Shiven Tripathi — Software Engineer

At Uber, I've built autonomous agentic systems and fault-tolerant infrastructure, specializing in the intersection of Generative AI and high-performance distributed systems. My work involves designing platforms that automate complex operational challenges. I've architected a multi-agent system for automated incident response, reducing engineer toil, and created versatile no-code platforms that enable the development of agentic workflows across the company. I've also applied my systems expertise to complex business domains, redesigning core components of the Fares Platform to enhance the scalability and reliability of Uber's global pricing systems. This expertise is grounded in a strong foundation of building distributed systems at scale. I worked on a million QPS distributed cache implementation in the Marketplace ecosystem which caches Rider, Driver, Vehicle, and other entities from Uber’s Core Services. This decouples Marketplace’s availability from those services, serving as a latency, availability, and capacity cache, and safeguarding core mobility flows worth over $100B GB. Additionally, my work on a generalized capture-replay framework improved the software development lifecycle by providing developers with a decentralized shadow environment and adding robust bulk replay validations for all changes. This required solving significant scaling challenges in our planet-scale OLAP database, optimizing performance for tables with billions of keys.

Stackforce AI infers this person is a SaaS-focused engineer with expertise in distributed systems and AI-driven automation.

Location: Bengaluru, Karnataka, India

Experience: 5 yrs 6 mos

Skills

Generative Ai
Distributed Systems
Software Development Lifecycle
Scalability
Robotics

Career Highlights

Architected autonomous platforms using Generative AI.
Designed scalable distributed systems for Uber's global pricing.
Developed innovative no-code tools for operational automation.

Work Experience

Uber

Software Engineer II (1 yr 2 mos)

Software Engineer (1 yr 8 mos)

Software Engineer Intern (2 mos)

ERA IITK

Team Head (10 mos)

Senior Member (1 yr 4 mos)

Indraprastha Institute of Information Technology, Delhi

Research Intern (1 mo)

International Neuroinformatics Coordinating Facility (INCF)

Google Summer of Code at INCF (3 mos)

Indian Institute of Technology, Kanpur

Research Associate, Artificial Intelligence and Data Analytics Research (AIDAR) Lab (1 yr 6 mos)

Vox Populi, IIT Kanpur

Senior Member (11 mos)

Core Group Member (7 mos)

Humanoid IITK

Team Member (6 mos)

Education

Bachelor of Technology - BTech at Indian Institute of Technology, Kanpur

Class 12 at Delhi Public School, Greater Noida

Shiven Tripathi

Software Engineer

Bengaluru, Karnataka, India5 yrs 6 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Architected autonomous platforms using Generative AI.
Designed scalable distributed systems for Uber's global pricing.
Developed innovative no-code tools for operational automation.

Stackforce AI infers this person is a SaaS-focused engineer with expertise in distributed systems and AI-driven automation.

Contact

shiventripathi1@gmail.com LinkedIn

Skills

Core Skills

Generative AiDistributed SystemsSoftware Development LifecycleScalabilityRobotics

Other Skills

Large Language Models (LLM)No-code toolsOLAP databaseDecentralized testingJavaGo (Programming Language)Computer VisionDeep LearningMachine LearningImage ProcessingSoftwareObject-Oriented Programming (OOP)Artificial Intelligence (AI)C (Programming Language)C++

About

Experience

5 yrs 6 mos

Total Experience

1 yr

Average Tenure

2 yrs 10 mos

Current Experience

Uber

3 roles

Software Engineer II

Mar 2025 – Present · 1 yr 2 mos · On-site

Designed no-code tools and platforms to MCP-fy any API at Uber and integrate agents with them across all work surface areas.
Architected autonomous, agentic platforms using Generative AI for automated incident response, reducing engineer toil.
Solved critical scaling challenges in Uber’s planet-scale OLAP database of fares capture-replay sessions, optimizing tables with billions of keys.

Large Language Models (LLM)Distributed SystemsGenerative AI

Software Engineer

Jun 2023 – Feb 2025 · 1 yr 8 mos · On-site

Redesigned core components of the Fares Platform to enhance the scalability and reliability of Uber's global pricing systems.
Improved the software development lifecycle by developing a generalized capture-replay framework, enabling decentralized shadow testing.
Worked on a million-QPS distributed cache that safeguards over $100B in mobility flows. This critical infrastructure serves as a latency and availability shield by decoupling Marketplace from core services.

JavaGo (Programming Language)Distributed SystemsScalability

Software Engineer Intern

May 2022 – Jul 2022 · 2 mos · Bengaluru, Karnataka, India

Developed data-driven categorisation and classification models for Uber’s microservice architecture
Processed Jaeger tracing data to DAGs, for edge-wise analysis of latency impact, call frequencies and criticality
Improving efficiency in outage control and latency optimisation by providing reduced architecture representations
Received Pre-Placement Offer to join the team as a full-time employee for exceptional performance

Era iitk

2 roles

Team Head

Jul 2021 – May 2022 · 10 mos · Kanpur, Uttar Pradesh, India

Senior Member

Mar 2020 – Jul 2021 · 1 yr 4 mos · Kanpur, Uttar Pradesh, India

Team ERA-IITK competes in IEEE ICRA DJI Robomaster Challenge, building autonomous ground robots.
Implemented object detection and tracking modules for the armoured bot using traditional CV based techniques and DL methods like YOLO.
Tested out RL using DQN agents on pygames as a proxy to the training of the bot to target and attack enemy bots.
Currently working on integrating RL Agents and Behavior Trees for optimal decision making under threat and advantage.

Indraprastha institute of information technology, delhi

Research Intern

Jun 2021 – Jul 2021 · 1 mo

International neuroinformatics coordinating facility (incf)

Google Summer of Code at INCF

May 2021 – Aug 2021 · 3 mos

Analyzing stimulus prediction capabilities of neurons: predictive information estimation methods
To guide behaviour, it has been proposed that neurons eventually learn to predict future states of sensory inputs. The main contribution of this project would be to publish highly optimised library codes that can serve as evaluation benchmarks for predictive accuracy. We also believe that neurons can generate efficient encodings on these predictions. Through this project, estimates of the predictive information would also be obtained by neural models.

Indian institute of technology, kanpur

Research Associate, Artificial Intelligence and Data Analytics Research (AIDAR) Lab

Nov 2020 – May 2022 · 1 yr 6 mos · Kanpur, Uttar Pradesh, India

Researched methods for autonomous vehicles to acquire accurate information about objects, in complex environments
Implemented fusion of 3D LIDAR and camera for object detection, increasing robustness with reduced latency
Explored datasets and algorithms in literature relevant to the problem statement of object detection and mapping

Vox populi, iit kanpur

2 roles

Senior Member

Apr 2020 – Mar 2021 · 11 mos

Core Group Member

Sep 2019 – Apr 2020 · 7 mos

Humanoid iitk

Team Member

Nov 2019 – May 2020 · 6 mos · IIT Kanpur

Team Humanoid-IITK competes in FIRA RoboWorld Cup, building humanoid robots capable of archery, wrestling etc.
Worked on obstacle detection modules for the Humanoid Robot using potential field mapping.
Worked with OpenCV and ROS to build efficient nodes solving CV tasks like detection, tracking and depth mapping, used to solve the problem statement of archery.