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Krish Aryan

SRE @ Netradyne · building AI agents so PagerDuty doesn’t wake me up at 3AM · AI × Infra × Cloud · occasional over-thinker

Bengaluru

1+ year of work experience

Netradyne
Feb 20267 mosPresent

The job got more interesting. Now I architect the AI systems instead of just shipping them. - Leading reliability and observability for large-scale distributed systems powering real-time AI products. Fancy way of saying: I make sure things don't fall over, and when they do, we know exactly why in minutes not hours. - Architecting internal platforms that automate incident detection, alert correlation, and root-cause discovery. The goal is a world where the system explains itself and nobody has to play detective at midnight. - Resident AI-tooling lead for the SRE org. If it involves an LLM doing something actually useful in production, it probably came through me.
Netradyne
Jul 20258 mosFeb 2026

This is where things got fun. - Built TraceLens from scratch — an agentic AI system that autonomously queries logs, metrics, and alerts, reasons over the data, and surfaces root causes. Full stack, solo, shipped org-wide. FastAPI backend, React + SSE streaming frontend, native LLM tool-calling loop. No agent frameworks. Just the spec and stubbornness. - Designed incident detection and escalation pipelines integrated with on-call tooling — so the right person gets paged with context, not just a wall of red. - Containerized and deployed internal tooling at org scale with Docker and Kubernetes on AWS. It scales. I'm unreasonably proud of it.
Netradyne
Feb 20256 mosJul 2025

Bengaluru

Started as an intern. Left having built a platform covering 150+ services. Not bad for six months. - Built AlertFlow — real-time alert correlation across distributed services. Turned alert storms into structured triage queues. Made on-call meaningfully less miserable. - Built and maintained monitoring coverage across Grafana, Datadog, Prometheus, and CloudWatch. At one point I had all four open simultaneously and felt nothing. - Automated incident detection and escalation workflows — reduced MTTR through log-driven diagnostics and structured RCA. The MTTR went down. The sleep quality went up.
Nebulixus
Jun 20242 mosJul 2024

India

Applied machine learning for predictive economic modeling using regression & clustering techniques. Conducted NLP-based sentiment analysis on economic policies. Developed interactive dashboards with Power BI to visualize economic trends & inflation patterns. Presented findings to stakeholders, contributing to data-driven decision-making.

Krish’s AI Stack

antigravity
antigravity
claude code
claude code
codex
codex
gemini
gemini
mcp
mcp
openai
openai

Education

New Horizon College of Engineering

Bachelor of Engineering - BE, Artificial Intelligence and Machine Learning

New Horizon College of Engineering

20214 yrs2025

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Headline

SRE @ Netradyne · building AI agents so PagerDuty doesn’t wake me up at 3AM · AI × Infra × Cloud · occasional over-thinker

About

I build systems that investigate incidents before anyone has to. Technically I'm an SRE. Realistically, I spend most of my time convincing AI agents to do the detective work that used to require a very tired engineer and an unhealthy relationship with grep. Here's what that's looked like: → TraceLens — an AI agent that autonomously digs through logs, metrics, and alerts and tells you what broke and why. Not a dashboard. Not a chatbot. An agent that actually investigates. Shipped it org-wide. It works. → AlertFlow — real-time alert correlation across 150+ services. Because 47 simultaneous alerts about the same thing isn't 47 problems — it's one problem and a terrible Tuesday. → A natural-language log analysis tool so engineers can ask "what was broken at 2:47PM?" instead of writing grep one-liners they'll regret later. Stack I live in: Python · FastAPI · React · AWS · Azure AI Foundry · Docker · K8s · Prometheus · Grafana · Elasticsearch I like working with people who take the work seriously but not themselves. If you're building something at the edge of AI × infrastructure — or just want to talk shop — say hi. I read every message. I respond to most of them. The bar is just: don't open with "hope this finds you well."

Location

Bengaluru

AI stack

antigravity

claude code

codex

gemini

mcp

openai

Work experience

Software Engineer - SRE at Netradyne, Feb 2026 - Present · 7 mos, The job got more interesting. Now I architect the AI systems instead of just shipping them. - Leading reliability and observability for large-scale distributed systems powering real-time AI products. Fancy way of saying: I make sure things don't fall over, and when they do, we know exactly why in minutes not hours. - Architecting internal platforms that automate incident detection, alert correlation, and root-cause discovery. The goal is a world where the system explains itself and nobody has to play detective at midnight. - Resident AI-tooling lead for the SRE org. If it involves an LLM doing something actually useful in production, it probably came through me.

Associate Site Reliability Engineer at Netradyne, Jul 2025 - Feb 2026 · 8 mos, This is where things got fun. - Built TraceLens from scratch — an agentic AI system that autonomously queries logs, metrics, and alerts, reasons over the data, and surfaces root causes. Full stack, solo, shipped org-wide. FastAPI backend, React + SSE streaming frontend, native LLM tool-calling loop. No agent frameworks. Just the spec and stubbornness. - Designed incident detection and escalation pipelines integrated with on-call tooling — so the right person gets paged with context, not just a wall of red. - Containerized and deployed internal tooling at org scale with Docker and Kubernetes on AWS. It scales. I'm unreasonably proud of it.

Cloud Intern at Netradyne, Feb 2025 - Jul 2025 · 6 mos, Bengaluru, Started as an intern. Left having built a platform covering 150+ services. Not bad for six months. - Built AlertFlow — real-time alert correlation across distributed services. Turned alert storms into structured triage queues. Made on-call meaningfully less miserable. - Built and maintained monitoring coverage across Grafana, Datadog, Prometheus, and CloudWatch. At one point I had all four open simultaneously and felt nothing. - Automated incident detection and escalation workflows — reduced MTTR through log-driven diagnostics and structured RCA. The MTTR went down. The sleep quality went up.

Research Associate Intern at Nebulixus, Jun 2024 - Jul 2024 · 2 mos, India, Applied machine learning for predictive economic modeling using regression & clustering techniques. Conducted NLP-based sentiment analysis on economic policies. Developed interactive dashboards with Power BI to visualize economic trends & inflation patterns. Presented findings to stakeholders, contributing to data-driven decision-making.

Education

Bachelor of Engineering - BE, Artificial Intelligence and Machine Learning, New Horizon College of Engineering

Public links

leetcode: https://leetcode.com/KrishAryan

github: https://github.com/KrishAryan12