Open to backend and AI roles · Delhi

AnjaneyaTiwari

I build software that works beyond the demo.

Selected work ↓GitHub ↗LinkedIn ↗Email ↗

Backend, automation and AI engineer, and full-stack developer, in Delhi. I build API orchestration, agentic workflows and voice-AI infrastructure, along with robotics simulation and interactive 3D systems.

Selected work

Work

Eleven projects: five told as full case studies, and six more projects, each with its own diagram you can poke at. The case studies set out the problem, the approach, the trade-off and the result.

Measured a result from real runsIllustrative a simulation that explains the mechanism, not live data

  1. XENOM IntelligenceResearch where every insight cites its source.
  2. Rooftop Rush3D multiplayer racing game, live on the web. Google Play: tester access only.
  3. Email Triage AssistantGmail API calls cut 92.5% across 1,800+ messages.Measured
  4. LoadPulseAn async backend shedding load, with live p50 / p95 / p99.
  5. AgentForgeSeven agents; a CEO agent delegates to six specialists.
  6. Six more projectsDermaCam, AutoApply Bot, LLM Gate, Nudge, H.E.R.C.S, VitalAI

Built at Rootstock Technology

XENOM
Intelli­gence

Company research where every insight keeps a path back to its source.

Try it · pick a claim

SOURCE ASOURCE BSOURCE C 123
Illustrative Every insight keeps a link to the source that supports it, so a reader can check it. Abstract diagram, not a screenshot.
Problem
AI-generated research is hard to trust when you can't see where a claim came from.
Approach
A research and company-intelligence platform: it ingests, normalizes and deduplicates sources, extracts claims, and links every insight to its supporting citations. It supports competitor analysis and opportunity detection.
Trade-off
Auditability comes first. Semantic embeddings are optional and live search (Brave Search) depends on configuration, so the core pipeline runs without either. Docker configuration is included.
Result
Every insight carries a path back to its source. Built as part of my work at Rootstock Technology as an agentic research pipeline for news discovery, evidence ranking and source-backed intelligence.

React · TypeScript · FastAPI · PostgreSQL/pgvector · Groq

Real gameplay screenshot of Rooftop Rush: a car on a three-lane neon road between glowing towers, with a translucent ghost car ahead, plus score, speed, flight and nitro meters.

Tap a marker.

Real gameplay Real gameplay from my QA captures (Neon district). Tap the markers.

Flight and landing safety · schematic

Flight meter

ON GROUND. The meter recharges.

Illustrative Schematic of the mechanic from the game's rules, not game footage. Landing never touches down on an obstacle: if something is below the descent path, the car holds above it.

Independent project · Live demo

Rooftop
Rush

A 3D multiplayer racing game, live on the web. The Google Play build is in testing.

Problem
A browser 3D game has to stay stable through long sessions, and a multiplayer race has to stay fair.
Approach
A 3D racing game in TypeScript and Three.js with chase and first-person cameras, a GLB car model, three districts and combo scoring. Five-chapter Story, Endless and Multiplayer modes, plus Ghost Rival, which races a replay of your previous run.
Trade-off
A fixed-timestep loop and object pooling keep long sessions stable. Tracks are generated dynamically, with flight sections, collision and landing-safety logic, and district progression. Multiplayer runs on a separate Node.js WebSocket server that handles rooms, shared-seed tracks and real-time player updates, so the server, not the clients, decides results.
Result
Live on the web. The Google Play build is on a testing track, so it is available to approved testers only.
Credit
The 3D car model was made with Vi3W. The game code, roads, districts, story and effects are my own work.
Client · TypeScript, Three.js, Firebase HostingServer · Node.js, WebSockets

TypeScript · Three.js · Node.js · WebSockets · Firebase Hosting

Independent project · Aug 2026

Email Triage Assistant: 200 → 15

Email Triage Assistant: an inbox assistant that learns from corrections and never sends on its own.

Try it · drag the slider

15 API calls per inbox · 92.5% fewer

Measured Vermilion: calls still made. Faded: calls avoided by batching and local semantic search together. The 200 → 15 and 92.5% figures are measured across 1,800+ messages; the squares in between are a scrub, not extra data.
Problem
Triaging a busy inbox takes a lot of Gmail API calls, and automatic replies are risky.
Approach
A Gmail add-on, FastAPI dashboard and CLI for multi-user triage: priority scoring, deadline extraction, local semantic search and reply drafts. Rules run first, with an LLM fallback, and the system adapts to user corrections.
Trade-off
Replies are FAQ-grounded and saved as drafts only, never sent. OAuth 2.0 with PKCE and per-user data isolation. Local semantic search and batching replace API calls.
Result
Measured: API calls cut by 92.5% (200 → 15 per inbox) across 1,800+ messages. 59 regression tests, plus documented real-Gmail validation.

FastAPI · Google Apps Script · Groq · FastEmbed · OAuth 2.0 (PKCE)

Built during the Telogo internship

LoadPulse

Concurrency benchmarking you can watch in real time.

Try it · send a burst

p50p95p99 latency →
Illustrative A simulation, not measured data. Left to right: requests, token-bucket rate limiter (squares: tokens left; hollow dots are rejected, as the real system does with a 429 or 503), a pool of async workers (six drawn here), then a latency histogram. The real system also has a bounded queue, left out here for clarity. The dashed outline is the expected shape; p50 / p95 / p99 mark where half, 95% and 99% of requests finish.
Problem
A backend pushed past its capacity can crash or fall over. LoadPulse simulates that load and shows the service degrading gracefully instead, live.
Approach
A concurrency observability platform on FastAPI: a token-bucket rate limiter, a bounded queue and a fixed pool of async workers, with a React and Recharts dashboard fed over WebSockets.
Trade-off
Overload is rejected, not buffered forever. When capacity is exceeded, requests get a clean 429 (rate limited) or 503 (queue full) instead of being dropped silently or taking the service down.
Result
A live dashboard streams p50, p95 and p99 latency, queue depth, drop rate and active workers as a run happens, with an in-browser load generator and a CLI load tester.

FastAPI · asyncio · React · Recharts · WebSockets

Independent project · Jun – Jul 2026

Agent
Forge

A multi-agent operating system for running a company's functions.

Problem
Coordinating several specialised agents around one goal.
Approach
Seven agents (CEO, Sales, Marketing, Support, Research, Finance, Hiring) on FastAPI, Next.js and LLM APIs. The CEO agent decomposes goals and delegates to the specialists, and agents talk to each other.
Trade-off
Central delegation through a CEO agent. Agent memory is dual-layer, Redis plus PostgreSQL, and a digital-twin dashboard tracks MRR, revenue, burn rate and runway.
Result
Deployed with Docker on AWS EC2 and tested by 4–5 users.

FastAPI · Next.js · Redis · PostgreSQL · Docker · AWS EC2

Try it · step through, or inspect an agent

GOAL Sales Marketing Support Research Finance Hiring CEORedisPostgreSQL DIGITAL TWINMRR · revenue · burn · runway
Illustrative 5. Results flow into the digital-twin dashboard: MRR, revenue, burn rate and runway. Schematic of the documented design, not live data.

Experience, Feb 2025 – now

Experience

Each column is a month, Feb 2025 to now. The hatched bar is my current role.

Rootstock Technology

Research & Development Apprentice

Aug 2026 – present · New Delhi

  • Engineered a 500+ API orchestration layer for AI workflows: endpoints, routing, API discovery and integrations.
  • Built XENOM Intelligence, an agentic research pipeline for news discovery, evidence ranking and source-backed intelligence.
  • Built GPU-accelerated computer-vision pipelines with Qwen on 2× Tesla V100 32GB GPUs for image recognition and ad verification.
  • Developed AI-assisted 3D and robotics simulation workflows with Unity (C#), ROS, Gazebo and NVIDIA Isaac Sim, including robotic-arm simulations.
  • Created clean-room and smart-factory simulation environments in Unity (C#) to demonstrate industrial and robotics workflows.

Gleska Private Limited

Full-Stack Developer

Jun 2026 – Aug 2026 · New Delhi

  • Built the FastAPI/PostgreSQL backend for a real-time workforce marketplace: 7+ REST APIs, 9 data models, 12 migrations.
  • Implemented PostGIS geospatial matching and a fault-tolerant job workflow with offer expiry and dual-OTP verification.
  • The matching engine uses PostGIS ST_DistanceSphere with an adaptive 10–30 km search radius and 50/30/20 weighted candidate ranking.
  • The job workflow has six stages, with two-minute offer expiry, transactional state transitions and dual-OTP verification.
  • Integrated Cashfree payment and verification APIs for billing, webhook reconciliation and KYC.

Telogo Communications

Backend & AI Systems Intern

Sep 2025 – Mar 2026 · Noida

  • Architected an AI-powered IVR platform with a custom speech pipeline for Indian accents and multilingual calls.
  • Architected high-concurrency voice-AI infrastructure processing 1,000+ concurrent requests with async call processing (FastAPI, asyncio, worker pools), autoscaling and streaming inference, at under 2 seconds end to end.
  • Cut end-to-end voice latency with streaming transcription, model warm-up and response caching.
  • Built a real-time observability stack for multilingual speech systems, profiling latency, throughput, queue depth and worker utilization.
  • Built LoadPulse, a concurrency-benchmarking and observability platform with a React, Recharts and WebSockets dashboard.

Motivus Innovation

Software Development Intern

Feb 2025 – Jul 2025 · Noida

  • Built production backend services and data pipelines for AI-driven ESG platforms, optimizing database workflows across renewable-energy and carbon-accounting systems.
  • Prototyped AI/ML models for sustainability analytics and turned research into deployable features.

Expertise, by what I actually use

Languages
Python, TypeScript · JavaScript, SQL, C#, Dart, Bash
Backend & distributed systems
FastAPI, async programming, WebSockets, REST, system design · Flask, Django REST, Node.js, Express, NestJS, GraphQL, Celery, SQLAlchemy, JWT, Swagger/OpenAPI, webhooks, API gateway, distributed systems, Redis Streams, multithreading, rate limiting, caching, NGINX, Pytest, Postman
AI & model infrastructure
LLM applications, RAG, multi-agent systems, computer vision · VLMs, LangChain, LangGraph, MCP, Groq, OpenAI and Anthropic APIs, vLLM, Ollama, Hugging Face, Qwen, PyTorch, TensorFlow, Scikit-learn, NumPy, Pandas, OpenCV, CUDA, GPU inference, LoRA/QLoRA fine-tuning, MLflow, Jupyter Notebook
Databases
PostgreSQL, PostGIS, Redis · pgvector, Supabase, Firebase Firestore, MongoDB, MySQL, SQLite, Apache Kafka
Cloud & DevOps
Docker, AWS, GitHub Actions · Docker Compose, Kubernetes, Terraform, AWS Lambda, Microsoft Azure (App Services), GCP (Compute Engine and Cloud Run), Oracle Cloud, Firebase Hosting, GitLab CI/CD, Linux, Prometheus
Automation
n8n, Gmail API, OAuth 2.0 · Zapier, workflow orchestration, browser automation, Playwright, Selenium, Google Apps Script, APScheduler, third-party API integrations, Cashfree, Razorpay, VirusTotal, WHOIS
3D, mobile & robotics
Three.js, Unity · Flutter, React Native, ROS, Gazebo, NVIDIA Isaac Sim
Frontend
React, Next.js · Angular, Tailwind CSS, HTML5, CSS3

About

I usually end up working on the half of a problem a demo never shows: what happens when an offer expires, when one user's data has to stay out of another's, when a thousand calls arrive at once.

I'm a software engineer in Delhi, finishing a B.Tech in Computer Science while working in industry. My projects go from Postgres schemas and geospatial queries, through async workers and LLM pipelines, up to the interface people touch. I also build interactive 3D and robotics simulations: Rooftop Rush is a game I built and deployed, with its own multiplayer server, and at Rootstock I work with ROS, Gazebo, NVIDIA Isaac Sim and Unity.

I like measuring things. If I can't say what changed, I haven't finished.

Roles
Backend, automation & AI engineer (LLM applications, agentic workflows and APIs) · Full-stack developer (robotics simulation and interactive 3D systems)
Education
B.Tech, Computer Science (Core), Dr. A.P.J. Abdul Kalam Technical University, 2023–2027, Lucknow
Now
R&D Apprentice, Rootstock Technology
Recognition
HackIndia Spark 4, Round 2 (DermaCam, built in 36 hours) · Vibecon India by Y Combinator, Round 2 (10,000+ participants, with AutoApply Bot) · GSSoC and SSOC 2026 contributor
Certified
Zapier + n8n Automation Mastery · AI Engineer Bootcamp

How it shows up in the work

  • Async & distributed systems1,000+ concurrent voice requests in under 2 seconds, with async workers, autoscaling and streaming inference.Telogo
  • Orchestration & API designA 500+ API orchestration layer for AI workflows: endpoints, routing, discovery and integrations.Rootstock
  • Reliability & testing59 regression tests and real-Gmail validation behind a 92.5% cut in API calls.Email Triage
  • Retrieval & data pipelinesSources ingested, normalized and deduplicated, claims extracted, every insight linked to its citations, and evidence ranking in an agentic research pipeline.XENOM
  • Agentic workflowsA CEO agent decomposing goals across six specialists, with shared Redis and PostgreSQL memory.AgentForge
  • Real-time & performanceA fixed-timestep game loop, object pooling and a multiplayer race where the server decides results.Rooftop Rush

Contact

If you're building backend or AI systems and care about the parts demos skip, I'd like to hear about it.

LinkedIn ↗GitHub ↗Resume on request

Open to full-time backend and AI roles. Delhi, UTC+5:30.