ENGINEERING RESILIENT PIPELINES & CLOUD-NATIVE SYSTEMS.
Backend & cloud systems engineer specializing in Python and FastAPI microservices on Microsoft Azure. Experienced in high-throughput ETL data ingestion pipelines, automated CI/CD rollouts (`-70% deployment time`), scalable database architectures, and multi-region disaster recovery failover systems.
Backend & cloud systems engineer with 2+ years of experience building scalable, cloud-native systems on Microsoft Azure with a primary focus on Python and modern backend architectures. Experienced in designing high-throughput ETL data ingestion pipelines, asynchronous FastAPI microservices, and robust CI/CD automation (`-70% deployment latency`). Seeking high-impact Python backend opportunities where engineering rigor, clean system design, and zero-downtime reliability matter.
EXPERIENCE & DEPLOYMENT TIMELINE
Zversal Private Limited (Backend & Cloud) + Coding Ninjas
[UTC LIVE_STREAM][STREAM ACTIVE] Processing financial data transformations across distributed Azure microservices. Disaster Recovery heartbeat verified: SYNC_OK across East US & Central India regions.
WORK EXPERIENCE & SYSTEM TELEMETRY
.NET / Python Developer(Internship + Full Time)
CLIENT PARTNERSHIP: QUODD (US-Based Financial Market Data Client)
- 01.Collaborated with a US-based client (QUODD) to design, develop, and maintain Azure-based microservices with a strong focus on backend architecture, performance, scalability, and ETL workflows.
- 02.Contributed to the QuoddFunds platform, working extensively on ETL pipelines for mutual fund data ingestion, transformation, validation, and delivery – ensuring data consistency, reliability, and timely availability across downstream systems.
- 03.Built CI/CD pipelines with GitHub Actions, achieving a 70% reduction in deployment time, zero-downtime rollouts, faster developer feedback cycles, and improved deployment reliability.
- 04.Designed and implemented a Disaster Recovery (DR) pipeline on Azure, enabling automated multi-region failover and reducing recovery time with minimal manual intervention.
[00:01:12] INGESTION: Mutual fund tick streams ingested via Azure Function triggers.
[00:01:14] TRANSFORMATION: Validating structured schemas across .NET / Python worker pools.
[00:01:15] CI/CD ACCELERATION: GitHub Actions workflow deployed with zero downtime (70% faster feedback loop).
[00:01:18] DISASTER RECOVERY: Automated multi-region Azure failover heartbeat active and operational.
Teaching Assistant -- Java & DSA(Part-Time Academic Role)
PRODUCTION PROJECTS & AI SYSTEM ARCHITECTURE
AI-POWERED WHATSAPP RAG CHATBOT
Multi-tenant RAG chatbot delivering real-time product recommendations via vector search & tiered tool authorization.
- •Engineered a production-grade, multi-tenant RAG chatbot delivering real-time product recommendations through semantic vector search over a structured retail knowledge base.
- •Architected a dynamic LangGraph agent with subscription-tier-based tool access, ensuring clients interact only with capabilities scoped to their plan — eliminating unauthorized tool hallucination.
PATTERN: Stateful Agent Workflow (LangGraph) with Multi-Tenant Vector Partitioning
THROUGHPUT/LATENCY: Sub-400ms vector retrieval + Cerebras token generation
CORE INNOVATION: Tiered MCP tool registry preventing lower-tier clients from executing privileged backend mutations.
INVENTORY MANAGEMENT SYSTEM
Full-stack web application for sales/inventory monitoring with FastAPI microservices and MCP integration.
- •Developed a full-stack web application for monitoring sales and inventory operations, improving inventory control efficiency by 35% through optimized tracking and reporting.
- •Migrated the backend from Django MVC to a high-throughput FastAPI microservices architecture deployed on Azure Static Web Apps, with SQLAlchemy ORM and MCP integration.
- •Collaborated directly with stakeholders to gather requirements and implement iterative feature enhancements.
PATTERN: Asynchronous REST Microservices with Model Context Protocol (MCP) Bridge
THROUGHPUT/LATENCY: 35% efficiency boost through automated inventory alert pipelines
CORE INNOVATION: Decoupled frontend static hosting (Azure SWA) from backend async microservice worker nodes.
ENGINEERING STACK ARCHITECTURE
PROGRAMMING
Core general-purpose runtime languages for system engineering and backend services.
PROD USE CASE: Async FastAPI services, LangGraph orchestration, ETL data pipelines
PROD USE CASE: High-performance enterprise microservices on Azure container runtime
PROD USE CASE: Data structures, algorithms, object-oriented systems design
FRAMEWORKS & LIBRARIES
Backend execution frameworks, ORMs, and stateful agentic AI orchestration.
PROD USE CASE: Asynchronous REST endpoints, OpenAPI schemas, Pydantic type validation
PROD USE CASE: Cyclic multi-agent workflows, subscription-based tool routing, state persistence
PROD USE CASE: Relational database connection pooling, async ORM queries, migration tracking
PROD USE CASE: Rapid MVC web scaffolding, ORM modeling, legacy service modernization
DEVOPS & TOOLS
Automated deployment pipelines, infrastructure as code, and containerization engines.
PROD USE CASE: 70% faster build & zero-downtime rollout workflows, automated testing
PROD USE CASE: Multi-stage container builds, reproducible microservice runtime packaging
PROD USE CASE: Declarative Azure resource provisioning, parameter-driven environment cloning
PROD USE CASE: Branching strategies, atomic commits, submodule and repository orchestration
PROD USE CASE: Server provisioning, bash scripting, systemd service diagnostics, cron automation
CLOUD (AZURE)
Microsoft Azure distributed compute, networking, and serverless architectures.
PROD USE CASE: Event-driven serverless ingestion triggers for mutual fund ETL pipelines
PROD USE CASE: Managed Kubernetes environment with automated KEDA scale-to-zero
PROD USE CASE: Production API hosting with custom domain binding and SSL offloading
PROD USE CASE: VNet peering, private endpoints, subnet isolation, disaster recovery routing
CERTIFICATIONS & ACADEMIC CREDENTIALS
Microsoft: Azure Fundamentals
Microsoft Certified
Python for Data Science
NPTEL
Design Thinking – A Primer
NPTEL
Data Structures in Java
Coding Ninjas
Introduction to Java
Coding Ninjas
Panipat Institute of Engineering and Technology
B.Tech in Computer Science and Engineering
Bal Bharati Public School
High School Certification / PCM Focus
Hiten graduated with an exceptional 8.26 / 10.0 CGPA from PIET while simultaneously serving as a Java & DSA Teaching Assistant at Coding Ninjas, debugging algorithms and resolving over 300+ architecture tickets.