Software Developer · AI/ML Engineer · Bengaluru
Building AI-driven solutions with expertise in Generative AI, NLP, and full-stack development. Focused on bridging technology and real-world impact through RAG systems, intelligent agents, and scalable applications.
Recognition
Selected among ~600 global applicants for a competitive residency focused on developing OS-level AI agent systems.
Conversational AI agent for restaurant reservations using custom tool-calling logic.
Built with Llama-3 via Groq API, featuring structured JSON tool calls, backend Python function invocation, and extensible architecture for handling complex reservation workflows.
Key Features: Natural language understanding for booking requests, real-time availability checking, multi-turn conversation handling, and integration with restaurant management systems.
Google Apps Script automation for email-based invoice processing.
Extracts and organizes business data from attachments with zero manual entry, integrating Gmail and Google Drive APIs for seamless document management.
Automated processing of 500+ invoices monthly, reducing manual data entry time by 85%. Features intelligent categorization and automatic filing system.
Comprehensive government record-keeping system with 40% improved data retrieval.
Features secure authentication, role-based access control, advanced filtering capabilities, and a real-time statistics dashboard for demographic visualization.
Handles 100K+ citizen records with sub-second query performance. Implements AES-256 encryption for sensitive data and comprehensive audit logging.
Natural language interface for querying system telemetry data.
Uses DuckDB for metrics storage and Llama2 via Ollama for RAG-powered analysis of CPU, memory, and disk usage patterns with conversational queries.
Enables DevOps teams to query infrastructure metrics using plain English. Supports anomaly detection and predictive alerting based on historical patterns.
AI-powered tool for navigating Bharatiya Nyaya Sanhita laws.
Implements semantic search with ChromaDB vector store and provides contextual AI responses for legal queries using RAG architecture with Groq API.
Indexes 500+ legal sections with 95% retrieval accuracy. Provides case law citations and relevant precedents for legal research.
Kubernetes cluster simulation for testing distributed algorithms.
Provides a controlled environment for evaluating distributed systems protocols with Docker containerization, Flask APIs, and Chart.js visualization.
Simulates cluster behavior under various failure scenarios. Used for testing consensus algorithms, load balancing strategies, and fault tolerance mechanisms.
Strong foundation in multiple programming paradigms with expertise in algorithm design and system architecture.
Hands-on experience building production ML pipelines, fine-tuning LLMs, and implementing RAG systems.
Full-stack development with modern frameworks, REST APIs, and responsive UI design.
Cloud-native development with containerization, orchestration, and CI/CD pipelines.
Expertise in relational, NoSQL, and vector databases for diverse application needs.
Open to opportunities in AI/ML engineering, full-stack development, and research collaborations.
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