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01

Software Engineer · Pune · Open to opportunities

Pranav
Chikte

I build agentic AI backends — systems that reason through failure, coordinate tools, and stay reliable at production scale.

Currently building with Claude Code and the Anthropic SDK — learning MCP tool patterns from the ground up.

github.com/pranavchikteResume
02

Selected Work

01

2024

Live

CineScope

Full-stack movie platform with conversational recommendations, Redis caching, and secure token rotation.

FastAPI · PostgreSQL · Redis · SQLAlchemy 2.0 · Gemini Pro

Case StudyGitHubLive
02

2024

Live

Finsight AI

AI-powered expense manager with async processing, robust auth, and production-ready full-stack deployment.

Flask · Celery · Redis · Gemini API · MongoDB

Case StudyGitHubLive
03

About

"Reliability is a feature, not an afterthought."

AI & Data Science background, but what I keep returning to is the infrastructure layer — async pipelines, retry logic, and tool-coordination patterns that make AI systems actually work in production. Drawn to the space where LLM reasoning meets backend reliability.

01

Agentic AI

Multi-step LLM pipelines, tool-use, retry patterns, async orchestration

02

Claude Code

Anthropic SDK, MCP servers, agentic coding workflows

03

Backend Systems

FastAPI, Celery, Redis, PostgreSQL, Docker, async architecture

04

Stack

AI / AgenticClaude Code · Anthropic SDK · MCP · Tool Use · Gemini API
BackendPython · FastAPI · Flask · Celery · Redis · PostgreSQL · MongoDB
DeployDocker · DigitalOcean · Vercel · GitHub Actions
FrontendNext.js · TypeScript · React · Tailwind CSS
05

Now

WorkingTata Consultancy Services, Pune — Digital / IAE
BuildingAnthropic SDK + MCP tool patterns for agentic workflows
SeekingGenAI backend roles — CRED, Razorpay, Groww tier
ReadingAnthropic research on agentic systems and MCP architecture
06

Let's talk.

chiktepranav1378@gmail.com
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© 2026 Pranav ChiktePune, Maharashtra