SUMAN PAUDEL · SENIOR AI ENGINEER · NEPAL

Suman Paudel

I design and ship production voice AI, RAG, LLM, and machine learning systems—from sub-second agents handling 2,000+ daily calls to GPU-backed retrieval platforms with 95% accuracy.

— suman@paudel:~/manifesto —

▊

LATENCY

<900ms

UPTIME

99.9%

CALLS/DAY

2000+

ACCURACY

95%

$ scroll --down --to=manifesto▼

suman@paudel:~$ cat README.md

// WHOAMI

Sr AI Engineer · Voice AI · RAG · Infrastructure · 5 years in the trenches

I'm a Nepal-based AI and machine learning engineer who builds systems that listen, understand, and respond — at scale. Currently a Senior AI Engineer at Leapfrog Technology, where I architect voice agents handling 2000+ daily calls with sub-second latency, and build RAG systems that reason across millions of manufacturing documents.

Five years across data science, machine learning, and voice engineering. From fine-tuning vision models to orchestrating multi-region LiveKit infrastructure. From winning international NLP competitions to shipping production healthcare AI.

$ cat /etc/skills

Languages:

PythonSQLRTypeScriptGoRust

ML / DL:

PyTorchTensorFlowscikit-learnHuggingFacepandasnumpyJAX

LLMs & AI:

LangChainLlamaIndexCrewAILangGraphGPT-OSS-20BQwen3LlamaMixtralClaudeGemini

Voice AI:

LiveKitDeepgramWhisperElevenLabsCartesiaWebRTCSIP TrunkingTwilioTelnyxPipecat

RAG & Search:

FaissChromaPineconeMilvusElasticsearchBM25Hybrid SearchRe-ranking

Infra & MLOps:

AWS (EC2/EKS/ECS)AzureAlibaba CloudKubernetesHelmDockervLLMSGLangGitHub ActionsMLflow

Databases:

PostgreSQLMongoDBInfluxDBRedisSupabaseSQLite

suman@paudel:~$ cat /var/log/experience

Senior AI Engineer

Leapfrog Technology, Inc

Apr 2025 — Present

Manufacturing RAG + SQL Agent: vLLM platform with GPT-OSS-20B, Qwen3-4B embeddings, Qwen3-VL-8B on H100/A100/A40 GPUs. LangGraph orchestration. 95% retrieval accuracy, 78% complex reasoning.
Document Processing Engine: Fine-tuned DeepSeek OCR, PaddleOCR, OLMO-v2, Qwen3-8B OCR using SFT/DPO. Improved accuracy from 84% to 95% on 1000+ labeled samples via Gemini 3.0 teacher.
Real-Time Voice Agent: Self-hosted LiveKit on AWS, 2000+ daily calls, <900ms latency, 99.9% uptime. Multi-channel SIP across Twilio, Plivo, Telecimi, Acefone with auto-failover. 60% failed call reduction.
Qwen3 TTS: Open-source TTS via Alibaba Cloud, 70% cost reduction. Healthcare RAG with 92% query accuracy, 40% medication adherence improvement.

AI Engineer

Dogma Group

Apr 2024 — Apr 2025

RAG-Based Tender Processing System: LangChain + OpenAI/Gemini + BM25/MMR reranking + MongoDB memory, deployed on Docker with Azure. 30% reduction in manual effort.

Data Scientist

BitsKraft

Apr 2021 — May 2024

Credit Risk Modelling: Improved accuracy from 54% to 71%. Azure + FastAPI backend for real-time scoring.
Customer segmentation & churn prediction pipelines for enterprise clients.

suman@paudel:~$ cat /etc/education

Master in Data Science

Tribhuvan University

2024 — 2026 · GPA 3.7/4.0

B.Tech in Computer Science

Chandigarh University

2017 — 2021

suman@paudel:~$ cat /etc/principles | head -3

[01]── LATENCY IS EVERYTHING

Every millisecond is a conversation lost

> I architected self-hosted LiveKit infrastructure on AWS achieving

> <900ms end-to-end latency, orchestrating 2000+ daily calls at

> 99.9% uptime. Because humans don't wait for machines.

p50_latency_ms=871

concurrent_calls=120

[02]── OWN THE STACK

Open source is not a compromise. It's a weapon.

> Integrated open-source Qwen3 TTS reducing costs by 70%.

> Fine-tuned OCR/VLM models (84% → 95%) on custom datasets.

> Self-hosted vLLM on H100 serving GPT-OSS-20B at production scale.

tts_cost_delta=-70%

gpu=H100

accuracy=95%

[03]── RETRIEVAL IS REASONING

Ground every answer in truth

> Designed RAG + SQL agent pipelines solving large-scale manufacturing

> analytics with LangGraph. 95% retrieval accuracy. 78% complex reasoning.

> Won CHIPSAL @ COLING 2025. ACL-published research.

retrieval_acc=95%

multi_step=78%

competition=1st place

suman@paudel:~$ cd /work/aiml-rag && ls -la

// AI/ML + RAG

Production RAG systems · LLM fine-tuning · NLP research · vLLM inference

Manufacture-Excel-RAG

Production RAG system for manufacturing Excel analytics. Multi-agent SQL query generation, hybrid search, GPU-accelerated vLLM inference on H100/A100. Docker, Alembic, comprehensive evaluation framework.

PythonFastAPILangGraphvLLMDockerPostgreSQL

SQL-GRINDA

Elasticsearch-based SQL AI Agent for Korean manufacturing enterprises. Full RAG pipeline with FastAPI, Alembic migrations, evaluation datasets, and React frontend.

PythonFastAPIElasticsearchDockerAlembic

uvc-text2sql

Text-to-SQL agent for manufacturing data across PostgreSQL + InfluxDB. LangGraph orchestration with LangSmith tracing. Vercel proxy, Docker deployment, comprehensive eval datasets.

PythonFastAPILangGraphPostgreSQLInfluxDBDocker

counselor-data-pipeline

RAG pipeline for AI Counselor system. Document processing, embedding, hybrid retrieval with evaluation framework. Built cost model analysis for RAG infrastructure.

PythonFastAPIRAGDockerAlembic

hwpx-intelligence

Korean HWPX document parsing & RAG pipeline. Custom document structure extraction, table parsing, and intelligent chunking for Korean regulatory documents.

PythonRAGDocument AIOCR

pps-mono-repo

AI-powered proposal generation & evaluation system. Multi-service architecture with AI engine, analysis pipeline, knowledge hub, and voice evaluation via Pipecat.

PythonFastAPIDockerPipecatRFP

suman@paudel:~$ cd /work/voice && ls -la

// VOICE AGENTS

LiveKit · SIP trunking · Real-time speech · 2000+ calls/day · 99.9% uptime

eugenix-voice-agent

Hair transplant clinic voice AI handling 2000+ daily calls. Multi-persona agent system (Welcome/Closer), LiveKit transport, SIP trunking across 4+ carriers, 99.9% uptime.

PythonLiveKitSIPDockerAlembic

voice-agent

Core voice AI agent platform with call dispatcher, noise filtering, STT/TTS/LLM factory. PM2 process management, egress template generation. Production-hardened.

PythonLiveKitDeepgramPM2Docker

callpal-livekit-py

AI phone calling platform with LiveKit backend. SIP trunk integration, Flask-like app structure, docker-compose for one-command deploy.

PythonLiveKitSIPDocker

chattrvox-production-saas

Production voice chat SaaS with React/Vite frontend, Node backend, Supabase auth, and LiveKit agents. Full production/staging Docker environments.

ReactNodeSupabaseLiveKitDocker

AIRAZOR Voice Agents

Multi-agent voice platform with control plane, frontend, and multiple Python agent backends. Monorepo with shared runtime core. Docker swarm deployment.

PythonLiveKitReactDockerMakefile

docuvoice

Document-to-voice platform with backend, frontend, agents, and infra services. Docker-compose for full-stack deployment.

PythonTypeScriptDockerVoice AI

rapida-voice-ai / voice-ai

Go-based voice AI platform with LiveKit integration, Pipecat end-of-speech detection (ONNX), document RAG, and Go LLM agent executor.

GoLiveKitPipecatONNXDocker

kai-voice / moshi-livekit / zenvoice

Additional voice platforms: Kai Voice (multi-agent + token server), Moshi + LiveKit bridge, ZenVoice (NestJS + Next.js + Python agent stack).

PythonLiveKitNestJSNext.jsDocker

suman@paudel:~$ cd /work/infra && ls -la

// INFRASTRUCTURE

Kubernetes · LiveKit self-hosting · AWS/Azure · Multi-region · Helm · Terraform

k8s-deploy

Kubernetes deployment infrastructure with Helm charts and Terraform. Production LiveKit K8s values including Redis, Traefik ingress, and autoscaling configuration.

KubernetesHelmTerraformAWS

livekit-infra-deployment

Self-hosted LiveKit infrastructure on AWS/Azure. Configs for multiple regions (AMS, Miami), Docker-compose + Kubernetes manifests, cloudflared tunnels.

LiveKitAWSAzureDockerKubernetes

oneinbox-lk-infra

Multi-region LiveKit deployment for OneInbox platform. SIP trunking across 4 carriers, auto-failover, cloudflared tunneling, production monitoring.

LiveKitSIPAWSMonitoring

AWS Setup Scripts

Automated LiveKit deployment scripts for AWS (EC2/EKS). Eugenix and Aivoco production environment setup with security hardening and monitoring.

AWSBashLiveKitTerraform

suman@paudel:~$ echo $MISSION

> let's build
what matters.

The future belongs to those who ship outcomes, not outputs.
If you're building something that listens — I want to help.

$ mail dastonsuman1997@gmail.com $ open linkedin.com/in/suman-paudel $ git clone github.com/p-sumann

suman@paudel:~$ exit▊