Lakshit Wasan · Backend & Distributed Systems Engineer

I build backend systems thatscale & stay up.

Production microservices and distributed APIs — owned end-to-end from system design and API contracts to containerized deployment, monitoring and performance.

View workBackend SWE resume↓ PDF

One engineer, two lenses — use the toggle to switch focus between AI and backend.

About

Software engineer specializing in backend systems, distributed APIs and cloud-native applications.

I'm Lakshit Wasan, based in New Delhi. I build and own production services end to end — from system design and API contracts through deployment, monitoring and performance tuning — on a strong foundation of microservices, async processing and scalable database design. What I care about most is systems that stay reliable and fast as they grow, and code that the next engineer can actually reason about.

99.9%
uptime on production systems I own
3+
client platforms shipped at Nebula9.ai
20–40%
latency & manual-ops time reduced

Currently

Software Engineer — Backend & AI Systems

Nebula9.ai · since Aug 2025

Education

B.Tech, Computer Science & Engineering

BML Munjal University, Haryana · 2021 – 2025

GPA 8.4 / 10.0

Based in

New Delhi, India

Selected work

Selected work for Backend / Fullstack

Prioritized and described for a backend / fullstack audience — switch lenses to re-rank them. Most were built in client and production environments, so the source is proprietary; I'm always happy to walk through the architecture and trade-offs.

Enterprise Event Logistics Platform

Microservices for large-scale event operations

Featured

A microservice backend for large-scale event logistics, with independently scalable booking and user services and zero-downtime releases. Secure FastAPI REST APIs, optional natural-language schedule querying via LLM APIs, and AWS deployment with observability tooling that cut debugging time by 30%.

0downtime deploys−30%debugging time
FastAPIPostgreSQLMicroservicesDockerAWS

Analytics & Ranking Platform

Deterministic, auditable athlete rankings

A backend that automates official athlete rankings for a sports federation with full transparency and auditability. A rule engine converts complex ranking criteria into deterministic algorithms over an optimized PostgreSQL schema built for fast recomputation, with Celery async processing cutting generation time by ~50%.

−50%ranking time100sof athletes
FastAPIPostgreSQLCeleryDocker

AI-Driven Financial Data Platform

Production RAG for real-time financial insight

A FastAPI + React platform powering a GenAI chatbot for real-time financial data. Ingestion and retrieval APIs combine insights across multiple databases for scenario-based analysis; upgraded from prototype to production architecture, cutting query latency by ~25%.

−25%query latencyhybridsearch retrieval
FastAPIPostgreSQLRAG PipelinesVector DBsReact

AgentZero

Autonomous AI coding agent

A local-first coding agent architected as a multi-agent state machine (planning → execution → validation). Built around a secure Docker sandbox, symbol-level code indexing over a vector DB, and an adaptive model-routing layer that balances reliability against cost.

symbol-levelcode retrievalself-healingexecution loopsandboxedDocker isolation
PythonMulti-AgentTree-sitterVector SearchDockerLLM Routing

Toolkit

Skills & stack

Groups most relevant to your current lens are highlighted.

AI Systems & LLMOps

  • LangChain
  • LangGraph
  • Google ADK
  • Snowflake Cortex
  • Autogen
  • RAG pipelines
  • Multi-agent systems
  • Prompt engineering
  • A2A protocols

Vector Search & Retrieval

  • FAISS
  • PGVector
  • Pinecone
  • ChromaDB
  • Hybrid retrieval
  • Embedding generation

Backend & APIs

  • FastAPI
  • Node.js
  • Express.js
  • REST APIs
  • Microservices
  • Async processing
  • Caching
  • Celery

Data

  • PostgreSQL
  • MSSQL
  • MongoDB
  • Snowflake

Cloud & DevOps

  • Docker
  • AWS
  • GCP
  • CI/CD
  • GitHub Actions

Languages & Frontend

  • Python
  • JavaScript
  • C++
  • React.js

Track record

Experience

  1. Software Engineer — Backend & AI Systems

    Aug 2025 – Present

    Nebula9.ai · Gurgaon, India

    • Design and deploy backend services powering LLM-driven enterprise workflows, cutting manual operations time 30–40% across 3+ client platforms.
    • Own multi-tenant delivery end-to-end — HLD/LLD, API contracts and staged rollouts with observability tooling holding 99.9% uptime.
    • Built modular AI service layers (embeddings, vector indexing, hybrid search) that improved retrieval accuracy and cut inference latency ~20%.
    • Shipped conversational analytics agents over Snowflake semantic views using Cortex Agents and LLM routing.
    FastAPIPostgreSQLLangGraphSnowflake CortexDockerAWS

  2. Software Engineer Intern — AI-Enabled Backend

    Oct 2024 – Jul 2025

    Nebula9.ai · Gurgaon, India

    • Migrated a legacy MERN architecture to FastAPI + PostgreSQL, improving performance and maintainability ~35% and enabling async model-serving.
    • Built ingestion, embedding-generation and document-chunking pipelines for vector search, improving retrieval throughput and relevance.
    • Developed secure REST layers abstracting LLM calls, enabling real-time insights for financial and operational dashboards.
    FastAPIPostgreSQLLangChainDockerAWSMERN

  3. Web Developer Intern

    Jun 2022 – Aug 2022

    Coding Blocks · Delhi, India

    • Delivered 6+ production applications with secure authentication, optimized data models and MongoDB query efficiency improved up to 25%.
    Node.jsExpress.jsMongoDBMongoose

Beyond shipping

Publications & certifications

Peer-reviewed publication

Explainable ML for Peptide Therapeutics

Co-authored a peer-reviewed study presenting an interpretable ML framework for identifying antimicrobial peptide candidates from physicochemical properties, powering the Pred-AHCP web server for therapeutic peptide design.

Read the paper — J. Chem. Inf. Model.

Certification — DeepLearning.AI

Natural Language Processing with Classification & Vector Spaces

Foundational NLP: text classification, vector-space models and word embeddings.

Certification — IBM

Introduction to Artificial Intelligence (AI)

Core AI concepts, applications and the modern ML landscape.

Get in touch

Let's build something reliable.

Open to backend / fullstack roles and interesting engineering problems. Send a message and it lands straight in my inbox — I usually reply within a day.

Email
lakshitwasan31@gmail.com
GitHub
lakshitwasan
LinkedIn
lakshitwasan
Resume
AI Systems ↓Backend ↓