LLM/RAG Applications
Document assistants, retrieval pipelines, vector search, tool-calling workflows, structured data collection, and AI app backends.
PythonFastAPIQdrantLangGraphRAGTool Calling
Ahmad Saladin
Remote AI/ML Engineer for production AI systems
I help teams build LLM/RAG apps, computer vision pipelines, FastAPI model APIs, vector search systems, n8n automations, and cloud inference backends.
Based in Indonesia, UTC+7. Available for APAC/Europe overlap and async global teams.
Open to remote roles, contractor work, freelance projects, part-time engagements, and project-based AI/backend implementation.
GitHub link pending LinkedIn link pending
What I Build
Computer Vision Systems
Image processing, segmentation, detection, OpenCV/PyTorch pipelines, sliding-window inference, post-processing, and production inference APIs.
PyTorchOpenCVONNXSegmentationDetectionSliding-Window Inference
AI Backend & Model Serving
FastAPI/Flask model APIs, async job queues, Redis/RabbitMQ workers, object storage flows, callback/webhook patterns, and cloud deployment.
FastAPIFlaskRedisRabbitMQDockerAWSGCPS3/GCS
n8n + AI Automation
Workflow automations combining APIs, LLMs, webhooks, human approval, messaging integrations, and business process automation.
n8nWebhooksLLMsGmailTelegramPostgresAutomation
Featured Case Studies
View all case studiesLLM/RAG Assistant with Tool Calling
Case study coming soonAI assistant workflow with retrieval, tool calling, structured information collection, and backend integration.
LLMRAGQdrantFastAPILangGraphTool Calling
Computer Vision Segmentation Pipeline
Case study coming soonProduction-oriented image segmentation workflow with preprocessing, sliding-window inference, post-processing, API/mobile deployment considerations, and visualization outputs.
Computer VisionPyTorchOpenCVSegmentationONNXAPI Deployment
Async AI Inference Backend
Case study coming soonBackend architecture for long-running AI jobs using API endpoints, queue workers, object storage, status tracking, and callback/webhook delivery.
FastAPIFlaskRedisRabbitMQDockerAWSGCPS3/GCS
PoC / Demo Preview
v0 PoCs are placeholders or static walkthroughs, not live backend demos.
Guided demo planned
RAG Document Assistant Demo
A document assistant flow with sample document selection, retrieved context, source-grounded answer, and productionization notes.
RAGVector SearchQdrantLLMFastAPI
Guided demo planned
Computer Vision Segmentation Demo
A visual walkthrough of image input, segmentation mask, overlay result, post-processing, and deployment considerations.
Computer VisionOpenCVPyTorchSegmentationONNX
Guided demo planned
Async AI Inference API Demo
A simulated long-running AI inference workflow: submit job, queue, process, store result, check status, and receive callback.
FastAPIQueueWorkerRedisRabbitMQStorageCallback
Available for roles and project work
I am available for remote AI/ML engineering roles, contractor engagements, freelance PoCs, part-time implementation support, and project-based AI/backend work.
For Hiring Teams
Looking for an AI/ML engineer who can build production-oriented systems, not just experiments.
- AI/ML Engineer
- LLM/RAG Engineer
- Computer Vision Engineer
- AI Backend Engineer
- Python Backend Engineer with ML deployment experience
For Clients & Agencies
Need help building AI prototypes, backend integrations, computer vision pipelines, RAG apps, or workflow automations.
- RAG/document assistant prototypes
- Computer vision pipelines
- Async model inference APIs
- AI workflow automation
- n8n + LLM implementation
- Backend integration for AI products
Tech Stack
AI / ML
PyTorchscikit-learnONNXOpenCVembeddingssegmentationdetection
LLM / Agents
RAGQdrantLangGraphtool callingLLM APIsprompt workflows
Backend
PythonFastAPIFlaskRedisRabbitMQREST APIswebhooks
Cloud / Infra
DockerAWSGCPS3/GCSCloudflare PagesVPS deployment
Automation
n8nTelegramGmailPostgresworkflow automation
Availability
Based in Indonesia, UTC+7. Available for APAC/Europe overlap and async global teams.
Open to remote roles, contractor work, freelance projects, part-time engagements, and project-based AI/backend implementation.
Can I help you build this AI system?
Start with the case study placeholders, review the PoC plans, or reach out directly with the system you want to build.