I BUILDINTELLIGENTBACKEND SYSTEMS.
Fast APIs. AI agents. Scalable infrastructure. Production systems.
WHO IS BEHIND THE SYSTEM?
Engineering philosophy, autonomous agents, and systems-level mindset.
I'm Tejas Jagdale, a backend developer focused on building reliable APIs, microservices, and AI-powered applications.
My work focuses on backend development with Python, FastAPI, TypeScript, Hono, PostgreSQL, and Redis.
I independently built a multi-agent startup validation workflow using LangChain and LangGraph for question generation, web research, and report generation.
I also build backend services for notifications, media, tracking, authentication, caching, rate limiting, and application storage, with hands-on AWS and Docker experience.
Backend Microservices
Built core, notification, media, tracking, and internal backend services using FastAPI, Hono, PostgreSQL, Redis, and TypeScript.
Multi-Agent AI
Independently built LangChain and LangGraph workflows for question generation, web research, and report generation.
API Performance
Used Redis caching and SlowAPI rate limiting, with sub-50 ms response times on most tested APIs.
Secure Backend
Implemented JWT, JWE, RBAC, token-based access control, and AWS S3 storage integration.
TEJAS JAGDALE
BACKEND DEVELOPER
THE STACK
Technologies I use to build backend systems and AI-powered applications.
Python
Primary language for backend APIs and AI applications
Backend & Core
Backend APIs, microservices, async services, and database integration
AI & Agent Systems
Multi-agent workflows, LLM integrations, tools, and structured outputs
Infrastructure & Cloud
Containers, caching, asynchronous jobs, and AWS deployment
Security & Engineering
Authentication, authorization, API reliability, and database performance
ENGINEERING EXPERIENCE
Backend development, microservices, and AI application engineering.
Backend Developer
Built backend APIs, microservices, and AI-powered workflows using Python, TypeScript, FastAPI, Hono, PostgreSQL, Redis, and LangChain/LangGraph.
- ✓Sub-50 ms response times on most tested APIs using Redis caching and rate limiting.
- ✓Independently built a multi-agent workflow for question generation, research, and report generation.
SYSTEMS I'VE BUILT
Distributed platforms, autonomous agent graphs, and high-concurrency microservices engineered for production resilience.
Starts Club
AI-Powered Startup Validation Platform
Backend for an AI-powered startup validation platform with multi-agent workflows for dynamic question generation, web research, market analysis, and business report generation.
ADDITIONAL PRODUCTION ARCHITECTURES
1 SYSTEMS DEPLOYEDHOW I BUILD AI WORKFLOWS.
Multi-agent execution for structured question generation, research, and report generation.
DETERMINISTIC AGENTIC STATE ENGINE
A practical multi-agent workflow built with LangChain and LangGraph, using external research tools, structured outputs, and persistent application state.
USER IDEA — Startup Idea
NODE RESPONSIBILITY:
Receives the startup idea and relevant application context.
EXECUTION MECHANISM:
The backend validates and passes the request into the AI workflow.
BEHIND THE API
The backend building blocks I have worked with in real projects.
Redis
ARCHITECTURAL ROLE & OPERATION:
Used for API caching, rate limiting, and asynchronous notification processing.
KEY RESPONSIBILITIES:
- ›API response caching
- ›Rate limiting support
- ›BullMQ-backed notification processing
BUILDING IN PUBLIC
Selected backend and AI projects available on GitHub.
CONTRIBUTION MATRIX // RECENT PRODUCTION SPRINTS
PRIMARY CODEBASE DISTRIBUTION
RECENT COMMIT & ARCHITECTURE DISPATCHES
Multi-vendor e-commerce backend with RBAC, PostgreSQL, SQLAlchemy, Alembic, and MinIO.
Deployed URL shortener with Redis caching, JWT authentication, Docker, Nginx, and AWS EC2.
AI-powered startup validation backend using LangChain, LangGraph, OpenAI/xAI, web search, and Langfuse.
CURRENTLY FOCUSED ON
Backend engineering, AI systems, and deeper infrastructure skills.
Multi-Agent AI Workflows
FOCUS: LangGraph & Agent Orchestration
Building practical multi-agent workflows with structured outputs, tool calling, web research, and persistent backend state.
Backend Performance
FOCUS: Caching & Query Optimization
Working with Redis caching, API rate limiting, PostgreSQL indexing, and query optimization to improve backend performance.
Microservices
FOCUS: Async & Real-Time Services
Developing backend services using FastAPI and Hono with BullMQ, Celery, Socket.IO, and Redis.
THE ENGINEERING JOURNEY
Comprehensive academic foundations and verified industry engineering trajectory.
ACADEMIC SPECIALIZATION
Master of Computer Applications (MCA)
Institute of Management and Career Courses (IMCC) — Pune, India
Master's degree in Computer Applications.
Bachelor of Computer Science (BCS)
Shri Saibaba Senior College — Shirdi, India
Bachelor's degree in Computer Science.
CORE COMPETENCIES SUMMARY
Asynchronous API architecture in FastAPI, database schema design & indexing in PostgreSQL, distributed caching with Redis, message queues with Celery, and Linux containerization.
Deterministic agent state machines using LangGraph, semantic search & hybrid retrieval (RAG) with ChromaDB and BM25, and structured prompt engineering with function calling.
Multi-stage Docker builds, AWS cloud deployment (EC2, S3, RDS, ECS), Nginx reverse proxying, SSL termination, and automated CI/CD pipelines via GitHub Actions.
OFFICIAL RESUME / CV
Full chronological employment, patents, publications, and verified production achievements.
LET'S BUILD SOMETHING.
Have a backend, AI, or infrastructure problem worth solving?