Help & Supportcareers@gravityer.com
Devops Engineer with 4+ years in AWS, Kubernetes & AI/ML Platforms.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
I have been working in DevOps for the past four years, handling infrastructure setup, CI/CD pipelines, monitoring, incident response, and production support. My core stack is AWS and Kubernetes, with hands-on experience across Azure and GCP as well. I take ownership of the systems I build — uptime, performance, and reliability are things I track closely, not just hand off. In my current role at Word Works AI, I work on the DevOps side of production AI/ML platforms on EKS, which has given me hands-on experience with GPU workloads, real-time inference pipelines, and the kind of scaling challenges that come with running AI systems in production.
Pune University
Bachelor of Engineering
August 1, 2020 – Present
Government Polytechnic, Dharashiv
Diploma in Engineering
August 1, 2016 – Present
Word Works AI
DevOps Engineer
January 1, 2026 – Present
India
Greatways Technologies
DevOps Engineer
November 1, 2024 – January 1, 2026
India
NoBroker Technologies
DevOps Engineer
February 1, 2022 – October 1, 2024
India
Cultural Fit Analysis
The candidate's diverse experience across multiple companies and their involvement in critical infrastructure projects, including an Azure-to-AWS migration and AI/ML platform deployments, indicate a strong cultural fit for a dynamic DevOps role. Their emphasis on automation, security, and continuous improvement aligns well with modern DevOps principles. The breadth of skills and tools used suggests a willingness to learn and adapt.
Soft Skills & Operational Fit
The candidate demonstrates strong ownership, a proactive approach to problem-solving, and a focus on reliability, performance, and cost efficiency. Their experience in incident response, RCA, and postmortems indicates a mature operational mindset. The ability to work with real-time, low-latency systems and AI/ML platforms suggests adaptability to complex, high-demand environments.