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Devops Engineer with 7+ years in AWS, MLOps & CI/CD
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
MLOps, DevOps & Cloud Platform Engineer with 4+ years of experience in designing, building, and operating highly available AWS platforms for enterprise and data-driven workloads. Experience in Kubernetes, CI/CD automation, Infrastructure as Code, cloud security, and large-scale monitoring systems. Strong hands-on exposure to production-grade MLOps platforms including SageMaker, MLflow, Kubeflow, and GenAI workloads using AWS Services.
Mahaveer Institute of Science and Technology
B.Tech
August 1, 2011 – June 30, 2015
Narayana Jr College
Intermediate in MPC
June 1, 2009 – May 31, 2011
Vidya Bodhini High School
SSC
N/A – Present
Capgemini
DevOps & MLOps Engineer
April 1, 2025 – Present
India
Tech Mahindra
DevOps Engineer
January 1, 2021 – April 1, 2025
India
Wipro
Software Engineer
October 1, 2017 – October 1, 2019
India
Cultural Fit Analysis
The candidate has worked for large, reputable IT services companies (Capgemini, Tech Mahindra, Wipro), indicating experience in structured corporate environments and client-facing projects. The diverse range of technologies and project types (application, ML, GenAI, telecom) suggests adaptability and a willingness to learn new domains, which is a positive indicator for cultural fit in dynamic teams. The progression from Software Engineer to DevOps & MLOps Engineer shows a clear career path aligned with modern cloud and AI/ML infrastructure needs.
Soft Skills & Operational Fit
The candidate's resume indicates a strong operational fit for a senior DevOps role, particularly with a focus on MLOps and cloud platform engineering. The detailed descriptions of responsibilities suggest a proactive approach to designing, implementing, and optimizing complex cloud environments. The emphasis on cost optimization, disaster recovery, and high availability points to a mature understanding of operational best practices. While direct soft skill assessment is not possible without interview data, the breadth of responsibilities implies strong problem-solving and technical leadership capabilities.