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You will get Java/Sprint Boot developer to work on your requirement/bug fix

Hitesh U.Status: Offline
Hitesh U.
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Let a pro handle the details

Buy Web Application Programming services from Hitesh, priced and ready to go.
Hitesh U.Status: Offline
Hitesh U.
Preview imagePreview imagePreview image

Let a pro handle the details

Buy Web Application Programming services from Hitesh, priced and ready to go.

Project details

ššššœš¤šžš§š š“šžšœš”š§šØš„šØš š¢šžš¬:
āœ“ Spring Boot Microservices, Spring Boot Cloud, Spring Security
āœ“ AWS Integration (Elastic Beanstalk, EC2, RDS, Elastic Search, etc)
āœ“ Elastic Search / Integration / Querying
āœ“ Netflix Eureka, Netflix Ribbon, Netflix Feign, Docker
āœ“ RabbitMQ (Spring-AMQP), Kafka (Spring-Kafka and Kafka Stream), Spring Batch
āœ“ REST APIs integration
Programming Languages
JavaScript, Java, TypeScript
What's included
Service Tiers Starter
$500
Standard
$1,000
Advanced
$1,500
Delivery Time 5 days 10 days 15 days
Number of Revisions
124
Number of Pages
3610
Design Customization
Content Upload
Responsive Design
Source Code
Hitesh U.Status: Offline

About Hitesh

Hitesh U.Status: Offline
Agentic AI Developer | LLM Apps, RAG, Multi-Agent Systems
ahemedabad, IndiaĀ - 3:52 am local time
I build AI agents that do the work ā€” LLMs that plan, retrieve, call tools, and complete multi-step tasks reliably enough for real users. Not demos. Production systems.

15+ years shipping backends in fintech, e-commerce, fleet, and ride-sharing. The last two years focused on the agentic layer. That combination is the point: most AI prototypes break on contact with real traffic, real data, and real auth. Mine don't, because I've shipped the boring half of software for a decade.

What I do best
Turn manual workflows into reliable agents. Fix RAG that retrieves the wrong thing. Wire LLMs into existing systems ā€” your database, queue, auth, observability ā€” without creating a parallel stack nobody owns.

Selected work
Multi-agent workflow automation for a fintech platform ā€” replaced a 6-step manual review process, cut turnaround from 2 days to 15 minutes
RAG system over 200K+ internal documents with hybrid search and evals ā€” answer accuracy moved from 61% to 92%

Custom MCP servers connecting Claude to internal tooling for an e-commerce ops team
Spring Boot microservices powering a ride-sharing platform at production scale

Stack
LangGraph, LangChain, LlamaIndex, CrewAI Ā· Claude, GPT-4/5, Llama 3
RAG, MCP servers, tool use, structured outputs, evals
Vector DBs: Pinecone, Weaviate, pgvector, Milvus
Java / Spring Boot Ā· Python / FastAPI Ā· Kafka Ā· AWS Ā· Docker Ā· Kubernetes

Background
35+ projects delivered, 5-star feedback. B.E. in Computer Engineering. Work daily in Claude Code and Cursor ā€” agentic tooling is how I build, not just what I build.

How I work
I'll push back if your agent will hallucinate, your retrieval will miss, or your tool schemas will confuse the model ā€” before writing code, not after. I think about latency, cost, retries, and what happens when the model provider goes down. The happy path is the easy half.

Steps for completing your project

After purchasing the project, send requirements so Hitesh can start the project.

Delivery time starts when Hitesh receives requirements from you.

Hitesh works on your project following the steps below.

Revisions may occur after the delivery date.

Initial Screening Phase

We can discuss share my expertise/skills and understand your requirement in high-level workflow

Review the work, release payment, and leave feedback to Hitesh.