Srujan Chilveri profile photo 1 on Tal

Srujan Chilveri

Software Engineer | DevOps & SRE | Cloud & Kubernetes | CI/CD | Automation | Distributed Systems

Bengaluru

2+ years of work experience

Bottomline
Jan 202610 moPresent

Bengaluru

• Architected a Spring Boot and React-based real-time communication platform that benchmarked 3 update delivery models API Polling, Server-Sent Events, and STOMP-based WebSockets across file updates, notifications, and chat workflows. • Designed and implemented persistent push-based communication flows using SseEmitter, WebSocket topics, and per-user queues, reducing dependency on redundant polling and enabling event-driven UI updates. • Built an observability layer with Prometheus, Micrometer, Spring Boot Actuator, and Grafana, instrumenting 10+ custom metrics across 3 backend branches to analyze request overhead, event delivery, and connection behavior
Airbus
Jul 20256 mosDec 2025

Bengaluru

• Developed dynamic Java algorithms for industrial simulations, including an adaptive 'Spare Shift' logic to correct lead-time inaccuracies and a 'Secondary Pull' mechanism to filter upstream assembly line constraints. • Architected a Java-Python bridge using the Alpyne library to wrap complex Discrete Event Simulations into standard Gymnasium environments, enabled 'headless' parallel training of Al agents, decoupling the simulation engine from the training logic. • Engineered a Deep Reinforcement Learning (DQN) solution for inventory optimization using Python (Stable Baselines3) and AnyLogic, achieving a 32% reduction in operational costs compared to traditional heuristic rule-based policies.
PwC Acceleration Centers in India
Feb 20256 mosJul 2025

Bengaluru, Karnataka, India

PwC Acceleration Launchpad Program Graduate 2025 •Demonstrated strong potential in the technical round and got selected for the PwC Acceleration Center Launchpad Program
Caze Labs Private Limited
May 20241 yr 1 moMay 2025

Bengaluru, Karnataka, India

• Architected and implemented 3+ high-performance CI/CD pipelines via GitHub Actions that slashed deployment time, enabling rapid iteration and dramatically accelerating time-to-market for critical releases • Revitalized legacy Docker infrastructure by diagnosing and resolving 60%+ of containerization inefficiencies, transforming deployment reliability across development, staging, and production environments • Engineered sophisticated CI workflows for multi-organizational GitHub environments that execute comprehensive test suites at both root and context-specific levels, significantly enhancing cross-repository integrity and system performance

Srujan’s AI Stack

anthropic apis
anthropic apis
claude code
claude code
claude
claude
github copilot
github copilot
hugging face
hugging face
openai
openai

Education

Manipal institute of technology

Bachelor of Technology - BTech Honours, Computer Science Engineering (Spl. Cybersecurity)

Manipal institute of technology

20224 yrs2026

12th grade, Science

Geetanjali Olympiad School - India

20211 yr2022

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Headline

Software Engineer | DevOps & SRE | Cloud & Kubernetes | CI/CD | Automation | Distributed Systems

About

I am a Computer Science Engineer with a particular affinity towards creating scalable and reliable software systems. The areas of interest for me include Software Engineering, DevOps, SRE, Cloud Infrastructure, and Cybersecurity, with a focus on automation and AI-based engineering. I work extensively through the entire lifecycle of software development - from building applications and automation of CI/CD pipelines to containerization, cloud infrastructure, observability, and system reliability. I have practical experience with technologies like Docker, Kubernetes, AWS, GitHub Actions, Jenkins, Argo CD, Terraform, Kafka, and Trivy and programming skills with Python, Java, Go, C, and SQL. Having gone through a curriculum in Cybersecurity gives me a firm knowledge of topics such as networking, secure systems, ethical hacking, cryptography, and digital forensics. In addition, I have an interest in Artificial Intelligence and Machine Learning, with hands-on experience with tools like Scikit-learn and TensorFlow. The projects that appeal to me most are those in which I will get an opportunity to solve difficult engineering problems, improve system reliability, automate repetitive tasks, and grow as a Software Engineer, DevOps Engineer, or SRE. Aside from technology, some of the other things I value is mentoring and teaching others. For instance, I have represented my college and school in football and basketball. I am always keen to meet people working on interesting problems in Software Engineering, Cloud, DevOps, SRE, Cybersecurity, and AI. Feel free to contact me in case you would like to discuss anything technology-related or collaborate on any projects.

Location

Bengaluru

AI stack

anthropic apis

claude code

claude

github copilot

hugging face

openai

Work experience

Trainee Engineer at Bottomline, Jan 2026 - Present · 10 mo, Bengaluru, • Architected a Spring Boot and React-based real-time communication platform that benchmarked 3 update delivery models API Polling, Server-Sent Events, and STOMP-based WebSockets across file updates, notifications, and chat workflows. • Designed and implemented persistent push-based communication flows using SseEmitter, WebSocket topics, and per-user queues, reducing dependency on redundant polling and enabling event-driven UI updates. • Built an observability layer with Prometheus, Micrometer, Spring Boot Actuator, and Grafana, instrumenting 10+ custom metrics across 3 backend branches to analyze request overhead, event delivery, and connection behavior

Software Engineer Intern at Airbus, Jul 2025 - Dec 2025 · 6 mos, Bengaluru, • Developed dynamic Java algorithms for industrial simulations, including an adaptive 'Spare Shift' logic to correct lead-time inaccuracies and a 'Secondary Pull' mechanism to filter upstream assembly line constraints. • Architected a Java-Python bridge using the Alpyne library to wrap complex Discrete Event Simulations into standard Gymnasium environments, enabled 'headless' parallel training of Al agents, decoupling the simulation engine from the training logic. • Engineered a Deep Reinforcement Learning (DQN) solution for inventory optimization using Python (Stable Baselines3) and AnyLogic, achieving a 32% reduction in operational costs compared to traditional heuristic rule-based policies.

Trainee at PwC Acceleration Centers in India, Feb 2025 - Jul 2025 · 6 mos, Bengaluru, Karnataka, India, PwC Acceleration Launchpad Program Graduate 2025 •Demonstrated strong potential in the technical round and got selected for the PwC Acceleration Center Launchpad Program

DevOps Intern at Caze Labs Private Limited, May 2024 - May 2025 · 1 yr 1 mo, Bengaluru, Karnataka, India, • Architected and implemented 3+ high-performance CI/CD pipelines via GitHub Actions that slashed deployment time, enabling rapid iteration and dramatically accelerating time-to-market for critical releases • Revitalized legacy Docker infrastructure by diagnosing and resolving 60%+ of containerization inefficiencies, transforming deployment reliability across development, staging, and production environments • Engineered sophisticated CI workflows for multi-organizational GitHub environments that execute comprehensive test suites at both root and context-specific levels, significantly enhancing cross-repository integrity and system performance

Education

Bachelor of Technology - BTech Honours, Computer Science Engineering (Spl. Cybersecurity), Manipal institute of technology

12th grade, Science, Geetanjali Olympiad School - India