I build backend systems, scalable architectures, and infrastructure for enterprise applications in commodities fintech (CTRM — Commodity Trading & Risk Management).

I'm particularly interested in how systems behave beyond the happy path — scalability, reliability, multi-tenancy, data consistency, APIs, distributed systems, performance, and clean architecture.

I'm also a curious engineer who enjoys exploring new technologies — from AI agents and LLM integrations to CRM platforms, quantitative/derivatives pricing systems, and cloud infrastructure.

• 🏗️ Design and build enterprise-grade backend systems
• ⚙️ Develop REST APIs and business services with Spring Boot and FastAPI
• 🗄️ Design and optimize PostgreSQL databases
• 🔄 Manage database evolution with Liquibase
• 🏢 Work with multi-tenant architectures (MySQL → PostgreSQL migrations, tenant/BU discriminators, UUID surrogate keys)
• 🔐 Build IAM, authentication, authorization, JWT/RBAC and license management systems
• ☁️ Deploy and monitor services on AWS (EC2, S3, CloudWatch), Docker, and Kubernetes
• 📊 Work with financial/pricing systems and data pipelines for derivatives
• 🧮 Migrate and build quantitative calculation engines (MATLAB → Python)
• 🎨 Build modern web applications with Angular
• 🤖 Explore AI agents, LLM integrations and AI-powered applications
• 🧪 Care about testing, code quality, observability and maintainability

• PostgreSQL / MySQL
• JSON / JSONB
• Database modeling & Liquibase migrations
• Numerical & quantitative processing with Polars (not Pandas) + vectorized NumPy
• Data pipelines for high-volume batch processing (1M+ records/day)

• Git / Git workflows, Bitbucket & Jira
• CI/CD, Jenkins
• Docker, Kubernetes, AWS (EC2, S3, CloudWatch)
• Postman, DBeaver, SonarQube
• Agile development

🤖 AI Agents 🧠 LLM integrations 🔌 AI-powered APIs ⚡ Automation 🧩 Tool calling & agent workflows 🔍 Exploring AI-assisted software engineering (Claude Code, MCP servers)

Migrating a legacy MATLAB derivatives pricing engine to a Python/FastAPI microservice, targeting 7-significant-figure numerical parity across 17+ derivative product types.

• Reverse-engineered proprietary SciComp MEX binaries with no source access, covering Kirk's Approximation, Bilognormal (BLN) quadrature, Normal Diffusion local vol with Levenberg-Marquardt calibration, Craig-Sneyd ADI splitting, and barrier option pricing
• Replaced the MATLAB batch pipeline with Polars + vectorized NumPy, cutting per-batch compute time by ~83%
• Implemented a Strategy Pattern routing mechanism supporting 15+ derivative models, reducing new-model onboarding from multi-day work to a single registration step
• Diagnosed and fixed production issues: FastAPI event-loop blocking causing pod restarts under batch load, and DataFrame chunking inefficiencies in bulk inserts
• Service processes 1M+ pricing records daily on AWS EC2 with CloudWatch monitoring

Leading a MySQL-to-PostgreSQL migration for a multi-tenant CTRM platform.

• Migration pattern: strip business-unit table suffixes, add tenant_id/business_unit discriminators, replace composite keys with UUID surrogates
• Wrote Liquibase changesets, debugged null-returning views across joined master data, and built financial-parameter management APIs with full CRUD, RBAC, and pagination

Built a centralized license and tenant management platform using Angular, Spring Boot, PostgreSQL, and Hibernate.

• JWT authentication and RBAC enforced across 6+ microservices with role-level multi-tenant isolation
• Audit logs and configuration stored on AWS S3

A full-stack CRM built with Angular + FastAPI + Supabase, targeting micro-influencers in India (1K–100K followers).

• Core features: shareable collab link, inbound brand-lead form with budget qualifier, kanban-style lead inbox, WhatsApp/email notifications
• Configurable lead-status system with immutable key slugs and safe deactivation flows
• Freemium monetization model (Free / Pro / Agency tiers)

Distributed Systems
        ↓
System Design
        ↓
Scalable Backend Architecture
        ↓
Cloud Infrastructure
        ↓
Observability & Reliability
        ↓
AI Agents + LLM Applications

Things I want to understand deeply rather than just use:

• Distributed systems & event-driven architecture
• Message queues & caching
• Database internals
• High-throughput APIs
• Kubernetes & cloud architecture
• Observability
• AI agent architecture & LLM infrastructure
• Large-scale data processing

Don't just make it work. Understand why it works, how it fails, and how it behaves at scale.

I care about:

Correctness → Maintainability → Performance → Scalability → Reliability

Good engineering is often less about writing more code and more about making the right architectural decisions before writing the code.

Working toward becoming a stronger backend / systems engineer, with a long-term focus on:

Backend Engineering → Distributed Systems → System Design → Infrastructure → Architecture

while keeping enough frontend knowledge to understand and build the complete product.

• 🍳 Cooking and Travelling
• 📱 Following consumer tech and the Indian job market
• 🏗️ Building side projects
• 🤖 Experimenting with AI agents

I'm always interested in talking about:

Backend Engineering • System Design • Distributed Systems • AI • Infrastructure • Startups • Open Source

If you're building something interesting, feel free to reach out.

Build systems. Break assumptions. Learn continuously.