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Devops Engineer with 5+ years in AWS, Kubernetes & CI/CD
AI is analyzing your overall score…
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Results-driven DevOps Engineer with 5 years of experience architecting and operating highly available, automated cloud infrastructure on AWS and Kubernetes in mission-critical fintech and enterprise environments. Proven track record of reducing deployment times by 60%+ through CI/CD automation, implementing zero-downtime release strategies, and enforcing infrastructure-as-code at scale. Currently expanding into AI/ML DevOps - integrating Claude AI APIs and LLM workflows into cloud pipelines to accelerate delivery and enable intelligent operations.
Heritage Institute of Technology
B.Tech · Computer Science
August 1, 2015 – June 30, 2019
Infosys
DevOps Engineer
January 1, 2025 – Present
Pune, Maharashtra, India
Accenture
Infra Managed Service Analyst
April 1, 2021 – December 1, 2024
Pune, Maharashtra, India
Certified Kubernetes Administrator (CKA)
The Linux Foundation
June 1, 2026 – Present
AWS Certified Solutions Architect - Associate
Amazon Web Services
January 1, 2024 – Present
AZ-900 - Azure Fundamentals
Microsoft
January 1, 2021 – Present
Cultural Fit Analysis
The candidate's experience across multiple enterprise clients (Accenture) and a major financial institution (HSBC via Infosys) demonstrates adaptability to diverse organizational cultures and strict regulatory environments. Their proactive pursuit of certifications (AWS CSA, CKA in progress) and interest in AI/ML DevOps indicates a strong drive for continuous learning and staying current with industry trends, which aligns well with a growth-oriented culture. The emphasis on automation and reducing toil suggests a pragmatic and efficiency-focused mindset.
Soft Skills & Operational Fit
The candidate demonstrates strong operational ownership and a production reliability mindset, crucial for a senior DevOps role. Their experience in BFSI environments highlights adherence to strict change management and audit processes, indicating a disciplined approach to operations. The focus on automation-first principles and continuous learning, particularly in AI/ML DevOps, suggests adaptability and a forward-thinking approach. Cross-functional collaboration is also highlighted, which is essential for integrating DevOps practices effectively.