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
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.
🟢 Online
At the keyboard and replying fast.
Peak throughput
0.0M
requests a second, on a web server I wrote from scratch
My local time
IST · UTC+5:30
0
tests across the systems projects
Languages
- JavaScript96
- CSS83
- TypeScript73
- HTML26
- Python21
Repositories
0
Upstream contributions
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.
IIITDM Kancheepuram
B.Tech, Computer Science & Engineering · 2022 – 2026
SDE I @ Xenotix Labs
Building ride-hailing, food-subscription and community platforms that are live and taking payments.
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.
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
Repositories created
0
75 public · 55 private · excludes 49 contribution forks
Tests written
0
Every systems project ships its own suite.
Where those tests live
- 300DSA & systems
- 47Coding agent
- 35Inference server
- 30HTTP server
- 23Vector DB
- 19Task queue
Five roles. Two years. Real users waiting on it.
Aug 2026 – Present
Remote
currentXenotix 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 NativeMar 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 memoryFeb 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 DBDockerNov 2024 – Present
Remote
currentFreelance
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.jsSupabasePostgreSQLn8nPaymentsOct 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
Rate limiter
mirrors Stripe / Cloudflare
Bloom · CMS · HyperLogLog
mirrors Redis PFCOUNT
Autocomplete (Trie, BK-tree)
mirrors Search suggest
Search engine (BM25)
mirrors Lucene
Diff (Myers)
mirrors git diff
LSM key-value store
mirrors RocksDB
B-tree index
mirrors PostgreSQL
Consistent hashing
mirrors DynamoDB
Job scheduler (Kahn)
mirrors Airflow
Route planner (A*)
mirrors Maps routing
Mini git (Merkle)
mirrors git
Compressor (Huffman, LZ77)
mirrors gzip
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.
My fixes run inside tools you already use.
28 contributions accepted or under review at LLVM, Docker, HuggingFace, Ray, Kubernetes and more. Real bugs — a crash, a race condition, silently wrong results — not spelling corrections.
- llvm/llvm-project#216155+27 −4open[Clang] Fixed a crash on forward-declared enums given an underlying type via __attribute__((mode(TI))) — the mode attribute marked an undefined enum complete.
- llvm/llvm-project#216157+337 −0open[InstCombine] Folds ucmp/scmp of no-wrap ops sharing an operand — order-preserving ops are a no-op on three-way compares.
- oras-project/oras#2126+128 −37mergedFixed a 'send on closed channel' panic: net/http's writeLoop kept reading a tracked request body after the update channel was closed.
- confident-ai/deepeval#3055+216 −10openMade DAG metric scoring deterministic — multiple reachable verdicts produced order- and sync/async-dependent scores for identical inputs.
- modelcontextprotocol/typescript-sdk#2618+97 −6openCache corruption on the failure path: a failed listTools() refresh silently disabled output validation in callTool().
- docker/docker-agent#656+61 −5mergedTUI notifications overflowed small terminals; added an 80-col clamp, a notification Type enum and error styling.
I can explain what I build.
The rules I hold myself to.
If something can fail, I test that it fails safely.
Bad configuration should stop a deploy, not wake someone at 3am.
A corrupted file gets refused, never quietly misread.
Every bug should be reproducible on demand, never 'sometimes'.
Swapping out a service should be a config change, not a rewrite.
A slow background job must never slow down someone's request.
Trust a heartbeat, not the network's word for it.
Prices live in config, so a business change isn't an engineering change.
What I actually work with.
Everything listed here is something I have shipped with, not something I have only read about.