Jatin Katiyar

Software Engineer

Ghaziabad, Uttar Pradesh, India6 yrs experience

Most Likely To SwitchHighly Stable

Key Highlights

Led design and development of critical forecasting systems at Amazon.
Developed RESTful APIs for financial tools at Sentieo.
Created a chatbot using ROS for autonomous navigation.

Stackforce AI infers this person is a Backend-focused Software Engineer with experience in SaaS and Fintech industries.

Contact

jatinkatiya97.jk@gmail.com LinkedIn

Skills

Core Skills

Distributed SystemsRest ApisService OptimizationBack-end Web Development

Other Skills

AWS NeptuneGremlinAPIsNetwork State ServiceSLARHCOptimizationContainerizationConfluenceReact.jsRESTful APIFAST APIProblem SolvingCommunicationPipeline Generation

About

I am an enthusiastic coder and recently added a debugger tag in that list by recently working as a teacher at the 'CODING NINJAS'. "I always believe to be the hardest worker in the room." and I am determined to work with the Tech Giants in the coding industry.

Experience

6 yrs

Total Experience

2 yrs

Average Tenure

4 yrs 3 mos

Current Experience

Amazon

3 roles

Software Development Engineer 2

Apr 2024 – Present · 2 yrs 2 mos

Software Development Engineer

Apr 2022 – Mar 2024 · 1 yr 11 mos

Currently working in the WWCP(World Wide Capacity Planning) team of Amazon which is responsible for routing the dense network of relevant Customer Agents to Customers in order to mitigate their queries in the least waiting time possible.
Worked on the project of building Network Forecasting Service which provides SLA(Skill label agreements) and RHC(Required HeadCounts) to meet SLA of different skills for future intervals. Implemented a DJS job which runs on different servers in parallel for different regions to predict the Network forecast for each day of different skills.
Currently working on the Network State Service(NSS) Optimization project which is responsible for pulling various BWGA levers to facilitate a skill in trouble via providing agents from the backup workgroup to skills in real time

ContainerizationConfluence

Senior Software Engineer

Mar 2022 – Present · 4 yrs 3 mos

● Working in Amazon’s World Wide Capacity Planning (WWCP) team, owning systems that optimize global customer-to-agent routing to minimize wait times and improve SLA performance at scale.
● Led design and development of the Network Forecasting Service, delivering half-hourly SLA and Required Headcount (RHC) forecasts for thousands of skills across regions via low-latency APIs.
● Built distributed, parallel forecasting pipelines and dynamic PB Group / connected-component generation using AWS Neptune and Gremlin, reducing graph computation latency from ~2 minutes to 1–2 seconds.
● Drove Network State Service (NSS) optimization by dynamically identifying skills in trouble and triggering BWGA levers, enabling <10-minute end-to-end recommendation cycles and measurable improvements in SLA miss metrics.

AWS NeptuneGremlinAPIsNetwork State ServiceSLARHC+2

Sentieo

Software Engineer (Full-stack)

Feb 2021 – Apr 2022 · 1 yr 2 mos · New Delhi, Delhi, India

1) Working as a part of Platform team of Sentieo and responsible(SME) for maintaining codebase and integrating new scalable features in the DASHBOARD module of the Platform team.
2) Worked on the project of building RESTful API design and product for clients using FAST API framework to create, update and delete a particular watchlist in the financial tool of Sentieo.

ContainerizationReact.jsRESTful APIFAST APIBack-End Web DevelopmentREST APIs

Qualcomm

Associate Software Engineer

Jun 2020 – Feb 2021 · 8 mos · Hyderabad, Telangana, India

1) Worked in the PMIC(Power management Integrated Circuit) department and underwent training for devising ways to charge smartphones efficiently using charging algorithms.
2) My team worked in Charging technology/Battery management system for android.

Problem SolvingCommunication

Nagarro

2 roles

Software Developer - Intern

May 2019 – Jul 2019 · 2 mos

1) Developed a Chat Bot using ROS and AIML in Python which worked well in three modes namely Text to Text mode, Text to Speech mode, Speech to Speech mode. This chat bot used to take voice inputs in order to command Turtle Bot Robot
2) Navigation of the Turtle Bot using Slam Gmapping Package of Ros and used Intel SR 300 Camera for depth data. The Robot was capable of navigating between two places specified in the map through the shortest path possible and simultaneously avoiding the obstacles that come in the way.

Problem SolvingCommunication

Software Engineer Intern

May 2019 – Jul 2019 · 2 mos

● Developed a chatbot using ROS and AIML in Python, supporting Text-to-Text, Text-to-Speech, and Speech-to-Speech interaction modes.
● Implemented autonomous navigation for TurtleBot using ROS SLAM (Gmapping) and Intel SR300 depth camera for real-time depth perception.
● Enabled the robot to navigate between user-defined locations on a generated map by computing the shortest path while dynamically avoiding obstacles.