Backend AI Builder
Santosh M builds backend AI that ships.
I focus on backend development, AI and machine learning engineering, API design, database workflows, and practical product work for teams building real software.
Introduction
Focused on backend systems and AI product work.
Santosh M is a technology professional working on AI-powered product development at CoAI.Pro, with a practical focus on backend engineering, frontend-backend integration, and shipping software that is stable, useful, and easy to extend.
The work is centered on real implementation: Python, FastAPI, APIs, databases, deployment, AI website generation, and prompt engineering. The goal is to grow toward a career in backend development and AI/ML engineering.
Focus
Backend Development
Work style
Practical product building
Scope
AI and ML systems
Interest
LLM-based applications
Technical Interests
A technical stack shaped by systems, models, and integration work.
The strongest fit is at the intersection of backend systems and AI workflows: designing APIs, connecting services, optimizing model behavior, and building interfaces that make complex capabilities feel straightforward.
Backend engineering
Python, FastAPI, APIs, database workflows, deployment, and integration across the product stack.
AI and ML engineering
Model selection, local inference, quantization, RAG, AutoML, and generative AI workflows.
Product integration
Frontend-backend integration, prompt engineering, AI website generation, and improving existing systems.
Current Projects
Work in progress is where the direction becomes visible.
My current work centers on AI-powered product development at CoAI.Pro and on an academic project exploring adaptive LLM inference for resource-constrained systems. Both directions are about making AI more useful, more efficient, and easier to deploy in real-world environments.
CoAI.Pro
AI-powered product development
Building and improving product features with backend, AI, and integration work that supports real delivery.
Academic project
Adaptive LLM Inference Engine
A system that selects model, quantization level, and execution configuration based on hardware resources and task needs.
Skills Showcase
A hands-on toolkit for building practical AI products.
The work spans implementation, system design, model experimentation, and deployment. The emphasis is on solving a concrete problem with the right tooling rather than adding complexity for its own sake.
Backend systems, API development, database workflows, and frontend-backend integration for practical products.
Local inference, quantization, resource-aware model selection, RAG, LangChain, and LangGraph experimentation.
Deployment, AI website generation, prompt engineering, and iteration on live systems with clear constraints.
Career Direction
Growing toward backend development and AI/ML engineering.
The next step is deeper ownership of backend architecture and machine learning systems that can support user-facing products at scale. The direction is technical, but it stays close to product needs and implementation detail.
Backend depth
Stronger system design, API architecture, database handling, and deployment thinking.
AI product judgment
Better decisions around model selection, inference tradeoffs, and useful AI features.
Reliable delivery
Clearer ownership of production systems, integration work, and shipping software people can depend on.
Contact Information
Reach out about backend systems, AI work, or collaboration.
If you are hiring or want to collaborate on backend development, AI engineering, APIs, databases, or product work, the Projects page contains the contact request form.
How to connect
- Use the Projects page to send a contact request.
- Share your name, organization, email, and message.
- Include context about the kind of backend or AI work you need.
FAQ