🟢Online· live

SiddarthaNallella

AI-Native Full-Stack Engineer. I build AI products people actually use — for real companies, real users, and real deadlines.

0M
requests a second, on a web server I wrote from scratch
0+
bookings taken by a platform I built
0
fixes accepted into major open-source projects
0
projects built and documented

At the keyboard and replying fast.see what I'm up to

LLVMApache DataFusionDockerHuggingFaceRayKubernetesMCP SDKMicrosoft AspireORASDeepEvalpromptfooValePyMCpandasThunderbirdFirebaseOrchardCoreMDNastropyQwik UIDrizzlePHP-CS-FixerLLVMApache DataFusionDockerHuggingFaceRayKubernetesMCP SDKMicrosoft AspireORASDeepEvalpromptfooValePyMCpandasThunderbirdFirebaseOrchardCoreMDNastropyQwik UIDrizzlePHP-CS-Fixer

The short version.

What I am doing right now, what I have built, and what has been accepted into other people's projects — on one screen.

right now

🟢 Online

At the keyboard and replying fast.

Hyderabad, India open to roles

Peak throughput

0.0M

requests a second, on a web server I wrote from scratch

My local time

--:--:--

IST · UTC+5:30

100%

0

tests across the systems projects

Languages

  • JavaScript96
  • CSS83
  • TypeScript73
  • HTML26
  • Python21

Repositories

0

202420252026

Upstream contributions

0pull requests

14 merged · 14 in review

Shipped & documented

0

projects on this site, each with a public repo

I build software that companies pay for.

Two years shipping AI products to real users, plus the low-level engineering most people leave to a library. Below is what that means in practice.

I ship products, not prototypes

Two years building AI features that companies actually launched — an assistant inside a health-tech platform, automated document workflows at Quanta Global, a prototype network agent at Ericsson, and a freelance booking platform that handled over 12,000 orders.

I build the hard parts myself

When something has to be fast or has to stay up, I write it rather than reach for a library. A database that survives servers crashing. A web server handling 2.8 million requests a second. An AI model runner that needs no graphics card.

I make sure it does not break

Every project ships with its own tests — 454 of them across my systems work. I find real bugs in other people's code too: 28 of my fixes have been accepted by the teams behind LLVM, Docker, HuggingFace, Ray and Kubernetes.

Education

IIITDM Kancheepuram

B.Tech, Computer Science & Engineering · 2022 – 2026

Right now

SDE I @ Xenotix Labs

Building ride-hailing, food-subscription and community platforms that are live and taking payments.

Looking for

My next role

AI products, backend engineering, or full-stack. Remote or Hyderabad — happy to walk through any project here.

What I am working on this month.

I update this myself whenever it changes. The status light at the top of the page comes from the same place.

🟢Online· live

Focus

Shipping ride-hailing and subscription-commerce backends at Xenotix Labs, and keeping a freelance pipeline alive on the side.

Learning

RL environments, evals and benchmarks — how frontier labs build and grade agent tasks.

Building

game changing for aspirants

Two years of work, counted.

Pulled straight from my GitHub account. Nothing rounded up.

Languages across every repository

JavaScript
96
CSS
83
TypeScript
73
HTML
26
Python
21
Shell
10
C++
7
PL/pgSQL
6
Kotlin / Swift
5
CMake
4

Repositories created

0

24
2024
63
2025
43
2026

75 public · 55 private · excludes 49 contribution forks

Tests written

0

Every systems project ships its own suite.

Where those tests live

  • 300
    DSA & systems
  • 47
    Coding agent
  • 35
    Inference server
  • 30
    HTTP server
  • 23
    Vector DB
  • 19
    Task queue

Open-source reach

0pull requests

across 25 projects in 24 orgs

0merged0in review

Five roles. Two years. Real users waiting on it.

  1. Aug 2026 – Present

    Remote

    current

    Xenotix Labs

    Software Development Engineer I
    • Architected a ride-hailing and parcel delivery backend as a two-process system — API gateway and BullMQ workers scale independently, so job throughput never blocks request latency.
    • Integrated a payment gateway end to end: signed callback verification per signing mode, platform-specific callback keys, and a runtime test/live toggle that removed the redeploy step.
    • Delivered a subscription commerce platform against a client-signed spec, encoding recurring cycles, pause limits, wallet gates and tiered delivery fees as enforced data-model invariants.
    • Shipped a multi-tenant community management suite and remediated two cross-tenant data-exposure defects in the authorization layer.
    Node.js 24TypeScriptExpress 5MongoDBRedisBullMQSocket.IONext.jsFlutterReact Native
  2. Mar 2026 – Aug 2026

    Bengaluru, India

    Ericsson

    Research Intern, Compute & Software
    • Engineered a prototype AI agent for 5G networks with FastAPI, LangGraph and FastMCP — natural-language-driven user session creation and modification from application-layer intent.
    • Benchmarked agent workflow configurations to cut end-to-end response latency.
    • Researched LLM serving, AI Agent Operating Systems, dynamic scheduling and agentic memory (A-Mem), folding disaggregated-serving strategies into prototype designs.
    FastAPILangGraphFastMCPLLM servingAgent memory
  3. Feb 2025 – Dec 2025

    Remote

    Quanta Global

    Software Developer Intern
    • Built and deployed production LLM workflows with LangChain, LangGraph, Google GenAI SDK and Vercel AI SDK, automating manual processing through reasoning pipelines.
    • Designed enterprise RAG systems on Pinecone, Astra DB and MongoDB that raised semantic retrieval precision over keyword search.
    • Optimized REST APIs across FastAPI, Express, PostgreSQL and Prisma; containerized AI microservices with Docker.
    Next.jsFastAPISupabaseLangChainPineconeAstra DBDocker
  4. Nov 2024 – Present

    Remote

    current

    Freelance

    Full-Stack Developer
    • Engineered an event platform that handled 12,000+ bookings — secure payments, automated SMS, a full admin dashboard and an enquiry chatbot.
    • Delivered real-estate, EdTech and retail platforms with automated email workflows and conversational enquiry capture, plus custom n8n backend automations.
    Next.jsSupabasePostgreSQLn8nPayments
  5. Oct 2024 – Dec 2024

    Remote

    Clinics on Cloud

    Health-Tech Platform Revamp
    • Migrated the core health-tech platform's legacy interfaces to a responsive React + Tailwind application.
    • Built metrics-driven internal dashboards and shipped a Python/REST AI assistant automating internal workflows and patient queries.
    ReactTailwindPythonPostgreSQL

Things I have built.

Products people use, and the machinery underneath them. Every card links to the code — nothing here is a slide deck.

I rebuilt the building blocks hiding inside databases, caches and search engines.

Thirteen of them, written from scratch — each with its own tests and a measurement against the simpler approach it replaces.

LRU / LFU cache

mirrors Redis maxmemory

01

Rate limiter

mirrors Stripe / Cloudflare

02

Bloom · CMS · HyperLogLog

mirrors Redis PFCOUNT

03

Autocomplete (Trie, BK-tree)

mirrors Search suggest

04

Search engine (BM25)

mirrors Lucene

05

Diff (Myers)

mirrors git diff

06

LSM key-value store

mirrors RocksDB

07

B-tree index

mirrors PostgreSQL

08

Consistent hashing

mirrors DynamoDB

09

Job scheduler (Kahn)

mirrors Airflow

10

Route planner (A*)

mirrors Maps routing

11

Mini git (Merkle)

mirrors git

12

Compressor (Huffman, LZ77)

mirrors gzip

13

Proof it actually works.

Real output from my own test suites. Pick a tab and watch one run — every number on this site comes from a test like these.

The rules I hold myself to.

If something can fail, I test that it fails safely.

Distributed database

Bad configuration should stop a deploy, not wake someone at 3am.

Ride-hailing backend

A corrupted file gets refused, never quietly misread.

Vector database

Every bug should be reproducible on demand, never 'sometimes'.

Simulation testing

Swapping out a service should be a config change, not a rewrite.

ML pipeline

A slow background job must never slow down someone's request.

Two-process architecture

Trust a heartbeat, not the network's word for it.

Job scheduler

Prices live in config, so a business change isn't an engineering change.

Subscription platform

What I actually work with.

Everything listed here is something I have shipped with, not something I have only read about.

C++20PythonTypeScriptRustGoLangGraphRaftHNSWepollAVX2gRPCQdrantNeo4jPostgreSQLRedisMongoDBFastAPIExpressNext.jsReactTailwindThree.jsFlutterReact NativeDockerAWSBedrockGeminiGroqMCPLangfuseRAGASBullMQRabbitMQPrometheusSupabasePrismaDrizzleSnowflakeFAISSPineconeLLVMKuberneteswhisper.cppGGUFSIMDWALPorcupine

Languages

C++20CPythonTypeScriptJavaScriptGoRustSQL / PL-pgSQLDartTCL

AI / LLM

LangGraphLangChainMCPGraph RAGHybrid dense + BM25RRF fusiontree-sitterStructured outputsTool callingLangfuseRAGASRed-team evalsBedrockGeminiGroqVercel AI SDKwhisper.cpp

Systems & distributed

RaftWAL / fsync orderingConsistent hashingDeterministic simulationPorcupinegRPCepoll ETSO_REUSEPORTsendfile(2)AVX2 + FMAmmapASan / TSanCMake

Backend & data

FastAPIExpress 5Node.js 24Socket.IOBullMQRabbitMQRedisPostgreSQLMongoDBNeo4jQdrantPineconeSupabasePrismaDrizzleSnowflakeFAISS

Frontend & mobile

Next.js 16React 19Server ComponentsTailwind v4shadcn/uiRadix UITanStack QueryFramer MotionThree.jsFlutterReact NativeExpo

Cloud & platform

AWS LambdaAPI GatewayS3TextractVercelDockerGitHub ActionsPrometheusn8n