R.

Hi, my name is

Rohit P T.

I build reliable AI systems.

I'm an AI & Cloud Engineer specializing in LLM orchestration, RAG pipelines (pgvector), and Python backend systems. I combine a strong background in AWS/GCP cloud migrations, infrastructure automation, and scripting with a focus on building production-ready AI workflows.

View ResumeGitHub

About Me

I am an AI Engineer with a strong focus on building Large Language Model applications, RAG pipelines, and safe orchestration architectures.

My expertise lies in designing robust backend systems that bridge the gap between experimental AI concepts and production-ready applications. I heavily utilize pgvector for scalable vector search, and ensure agentic systems transition safely using strict state machines.

When I'm not architecting AI solutions, I'm usually exploring new model capabilities, reading up on the latest in retrieval-augmented generation techniques, or optimizing database queries for high-throughput AI platforms.

main.ts
1const buildAI = async () => {
2 const rag = new RagPipeline({
3 vectorStore: "pgvector",
4 llm: "GPT-4 / Claude-3.5",
5 embedding: "OpenAI-v3"
6 });
7
8 const app = new Orchestrator({
9 safeTransitions: true,
10 agenticWorkflows: true,
11 });
12
13 return app.deploy(rag);
14};

Experience

Site Reliability Engineer

@ Ankercloud Technologies Pvt. Ltd.

Jul 2024 - Present
  • ▹Reduced deployment time by ~80% and MTTR by ~40%.
  • ▹Saved $10k+ annually through infrastructure optimization and automation.
  • ▹Engineered secure, deterministic transitions in complex workflows.
  • ▹Collaborated on building robust systems to trace performance and usage.

Featured Projects

AIREX

AI Incident Response Platform with RAG via pgvector, guarded action flows, SSE, and async workers.

  • Python
  • pgvector
  • SSE
  • Async Workers

Lens

AWS to GCP Migration Automation Platform featuring Terraform and Kubernetes manifest generation.

  • Terraform
  • Kubernetes
  • AWS
  • GCP

GCP Security Audit

GCP Security Audit & Reporting Automation with Scout Suite and Gemini AI remediation suggestions.

  • Python
  • GCP
  • Scout Suite
  • Gemini AI

Skills Overview

AI Systems

  • ▸RAG Architecture
  • ▸LLM Fine-Tuning
  • ▸Prompt Engineering
  • ▸pgvector
  • ▸LangChain
  • ▸LlamaIndex

Backend

  • ▸Python
  • ▸FastAPI
  • ▸TypeScript
  • ▸Node.js
  • ▸PostgreSQL
  • ▸Redis

Cloud & Platform

  • ▸AWS
  • ▸Google Cloud
  • ▸Docker
  • ▸Kubernetes
  • ▸CI/CD
  • ▸Terraform

Observability

  • ▸Prometheus
  • ▸Grafana
  • ▸Datadog
  • ▸Tracing
  • ▸Logging
  • ▸Langfuse

05. What's Next?

Get In Touch

Currently open for new opportunities. Whether you have a question about RAG systems, want to build safe LLM agents, or just want to say hi, my inbox is always open.

Say Hello