Lakshit Wasan · AI Systems & LLMOps Engineer

I build AI systems thatreason, retrieve & route.

LLM-powered APIs, RAG pipelines and multi-agent systems in production — from prompt and retrieval design to routing, safety layers and observability.

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

About

Software engineer specializing in backend architecture and AI-enabled systems.

I'm Lakshit Wasan, based in New Delhi. I build scalable microservices, LLM-powered APIs, RAG pipelines and multi-agent systems on cloud infrastructure — and I own them end to end, from system design and API contracts through deployment, observability and performance. What I enjoy most is turning ambiguous product ideas into services that stay accurate, fast and safe once real users hit them.

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 AI Systems

Prioritized and described for a ai systems 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.

AgentZero

Autonomous AI coding agent

Featured

A local-first autonomous coding agent built on a multi-agent state machine spanning planning, execution and validation. AST-aware semantic retrieval (Tree-sitter + vector DB) gives high-precision code context at the symbol level, and a self-healing execution loop runs inside a secure Docker sandbox with adaptive model routing for reliability and cost.

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

Conversational Analytics Platform

Natural-language querying over Snowflake

A conversational analytics platform for natural-language interaction over multi-domain marketing & retail datasets on Snowflake. Strategy-specific LLM agents sit over semantic views (UMM, MTA, Sonic, Retail, EDM) with intent routing and dynamic tool selection, turning simulation and optimization workflows into conversational execution — deployed via Streamlit on Snowflake.

5strategy agentsmulti-domainNL querying
Snowflake CortexCortex AgentsStreamlitLLM RoutingPrompt Engineering

AI-Driven Financial Data Platform

Production RAG for real-time financial insight

A production RAG system for real-time financial insight — ingestion, vector indexing, hybrid retrieval and LLM-orchestration APIs. Tuned embedding retrieval and batching to cut model-query latency by ~25%.

−25%query latencyhybridsearch retrieval
FastAPIPostgreSQLRAG PipelinesVector DBsReact

Enterprise Event Logistics Platform

Microservices for large-scale event operations

A microservice backend for large-scale event logistics with an optional natural-language interface — LLM APIs let operators query schedules conversationally over independently scalable booking and user services.

0downtime deploys−30%debugging time
FastAPIPostgreSQLMicroservicesDockerAWS

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 ai systems roles and interesting engineering problems. Send a message and it lands straight in my inbox — I usually reply within a day.

LinkedIn
lakshitwasan