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Shreesh-Sree/README.md
Typing intro
name: Sreesanth R
role: Software Engineer
location: India
focus:
  - AI systems
  - backend engineering
  - cloud-native workflows
currently_building:
  - retrieval and orchestration systems
  - event-driven applications on AWS
  - full-stack products with strong backend architecture
looking_for:
  - software engineering internships
  - backend engineering roles
  - AI engineering roles

Portfolio LinkedIn Email GitHub

About

I build systems where APIs, data, models, and deployment meet. Most of my projects live at the intersection of backend services, AI-enabled workflows, and cloud infrastructure, with a strong preference for clean interfaces, explicit failure handling, and software that stays understandable as it grows.

System Profile

input         -> request, event, or user workflow
service layer -> API contracts, auth, validation, orchestration
data layer    -> SQL, vector search, document stores, queues
intelligence  -> retrieval, ranking, reasoning, prediction
output        -> decisions, automations, recommendations, dashboards

Build Map

flowchart LR
    A["User or system signal"] --> B["API or ingestion layer"]
    B --> C["State, queues, and storage"]
    C --> D["ML or LLM reasoning"]
    D --> E["Workflow, decision, or insight"]
    E --> F["Observable deployed product"]
Loading

Flagship Builds

AWS Lambda API Gateway SQS DynamoDB Bedrock Terraform

Event-driven grievance workflow platform built around secure intake, asynchronous processing, and AI-assisted resolution pipelines on AWS.

FastAPI Streamlit FAISS SQLAlchemy Ollama Docker

AI engineering workspace for retrieval, evaluation, privacy-aware workflows, and local LLM-backed experimentation with deployment-friendly structure.

FastAPI React Firebase PostgreSQL pgvector Groq

Career-learning platform that combines application services, semantic resource discovery, and personalized workflow design across frontend and backend layers.

PyTorch LangGraph Ollama PostgreSQL Docker

Scientific optimization system combining physics-informed modeling, constrained search, and agentic orchestration for additive manufacturing experimentation.

Technical Matrix

Layer Tools
Languages Python, TypeScript, JavaScript, Java, C, C++
Backend FastAPI, Node.js, REST APIs, auth, async workflows, service design
Data PostgreSQL, pgvector, DynamoDB, Firebase, SQLAlchemy, FAISS
AI and ML LangGraph, Ollama, PyTorch, TensorFlow, scikit-learn, RAG
Cloud and DevOps AWS Lambda, API Gateway, SQS, S3, Terraform, Docker, GitHub Actions, Linux
Product React, Next.js, Streamlit, Vite

Coding Profiles

LeetCode Codeforces CodeChef HackerRank GeeksforGeeks Code360

Activity

GitHub stats GitHub streak
Contribution graph

Engineering Notes

const engineeringPrinciples = [
  "Design data flow before interface polish",
  "Keep failure paths explicit and observable",
  "Use AI where it improves decisions, not just demos",
  "Treat deployment and security as product features"
];

Open to software engineering, backend, AI engineering, and platform opportunities.

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