Building AI Systems That Work in Production

Prabhata Kumar Maharana

Senior AI Systems Engineer

Building AI systems that work in production. Sharing lessons on AI, ML, RAG, Agents, Cloud Infrastructure, Reliability, and System Design.

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About

AI is everywhere. But most AI systems fail the moment they hit production.

I focus on building AI systems that actually work—beyond demos, hype, and perfect conditions.

With years of experience in backend engineering, cloud platforms, and distributed systems, I apply the same engineering principles to modern AI systems.

  • →Reliability over hype
  • →Systems over shortcuts
  • →Real-world trade-offs over theory

Production AI is not just about models. It requires infrastructure, observability, evaluation, scalability, governance, and resilience. Those are the challenges I enjoy solving.

Areas of Focus

Production AI

Designing and operating AI systems that move beyond prototypes into reliable production services.

AI Architecture

Building systems with LLMs, RAG, Agents, APIs, workflows, and supporting infrastructure.

Reliability Engineering

Improving resilience through monitoring, observability, evaluation, guardrails, and failure analysis.

Cloud & Scalability

Designing cloud-native architectures that balance performance, throughput, availability, and cost.

System Design

Applying proven software engineering principles to modern AI and distributed systems.

What I Share

Practical lessons for engineers building AI systems outside ideal conditions.

I regularly write and share insights on AI systems, machine learning, LLMs, RAG, agents, cloud architecture, reliability engineering, and system design.

  • Artificial Intelligence
  • Machine Learning
  • Large Language Models
  • Retrieval-Augmented Generation
  • AI Agents & Workflows
  • Cloud Architecture
  • Reliability Engineering
  • System Design

My goal is simple: help engineers understand what it takes to build AI systems that continue delivering value in production.

Insights & Articles

Technical articles and engineering deep dives are currently in development.

I'm documenting lessons from building and studying AI systems, cloud infrastructure, reliability engineering, and modern software architecture.

Coming Soon

Long-form articles, practical guides, and production engineering lessons on AI Systems Engineering, LLM Architecture, RAG & Advanced RAG, AI Agents & Workflows, Cloud Infrastructure for AI, Reliability & Observability, and Production AI Patterns.

Until then, I regularly share insights and engineering lessons on LinkedIn.

Follow my work on LinkedIn

Practical insights, architecture discussions, and real-world lessons on building AI systems that work in production.

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