I build practical software across AI applications, data pipelines, voice automation, computer vision, image generation, cloud infrastructure, and backend systems.
SYSTEM PROFILE
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Name Zaafir Rizwan
Focus AI Apps · Data Engineering · Cloud · Automation
Builds Intelligent systems that connect models, data, APIs, and users
Stack Python · FastAPI · AWS · Bedrock · LangGraph · Data Pipelines
Direction Product-minded engineering across modern AI and cloud workflows
────────────────────────────────────────────────────I work across the full stack of modern AI products: data, models, APIs, cloud, automation, and user-facing workflows.
- AI applications using LLMs, agents, retrieval, function calling, structured outputs, and workflow automation
- Data engineering pipelines for ingestion, transformation, storage, search, analytics, and production data flows
- Voice AI systems for speech interfaces, calling workflows, transcription, summarization, and automation
- Image and multimodal systems for image generation, document understanding, video analysis, and vision workflows
- Cloud-native backends using APIs, containers, queues, databases, serverless services, and scalable deployment patterns
- AWS and Bedrock workflows for building model-powered applications on managed cloud infrastructure
flowchart LR
A[Users / Business Workflow] --> B[API Layer]
B --> C[Orchestration]
D[Documents] --> H[Data Pipeline]
E[Audio / Voice] --> H
F[Images / Video] --> H
G[Structured Data] --> H
H --> I[Storage + Search]
I --> C
C --> J[LLMs / Bedrock / Vision Models]
J --> K[Tools + Automations]
K --> L[Product Output]
L --> M[Monitoring]
M --> N[Evaluation + Iteration]
N --> C
Data → cloud → models → automation → product → feedback loop
| Project | What it shows | Area |
|---|---|---|
mini-agentic-rag-system |
Model orchestration, retrieval, reasoning, and tool use | AI Applications |
Building-Autonomous-AI-Agents-with-LangGraph |
Agent workflows, graph state, planning loops, and automation patterns | Agents / Automation |
Rag_log_analysis |
Log analysis, data search, and operational intelligence | Data + AI |
local-rag |
Private document intelligence and local-first AI workflows | Knowledge Systems |
resume-fit |
Resume matching, scoring, and workflow automation | AI Product |
video-understanding |
Video analysis, multimodal reasoning, and computer vision workflows | Multimodal AI |
bim-agent |
Built-environment automation with spatial/document reasoning | Applied AI |
I build model-powered applications that combine prompts, tools, APIs, memory, structured outputs, and real user workflows.
OpenAI · Gemini · AWS Bedrock · LangGraph · LangChain · Structured Outputs · Tool Calling
I design pipelines that move data from raw sources into systems that can search, analyze, reason, and automate.
Python · ETL/ELT · PostgreSQL · Vector Search · Data Ingestion · Analytics · Automation
I work with audio, image, video, documents, and structured data to build systems that understand more than text.
Voice AI · Transcription · Image Generation · Computer Vision · Video Understanding · Document AI
I care about making ideas deployable: clean APIs, scalable services, cloud infrastructure, observability, and maintainable architecture.
FastAPI · Docker · AWS · GCP · Bedrock · SageMaker · Lambda · CI/CD
| AI / LLMs | OpenAI · Gemini · AWS Bedrock · LangGraph · LangChain · LlamaIndex · Hugging Face |
| Data | Python · SQL · PostgreSQL · ETL/ELT · data ingestion · analytics · search pipelines |
| Voice / Multimodal | Speech workflows · transcription · image generation · computer vision · video understanding · document AI |
| Backend | FastAPI · REST APIs · background workers · queues · authentication · databases |
| Cloud / MLOps | AWS · GCP · Docker · Kubernetes · Terraform · SageMaker · GitHub Actions · CI/CD |
Good AI products are not just prompts. They are systems: data pipelines, model orchestration, cloud infrastructure, backend APIs, evaluation, automation, and user experience working together.
I like building systems that are:
- useful beyond a demo
- connected to real data and real workflows
- reliable enough to run in production
- designed for latency, cost, and maintainability
- flexible across text, voice, image, video, and structured data
- built with a product mindset, not just a model-first mindset
- AI agents and workflow automation
- Voice AI and real-time assistant experiences
- Image generation and multimodal AI products
- Data engineering for AI-ready systems
- AWS Bedrock and cloud-native AI applications
- Backend infrastructure for AI products
