics and Communication Engineering
N/A – June 30, 2022
Alorica
Technical Support Engineer
October 1, 2024 – July 1, 2025
India
Capgemini
iOS Developer
April 1, 2022 – September 1, 2022
India
AI Resume Screening System
June 4, 2026 – Present
Designed and implemented an intelligent hiring assistant utilizing natural language processing and machine learning to analyze raw resume text data. Implemented TF-IDF Vectorization combined with Cosine Similarity algorithms to match and rank resumes against target job descriptions accurately. Improved candidate shortlisting structural efficiency by approximately 60%, drastically minimizing human screening overhead.
E-Commerce Backend System
June 4, 2026 – Present
Developed robust backend architecture covering critical application modules including product catalogs, order processing, and user profile management. Implemented flexible role-based access control (RBAC) and managed session state structures for handling an interactive, real-time user cart system. Optimized complex SQL database queries to minimize response bottlenecks and ensure performance stability under concurrent requests.
REST API Microservices Application
June 4, 2026 – Present
Built production-ready, enterprise-level RESTful APIs using Spring Boot, incorporating standard CRUD operations and security patterns. Designed and decoupled application modules into a scalable microservices architecture ensuring independent deployment capabilities and low systemic latency. Configured secure authentication protocols and managed seamless data persistence through MySQL database integrations using JDBC.
Image Classification System (Deep Learning)
June 4, 2026 – Present
Engineered a custom Convolutional Neural Network (CNN) architecture inside TensorFlow/Keras for handling multi-class image classification. Applied advanced data preprocessing pipelines, synthetic data augmentation steps, and strategic hyperparameter tuning methods. Achieved high validation accuracy thresholds, validating model resilience against over-fitting anomalies.
AI Chatbot for Customer Support
June 4, 2026 – Present
Developed an advanced NLP-powered chatbot engineered to automate response pipelines and scale back manual Level-1 support overhead. Implemented intelligent intent recognition layers and optimized keyword-based tokenization models to maximize response accuracy. Designed an adaptable interface architecture to support seamless operational integration into standard web enterprise backend systems.
Cultural Fit Analysis
The candidate's project portfolio shows a strong focus on AI/ML applications, which aligns well with an AI Engineer role. The diversity of projects (NLP, image classification, backend systems) indicates a broad technical interest and adaptability. The 'Dual Domain Expertise' in both backend engineering and AI/ML model deployment is a significant asset for roles requiring full-stack AI capabilities. However, the professional experience is limited and not directly in an AI engineering role, which might require a stronger demonstration of cultural fit within a dedicated AI team.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a 'Production Mindset' and an ability to improve efficiency (e.g., 60% improvement in shortlisting efficiency). Collaboration within cross-functional teams is mentioned in previous experience, suggesting an ability to work in team environments. However, specific soft skills like problem-solving, adaptability, or leadership are not explicitly detailed beyond project outcomes.