Architecting Resilient Backend & Applied AI Systems
Combining systems discipline with explainable, evidence-backed machine intelligence.
Computer Science and Engineering student with hands-on experience building Java and Spring Boot backend systems — REST APIs, database-driven services, and containerized microservices. Has designed AI-integrated systems spanning cybersecurity and production-incident intelligence, including real-time communication, anomaly detection, automated threat analysis, retrieval-augmented generation (RAG), AI agents, and event-driven/distributed processing. Focused on building systems that are explainable, evidence-backed, and production-minded rather than purely academic exercises.
“The system prefers explicit uncertainty over hallucination — it will not fabricate a root cause without adequate evidence.”
Backend Engineering
Scalable Java & Spring Boot microservices, high-throughput REST APIs, and containerized services with robust database schemas.
Applied AI & RAG
Evidence-grounded AI agents, hybrid semantic + keyword retrieval, and deterministic safety layers preventing model hallucinations.
Distributed Systems
Event-driven telemetry ingestion, asynchronous processing at scale, and real-time streaming architectures.
Security & Observability
Zero-trust principles, token-based authentication, real-time anomaly detection, and granular distributed tracing.
Production Systems & Deep Dives
Explore interactive 3D architectures, deterministic anomaly detection, and simulated incident pipelines.
ResolveIQ
Production Incident Intelligence Platform
Deterministic correlation, autonomous agent investigation, and evidence-backed root cause analysis.
Deterministic Detection & Correlation Engine preceding AI evaluation
Spring AI Investigation Agent operating with sandboxed read-only tools
Hybrid RAG combining pgvector cosine similarity with BM25 keyword precision
Cyber Sentinel
Secure Real-Time Communication Platform
End-to-end encrypted messaging paired with dual-layer machine learning and LLM threat intelligence.
Dual-layer threat detection: K-Means clustering pre-filter + Gemini AI reasoning
Full-duplex WebSocket / STOMP messaging with Spring Cloud Gateway perimeter
Redis Pub/Sub broadcasting with automatic TTL cleanup for ephemeral chat rooms
Engineered Capabilities & Technologies
Categorized toolchains across systems programming, persistence, distributed streaming, and applied AI.
// LANGUAGES
5 TOOLSCore programming and query languages used for system implementation
// BACKEND
3 TOOLSApplication frameworks, protocols, and microservice architectures
// DATABASES
3 TOOLSRelational, in-memory caching, and vector indexing engines
// DEVOPS & TOOLS
3 TOOLSContainerization, version control, and deployment pipelines
// MESSAGING & AI
4 TOOLSDistributed message queues, workflow automation, and LLM integrations
Engineering Challenges & Milestones
Participation in national-level competitive engineering and hackathon sprints.
Amazon ML Challenge 2026
National-Level 72-Hour Machine Learning Sprint
Participated in Amazon's prestigious national-level 72-hour Machine Learning Challenge, collaborating in a team to build an applied ML pipeline tackling a large-scale real-world problem using an Amazon-provided multimodal dataset.
Full-Stack Enterprise Specialization
Intensive immersion in Java, Spring Boot microservices, and persistence systems.
Java Full Stack Development
Hands-on immersion in enterprise Java architecture, full-lifecycle Spring Boot backend engineering, transactional persistence layers, and RESTful API services.
Certifications & Validated Studies
Verified coursework spanning Generative AI, LLM prompting, and autonomous workflows.
Master Generative AI & Generative AI Tools
Infosys Springboard
Deep dive into foundational GenAI concepts, LLM architectures, fine-tuning, embeddings, and enterprise generative toolchains.
ChatGPT-4 Prompt Engineering: ChatGPT, Generative AI & LLM
Specialized AI Certification
Advanced structured prompting methodologies, few-shot patterns, system instruction architectures, and zero-shot reasoning evaluation.
Build Generative AI Apps with No-Code Tools
AI Solutions Program
Architecting automated AI agent pipelines, webhook integrations, and vector retrieval using visual orchestration platforms.
Education & Foundations
Formal computer science coursework and academic progress from matriculation to undergraduate degree.
Specializing in software systems, distributed computing, database management, and intelligent software engineering.
Built strong foundations in core computer science, data structures, algorithms, object-oriented programming, and relational databases.
Achieved maximum score (100%) in secondary school matriculation examinations.
Direct Communication Channel
Open for backend engineering, AI/ML systems, and distributed architecture opportunities.