Manas Srivastava profile photo 1 on Tal

Manas Srivastava

Agentic AI / Software Engineering | Backend | Distributed & Low Latency Systems | Kubernetes | Java | Go | Python | Scala | C++ | Spring Boot | AWS

India

4+ years of work experience

Uber
May 20264 mosPresent

Bengaluru

Intuit
Mar 20251 yr 3 mosMay 2026

Pioneered Agentic Commerce: Implementated Google AP2 and OpenAI ACP in Python to architect a Multi-Agent Payment System for secure, transparent conversational commerce via chat. Engineered AI Automation: Architected and lead the team of 2 to develop an AI Automation Agent (leveraging custom MCP Servers) that integrated PagerDuty, Splunk, and Slack to automate on-call reporting and provide proactive issue-resolution support, significantly reducing Mean Time To Respond (MTTR). Accelerated Development: Utilized advanced AI tools and custom tracing servers to rapidly generate 80% of production code with resilient design principles and integrated unit/integration tests. Led Architectural Consolidation: Migrated customer accounts (Solo and Enterprise) to a single unified entity, enabling comprehensive multi-currency and multi-country taxation and accounting support across the US/Canada. Delivered AI-Powered Customer Value: Led development of an AI-powered "done-for-you" experience, enabling customers to seamlessly query orders, resulting in a 98% conversion rate of customers landing on the cart. Managed Core Commerce Systems: Ensured smooth, high-volume order placement across Intuit’s ecosystem (TurboTax, QuickBooks, MailChimp) and oversaw secure payment processing (Credit Card, Apple Pay, Google Pay). Deep Technical Stack: Architected solutions using Java, Spring Boot, Python, Apache Pulsar/Kafka, and managed AI/ML Ops including Hugging Face fine-tuning and RAG implementation.
Sumo Logic
Sep 20247 mosMar 2025

Sumo Logic
Aug 20248 mosMar 2025

Remote

Sumo Query Autocomplete - Architected an autocomplete backend for Sumo Query Language with a team of 3, providing users with query suggestions similar to a Google search experience. This project significantly reduced the learning curve for new users on the Sumo Logic platform, enabling them to query logs effectively without requiring extensive expertise in Sumo Query Language. Data Engine For Artificial Intelligence Based Recommendation - Designed the core engine of an LLM-driven AI recommendation system for debugging logs, responsible for extracting relevant data from customer logs to suggest precise queries. This system enables the LLM to generate queries for effective debugging, plotting, and analysis of system logs and metrics. LLM based Query Summarization - Developed an LLM-powered query summarization system using Meta’s LLaMA to streamline dashboards and simplify complex queries, improving onboarding experiences for new SumoLogic customers.
Paytm Payments Bank
Jul 20221 yr 4 mosOct 2023

Noida, Uttar Pradesh, India

I have worked on a Server Patching Tool that creates automated updates to software and operating systems in live servers as per RBI guidelines. The tool specializes in patching critical infrastructure with graceful reboot and zero downtime of services such as Kubernetes, Etcd, Kafka, Elasticsearch, MySQl and Aerospike. The tool is built in Golang, gin(backend framework), reactjs typescript (frontend), HA proxy load balancer and rate limiter, Redis for cache management, and high concurrency management. It can be deployed on many servers/k8s pods such that it acts as one under the concepts of distributed systems. GOJobManager - It is a high-performance job scheduler designed for distributed systems, such as multi-pod/server applications. With a focus on high availability, low latency, and consistency, It efficiently manages functional jobs with the help of queues and locking mechanisms. It uses Redis for cache management, ensuring fast and reliable performance even under heavy loads. It's distributed design ensures that it can handle large volumes of jobs with ease, while its locking mechanism and consistent hashing approach ensure that jobs are distributed fairly across the cluster. We successfully implemented the CIS security benchmarks across the production Linux servers in our infrastructure with automation. These servers were critical to our organization, serving highly important services. Despite the challenges, my efforts resulted in zero downtime and greatly enhanced the cyber security of our systems. The implementation of these benchmarks helped to ensure that our infrastructure was secure and compliant. Tech Stack Used - Python, Django, Go, Salt Stack, Docker, Kubernetes, Linux (Ubuntu and CentOS), AWS, Elastic Load Balancer, Elastic Search, Jenkins, Graphana, Statsd, Etcd, Apache HTTP Server, Nginx, HA-Proxy, GIN(Golang Backend), ReactJS
Paytm Payments Bank
Jan 20221 yr 10 mosOct 2023

Noida, Uttar Pradesh, India

Dr. Patch Developed a Server Patching Tool adhering to Reserve Bank of India guidelines, enabling automated updates for software and operating systems on live servers. Specialized in patching critical infrastructure with graceful reboot and zero downtime for services like Kubernetes, Etcd, Kafka, Elasticsearch, MySQL, and Aerospike. Successfully patched 500+ servers in a single day with 100% accuracy. GOJobManager Designed a high-performance job scheduler for distributed systems with a focus on high availability, low latency, and consistency. Efficiently manages functional jobs using kafka queues and locking mechanisms. Utilizes Redis for cache management, ensuring fast and reliable performance under heavy loads. Features a distributed design capable of handling large volumes of jobs seamlessly. Implements a locking mechanism and consistent hashing approach to distribute jobs fairly across the cluster. K8s Cluster Setup Set up multiple Kubernetes clusters as part of the expansion plan for Paytm UPI and the newly launched UPI lite service. Configured clusters with 200+ of Linux servers from vendors like Cisco, Huawei, and Dell. Ensured seamless transitions and zero downtime for services and deployments through meticulous planning and execution. Established robust connections between clusters using ArgoCD for deployment management and Hashicorp Vault for secrets management, enabling secure and efficient application and secrets management. Implemented comprehensive monitoring solutions using Prometheus and Grafana, providing real-time insights into cluster health and performance. Security Monitoring Analytics Tool - To provide collated view of logs generated by different security tools like Anti Viruses. Encrypted Message/File sharing Tool with Key chaining techniques for point-to-point sharing. To prevent unauthorized sharing of information in the organization.
MINISTRY OF EDUCATION, GOVERNMENT OF INDIA
Sep 20215 mosJan 2022

Delhi, India

Optimize, build and deploy robust scalable systems. Responsibilities - 1. Manage Cloud Infrastructure 2. Code highly optimized back end 3. Debug existing systems Tech Stack- 1. Python 2. Django 3. AWS Code Deploy 4. AWS Code pipeline 5. Load Balancers
GitHub
@mastermanas805

Manas’s AI Stack

claude code
claude code
cursor
cursor
langfuse
langfuse
langgraph
langgraph
langsmith
langsmith

Education

Inderprastha Engineering College

Bachelor of Technology, Computational Science

Inderprastha Engineering College

20184 yrs2022
Central Board of Secondary Education

12

Central Board of Secondary Education

20171 yr2018

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Headline

Agentic AI / Software Engineering | Backend | Distributed & Low Latency Systems | Kubernetes | Java | Go | Python | Scala | C++ | Spring Boot | AWS

About

Manas Srivastava is a highly skilled software engineer with deep expertise in Agentic AI, backend development, cloud infrastructure, AI-driven analytics, and large-scale distributed systems. Beyond building scalable platforms, he has a strong track record of taking products from 0 to 1—working across the entire lifecycle from identifying customer problems and shaping product direction to designing, implementing, and deploying production-ready solutions. He thrives in ambiguous environments, moves quickly from idea to execution, and consistently turns innovative concepts into practical, scalable products.

Location

India

AI stack

claude code

cursor

langfuse

langgraph

langsmith

Work experience

Software Development Engineer 2 at Uber, May 2026 - Present · 4 mos, Bengaluru

Software Engineer II at Intuit, Mar 2025 - May 2026 · 1 yr 3 mos, Pioneered Agentic Commerce: Implementated Google AP2 and OpenAI ACP in Python to architect a Multi-Agent Payment System for secure, transparent conversational commerce via chat. Engineered AI Automation: Architected and lead the team of 2 to develop an AI Automation Agent (leveraging custom MCP Servers) that integrated PagerDuty, Splunk, and Slack to automate on-call reporting and provide proactive issue-resolution support, significantly reducing Mean Time To Respond (MTTR). Accelerated Development: Utilized advanced AI tools and custom tracing servers to rapidly generate 80% of production code with resilient design principles and integrated unit/integration tests. Led Architectural Consolidation: Migrated customer accounts (Solo and Enterprise) to a single unified entity, enabling comprehensive multi-currency and multi-country taxation and accounting support across the US/Canada. Delivered AI-Powered Customer Value: Led development of an AI-powered "done-for-you" experience, enabling customers to seamlessly query orders, resulting in a 98% conversion rate of customers landing on the cart. Managed Core Commerce Systems: Ensured smooth, high-volume order placement across Intuit’s ecosystem (TurboTax, QuickBooks, MailChimp) and oversaw secure payment processing (Credit Card, Apple Pay, Google Pay). Deep Technical Stack: Architected solutions using Java, Spring Boot, Python, Apache Pulsar/Kafka, and managed AI/ML Ops including Hugging Face fine-tuning and RAG implementation.

Software Engineer II at Sumo Logic, Sep 2024 - Mar 2025 · 7 mos

Software Engineer at Sumo Logic, Aug 2024 - Mar 2025 · 8 mos, Remote, Sumo Query Autocomplete - Architected an autocomplete backend for Sumo Query Language with a team of 3, providing users with query suggestions similar to a Google search experience. This project significantly reduced the learning curve for new users on the Sumo Logic platform, enabling them to query logs effectively without requiring extensive expertise in Sumo Query Language. Data Engine For Artificial Intelligence Based Recommendation - Designed the core engine of an LLM-driven AI recommendation system for debugging logs, responsible for extracting relevant data from customer logs to suggest precise queries. This system enables the LLM to generate queries for effective debugging, plotting, and analysis of system logs and metrics. LLM based Query Summarization - Developed an LLM-powered query summarization system using Meta’s LLaMA to streamline dashboards and simplify complex queries, improving onboarding experiences for new SumoLogic customers.

Software Engineer at Paytm Payments Bank, Jul 2022 - Oct 2023 · 1 yr 4 mos, Noida, Uttar Pradesh, India, I have worked on a Server Patching Tool that creates automated updates to software and operating systems in live servers as per RBI guidelines. The tool specializes in patching critical infrastructure with graceful reboot and zero downtime of services such as Kubernetes, Etcd, Kafka, Elasticsearch, MySQl and Aerospike. The tool is built in Golang, gin(backend framework), reactjs typescript (frontend), HA proxy load balancer and rate limiter, Redis for cache management, and high concurrency management. It can be deployed on many servers/k8s pods such that it acts as one under the concepts of distributed systems. GOJobManager - It is a high-performance job scheduler designed for distributed systems, such as multi-pod/server applications. With a focus on high availability, low latency, and consistency, It efficiently manages functional jobs with the help of queues and locking mechanisms. It uses Redis for cache management, ensuring fast and reliable performance even under heavy loads. It's distributed design ensures that it can handle large volumes of jobs with ease, while its locking mechanism and consistent hashing approach ensure that jobs are distributed fairly across the cluster. We successfully implemented the CIS security benchmarks across the production Linux servers in our infrastructure with automation. These servers were critical to our organization, serving highly important services. Despite the challenges, my efforts resulted in zero downtime and greatly enhanced the cyber security of our systems. The implementation of these benchmarks helped to ensure that our infrastructure was secure and compliant. Tech Stack Used - Python, Django, Go, Salt Stack, Docker, Kubernetes, Linux (Ubuntu and CentOS), AWS, Elastic Load Balancer, Elastic Search, Jenkins, Graphana, Statsd, Etcd, Apache HTTP Server, Nginx, HA-Proxy, GIN(Golang Backend), ReactJS

Software Engineer at Paytm Payments Bank, Jan 2022 - Oct 2023 · 1 yr 10 mos, Noida, Uttar Pradesh, India, Dr. Patch Developed a Server Patching Tool adhering to Reserve Bank of India guidelines, enabling automated updates for software and operating systems on live servers. Specialized in patching critical infrastructure with graceful reboot and zero downtime for services like Kubernetes, Etcd, Kafka, Elasticsearch, MySQL, and Aerospike. Successfully patched 500+ servers in a single day with 100% accuracy. GOJobManager Designed a high-performance job scheduler for distributed systems with a focus on high availability, low latency, and consistency. Efficiently manages functional jobs using kafka queues and locking mechanisms. Utilizes Redis for cache management, ensuring fast and reliable performance under heavy loads. Features a distributed design capable of handling large volumes of jobs seamlessly. Implements a locking mechanism and consistent hashing approach to distribute jobs fairly across the cluster. K8s Cluster Setup Set up multiple Kubernetes clusters as part of the expansion plan for Paytm UPI and the newly launched UPI lite service. Configured clusters with 200+ of Linux servers from vendors like Cisco, Huawei, and Dell. Ensured seamless transitions and zero downtime for services and deployments through meticulous planning and execution. Established robust connections between clusters using ArgoCD for deployment management and Hashicorp Vault for secrets management, enabling secure and efficient application and secrets management. Implemented comprehensive monitoring solutions using Prometheus and Grafana, providing real-time insights into cluster health and performance. Security Monitoring Analytics Tool - To provide collated view of logs generated by different security tools like Anti Viruses. Encrypted Message/File sharing Tool with Key chaining techniques for point-to-point sharing. To prevent unauthorized sharing of information in the organization.

Cloud Engineer at MINISTRY OF EDUCATION, GOVERNMENT OF INDIA, Sep 2021 - Jan 2022 · 5 mos, Delhi, India, Optimize, build and deploy robust scalable systems. Responsibilities - 1. Manage Cloud Infrastructure 2. Code highly optimized back end 3. Debug existing systems Tech Stack- 1. Python 2. Django 3. AWS Code Deploy 4. AWS Code pipeline 5. Load Balancers

Education

Bachelor of Technology, Computational Science, Inderprastha Engineering College

12, Central Board of Secondary Education

Public links

github: https://github.com/mastermanas805