Mohit Sehgal — DevOps Engineer

Technology-Driven Engineering Leader with 8+ years of experience in architecting Cloud-Native Data & AI solutions and modern DevOps practices. Specialized in building robust, scalable AI applications deployed across multi-cloud environments, with deep expertise in end-to-end data engineering solutions. 1. Proven track record in designing secure, automated CI/CD workflows, Infrastructure as Code, and cloud-native deployment strategies that accelerate innovation. Experienced in delivering enterprise-scale data solutions, including end-to-end data warehouse and data integration pipelines that enable advanced analytics and AI adoption. 2. Adept at embedding security into DevOps and AI workflows through advanced automation. Recognized for cross-functional collaboration and driving enterprise adoption of AI-powered solutions with measurable business impact. 3. Architected and delivered more than 20 enterprise-scale Data & AI applications/APIs on cloud-native architectures, defining reference architectures while remaining hands-on in implementation. 4. Gained end-to-end SDLC experience in Agile environment and have built multiple applications and APIs using Flask, Django, Next.js etc. Strong scripting expertise in Python, Bash and related technologies. 5. Designed end-to-end enterprise data ecosystems using Microsoft Fabric and Azure Synapse, establishing standards for ingestion, transformation, modeling, governance, and analytics. 6. Owned cloud infrastructure architecture and capacity planning, creating BOM estimates, cost optimization strategies, and secure environment blueprints. 7. Designed and implemented CI/CD frameworks for data and AI workloads, enabling automated testing, controlled releases, and environment consistency. 8. Orchestrated infrastructure as code (IaC) using tools like ARM templates and Terraform to streamline provisioning and scaling of cloud resources. 9. Partnered with executive stakeholders and cross-functional teams, translating business strategy into scalable technical architecture while actively contributing to hands-on delivery. 10. Managed containerization and orchestration using Docker and Kubernetes, optimizing resource utilization and enabling efficient scaling. 11. Conducted regular security assessments, vulnerability scans, and penetration testing of AI Applications to proactively identify and mitigate security risks. 12. Defined enterprise observability and security frameworks for AI Platforms, integrating monitoring, logging, access controls, and compliance best practices.

Stackforce AI infers this person is a Cloud and AI Solutions Architect with a strong DevOps focus.

Location: Delhi, India

Experience: 7 yrs 6 mos