📍 New Delhi, India | 🤖 Applied AI Systems Engineer & GenAI Reliability Specialist | 🚀 Data Science Enthusiast

Passionate about building robust AI infrastructure for reliable GenAI applications. From hallucination auditing to bias-free hiring platforms, I engineer systems that scale with integrity. Currently in my final year at KIIT, pushing the boundaries of applied AI.

• Kalinga Institute of Industrial Technology (KIIT) | B.Tech in Computer Science & Systems Engineering | 2022–2026
• Data Analytics Intern | National University of Singapore | Jun–Jul 2025
  • Conducted EDA on 10k+ Airbnb records, boosting prediction accuracy by 12%.
  • Automated Python workflows, reducing errors by 20–25%.
  • Deployed Power BI dashboards for efficient analysis.
• Data Science Intern | Sukrit Technologies Pvt. Ltd. | 2025
  • Developed SQL-based analytics and automated reporting pipelines.

• 🛡️ Epistemic Audit Engine - Claim-level LLM reliability auditing service for long-form outputs. Features claim extraction, evidence retrieval from Wikidata/Wikipedia, verification, and risk aggregation. Includes a FastAPI backend, Next.js UI, deterministic evaluation harness, and append-only logging for internal datasets.
• ⚖️ FairHire-AI - Resume intelligence platform analyzing hiring bias. Multi-service architecture with Next.js frontend, FastAPI backend, PostgreSQL/Redis storage, and RQ workers for async jobs. Includes Docker Compose setup, Prometheus metrics, and Grafana dashboards for monitoring.
• 🔍 DealLens AI - M&A screening platform with API and worker runtime. Monorepo using Next.js, FastAPI, Celery workers, Redis/PostgreSQL. Hardened for production with retries, structured logging, metrics, and health/readiness endpoints.
• 📈 Dynamic Pricing Decision Simulator - Strategy evaluation platform for pricing under uncertainty. Full simulation runner with Next.js dashboard for comparisons, showing ~4–5% revenue lifts vs. static policies.

• Engineering AI Reliability - Developing tools for GenAI auditing, bias detection, and scalable infrastructure.
• Internship Insights - Applying data analytics and ML from NUS and Sukrit to real-world projects.
• Rapid Prototyping - Building full-stack AI systems with FastAPI, Next.js, and containerized deployments.
• Learning & Contributing - Exploring RAG, embeddings, vector retrieval, and observability in AI workflows.

• NUS Internship Achievements - Improved model accuracy by 12% and reduced defects by 25% through feature engineering and automation.
• KIIT B.Tech Project Highlights - Focused on AI systems engineering with emphasis on reliability and scalability.
• Open Source Contributions - Building production-grade AI tools with modern stacks for community use.

"Reliability first in AI – because trust is the ultimate metric." I focus on systems that not only perform but verify, audit, and scale ethically.

Summary: Random Facts

• Final-year student balancing academics with hands-on AI internships.
• Powered by coffee and code marathons.
• Enthusiast for ethical AI and bias mitigation.
• Always experimenting with new tools like Celery, RQ, and Grafana.