About me

I am a Software Engineer based out of Banglore, India, working in Software Infrastructure and Site Reliability. During my current stint with LinkedIn, I've gained professional experience working with Edge Network Infrastructure of large-scale Internet-facing platforms. This involves managing, setting up and developing automation for technologies such as Domain Name Systems (DNS), Content Delivery Networks (CDNs) and Edge-Proxies (Azure Front Door, etc.).

I've got a knack for intelligent automation, and I love looking for patterns in repetitive tasks because I believe they're better off being done by a machine. In the SRE and DevOps world, such AI automation can prove to be revolutionary in areas such as reducing operational load and assisting engineers with incident response & triaging.

At LinkedIn's Edge Infrastructure team, I single-handedly proposed and built an intelligent automation system which is capable of orchestrating the Edge dynamically based on any set of configured performance metrics. I also worked on devising and building a pipeline which can perform automated Root-Cause Analysis for Azure Front Door-related availability SLA incidents at LinkedIn.

While interning with LinkedIn's Capacity Engineering team, I devised an AI-based pipeline which used statistical heuristics and graph search to infer the top root causes of anomalies during site capacity load tests.

Experience

  1. Senior Engineer, Site Reliability

    Oct 2023 - Present Bengaluru, India
    • Senior Individual Contributor in the Edge Performance and Engineering team at LinkedIn
  2. Site Reliability Engineer

    July 2021 - Sept 2023 Bengaluru, India
    • Working with the Edge Infrastructure team, responsible for managing LinkedIn's Edge Network which involves services like DNS, CDNs, Azure Front Door, TLS certificates and related tools.
    • Developed an AI-based tool capable of intelligently orchestrating the Edge (AFD, PoPs, CDNs) on the DNS layer for optimal end-user availability. This completely automated the mundane task of manual fail-overs, cutting down on several man hours.
    • Worked on migrating site-traffic from LinkedIn's legacy Edge on to Azure Front Door. Responsible for setting up Azure Front Door and DNS ramp for the migration.
    • Worked closely with Microsoft Azure counterparts to help them recognise and solve ongoing issues with their AFD platform as it pertains to LinkedIn. Worked on devising a Proof of Concept for performing Automated Root Cause Analysis of such issues.
    • Introduced manifold improvements to LinkedIn's url short-link feature - lnkd.in - by aligning stakeholders to remove extra redirect and by onboarding it to AFD with Caching at the Edge.
  3. Site Reliability Engineering Intern

    May 2020 - July 2020 Bengaluru, India (Remote)
    • Worked with the Capacity Engineering team to devise an AI pipeline for diagnosing site performance issues and detecting capacity bottlenecks in Linkedin's RESTful service oriented infrastructure.

Education

  1. Netaji Subhas Institute of Technology

    August 2017 — June 2021
    • Univeristy of Delhi
    • Bachelor of Engineeering in Computer Engineering
    • CGPA: 8.65/10
  2. Central Board of Secondary Education

    2016 — 2017
    • Class 12th
    • Score: 97.0%
  3. Central Board of Secondary Education

    2014 — 2015
    • Class 10th
    • CGPA: 10.0/10

Skills

Programming

  • Python
    90%
  • Java
    70%
  • C/C++
    60%
  • Golang
    50%
  • JavaScript
    60%
  • Data Structures and Algorithms
    80%

Computer Networks

  • Domain Name System (DNS)
    80%
  • Content Delivery Networks (CDNs)
    80%
  • Distrbuted Networks
    60%
  • TCP/IP
    70%
  • Microsoft Azure
    65%

Internet Technologies

  • Python-Flask Framework
    85%
  • REST-APIs
    70%
  • Spring-Boot
    50%
  • HTTP/HTTPS
    70%

Datastores

  • MySQL
    65%
  • Azure Blob Storage
    50%
  • Firebase
    60%
  • RabbitMQ
    50%

Tools

  • Linux
    70%
  • Docker
    50%
  • Git/Github
    60%

Aritficial Intelligence

  • Machine Learning
    70%
  • Deep Learning
    80%
  • Natural Language Processing
    60%
  • Computer Vision
    65%
  • Tensorflow
    65%
  • Keras
    75%
  • Scikit-Learn
    75%
  • Mathematical Modelling
    70%

Posts