AWS Cloud DevOps & SRE Engineer

THARUN KUMAR VADLA

AWS Cloud DevOps Engineer Site Reliability Engineer (SRE)

Linkedin: linkedin.com/in/tharun-kumar-vadla-1b65a6211 Email Id: **********@*****.***

Mexico (Mob): +52-442*******

DevOps Engineer with 3+ years of experience in AWS Cloud and L2 Production Support, with hands-on experience in CI/CD automation, Infrastructure as Code, and containerized application deployment. Skilled in AWS, Jenkins, Docker, Terraform, Git, Kubernetes, Linux, and Ansible, with experience building automated deployment pipelines, managing cloud infrastructure, and deploying applications using Amazon ECS, ECR, S3, and IAM. Strong background in production support, incident management, troubleshooting, and delivering reliable, scalable cloud solutions in Agile environments. Technical Skills:

• DevOps & CI/CD: Jenkins, GitHub, Terraform, Ansible, Docker, Kubernetes, CI/CD pipeline design and automation

• Cloud Platforms: Amazon Web Services (AWS) / IBM / Azure

• AWS Services: ECS, EKS, S3, EC2, Bedrock, Lambda, VPC, API Gateway, SQS, SNS, CloudWatch, Glue, Step Functions, Airflow, Aurora, DynamoDB, Athena, EMR, Cloud Formation

• Programming Languages: Python, Java, SQL

• Data Engineering / ETL: AWS Glue, Airflow (workflow orchestration, data pipelines)

• Monitoring & Logging: CloudWatch, Datadog, Grafana

• Tools & Platforms: Jira, Confluence, Service now

• Web & OS: HTML, CSS, Linux

• Backend & API Development: FastAPI, Flask, REST APIs, Python, Java, Uvicorn, JSON, Swagger.

• Databases: MySQL, Amazon Aurora, DynamoDB, PostgreSQL

• Methodologies: Agile, Scrum, DevOps practices, Technical Leadership

• Core Competencies: System design, cloud architecture, performance optimization, cost optimization, automation, data analysis

• Domain Experience: Banking, Enterprise, and Internal Applications

• Reporting Tools: Power BI

• AI Models: Nova, Titan, GPT-5.4 mini, Claude Haiku 4.5, Gemini 3.0 Flash, DeepSeek-V4-Flash. Key Achievements

• AWS Certified Cloud Practitioner, Developer Associate, Solutions Architect Associate, and AI Practitioner.

• Designed and supported scalable cloud applications deployed on AWS processing data from multiple enterprise sources.

• CI/CD Pipeline for Containerized Application Deployment on AWS Developed REST APIs and AI- powered applications using FastAPI and AWS services.

• Automated deployment and operational workflows using Jenkins and GitHub CI/CD.

• Reduced manual operational effort through automation and monitoring improvements.

• Experience working directly with business stakeholders and cross-functional teams in Agile environments. TCS (SRE & Release Management)

SRE and support management, Mexico (Sept 2023 to till now) Responsibilities

• Designed, developed, and maintained enterprise applications while ensuring high availability, performance, and reliability.

• Contributed to the design, development, and support of scalable cloud-based applications using AWS services.

• Collaborated with business stakeholders and cross-functional teams to gather requirements and deliver optimized technical solutions.

• Built and maintained CI/CD pipelines using Jenkins Declarative Pipelines, automating application build and deployment processes.

• Containerized applications using Docker, created custom Dockerfiles, and built Docker images for consistent deployments.

• Gained hands-on experience deploying containerized applications using Amazon ECS, Amazon ECR, Amazon S3, IAM, and the AWS CLI.

• Automated infrastructure provisioning using Terraform modules and managed infrastructure as code (IaC).

• Worked with Git for source code management and version control following collaborative development practices.

• Collaborated with development teams to manage application releases, deployments, and CI/CD workflows across development environments.

• Monitored application health using AWS CloudWatch, investigated production incidents, performed root cause analysis (RCA), and implemented preventive measures to improve system reliability.

• Developed and optimized SQL queries and database operations to improve application performance.

• Designed, developed, tested, and maintained RESTful APIs to enable seamless integration between enterprise applications and services.

• Worked within Agile and Scrum methodologies, participating in sprint planning, daily stand-ups, code reviews, and production deployments.

• Provided L2 Production Support, resolving incidents, service requests, and deployment issues while meeting defined SLAs.

Description:

• Worked on a cloud-based, data-driven platform that processed data from multiple internal and external sources using business rules and transformation logic.

• Provided L2 Production Support by monitoring applications, troubleshooting production incidents, performing root cause analysis (RCA), and ensuring SLA compliance.

• Monitored application performance and data pipelines, resolving production issues to maintain high availability and reliability.

• Collaborated with development teams to support application releases, deployments, and CI/CD activities in Agile environments.

• Managed and supported Linux and Windows servers, performing system administration, troubleshooting, incident resolution, and routine maintenance.

• Developed and optimized SQL queries to support data validation, troubleshooting, and application performance improvements.

• Gained hands-on experience with AWS Cloud services, Jenkins, Docker, Terraform, Git, Amazon ECS, Amazon ECR, Amazon S3, IAM, and the AWS CLI through automation and deployment projects.

• Developed and maintained RESTful APIs and integrated AI/LLM models with FastAPI-based microservices for chatbot and document-processing solutions.

• Created API documentation using Swagger/OpenAPI and implemented authentication, logging, and error-handling mechanisms to improve API reliability and maintainability. Skills:

• Requirement gathering, analysis, and stakeholder collaboration

• AWS cloud services and cloud-native application support

• CI/CD pipeline implementation, automation, and stability (Jenkins, GitHub)

• DevOps practices and release management

• Data pipeline development and orchestration (AWS Glue, Airflow)

• Monitoring, logging, and performance optimization (CloudWatch, Datadog)

• Database management and querying (PostgreSQL, Aurora, DynamoDB)

• Incident management, root cause analysis, and production support

• Agile and Scrum methodologies

Certifications:

• AWS Certified Cloud Practitioner

• AWS Certified Developer – Associate

• AWS Certified Solutions Architect – Associate

• AWS Certified AI Practitioner

• Microsoft Certified: Azure Fundamentals (AZ-900) – Microsoft, 2026 AI & Cloud Projects

AI Document Search (RAG Chatbot)

Developed an AI-powered chatbot that enables users to chat with PDFs using semantic search and LLMs. Implemented document chunking, embeddings, vector search, and conversational retrieval using LangChain and OpenAI/AWS Bedrock. Tech Stack: React, Tailwind, FastAPI, LangChain, Pinecone/FAISS, Docker, Vercel.

AWS Data Processing Pipeline

Developed serverless data processing and notification workflows using AWS Lambda, Step Functions, SQS, and SNS. Built event-driven solutions to automate business processes, while implementing monitoring, logging, and error-handling mechanisms with CloudWatch to ensure reliability, scalability, and operational efficiency. CI/CD Pipeline for Containerized Application Deployment on AWS Designed and implemented an end-to-end CI/CD pipeline using Jenkins, Docker, and AWS to automate application deployment. Built Docker images, deployed containerized applications using Amazon ECS and ECR, automated deployments with the AWS CLI, and configured Amazon S3 and IAM for secure cloud deployments.

Core Strengths:

Cloud Architecture, AWS Services, API Development, CI/CD Automation, DevOps Practices, Site Reliability Engineering (SRE), Production Support, Incident Management, Root Cause Analysis, System Monitoring, Stakeholder Management, Agile Delivery, Release Management, Automation, Performance Optimization, and Cloud-Native Solutions. Education Summary

• B.Tech – College of Technology and Engineering (2020-2023) Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad Percentage: 93.9%

• Diploma (Polytechnic) (2017-2020)

Government Polytechnic College, Hyderabad

Percentage: 93.47%

• SSC (10th Standard) (2016-2017)

NVHS

CGPA: 9.8

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