Professional Experience
Move37 AI Technologies Pvt. Ltd.
Software Engineer | Jan 2026 – Present
- Working on AI-driven data and intelligent document processing systems.
- Designing and building backend services with a focus on scalability, reliability, and clean architecture.
- Collaborating closely with founders and senior leadership on technical roadmap and execution.
- Contributing across backend development, system design, and deployment workflows.
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Tussle Digital
Python Backend Developer | Sept 2025 – Nov 2025
- Developing and maintaining backend APIs using Python (FastAPI & Django).
- Handling client project for APS (Australia Payroll Services) — managing technical queries, backend issues, and optimizing performance.
- Leveraging SQL, PostgreSQL, and Python scripts for debugging and analytical reports.
- Managing Virtual Machines and RDP sessions on Linux & Windows servers.
- Collaborating with DevOps teams for CI/CD automation and API deployment on AWS.
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RakshaIT (Subsidiary of Tussle Digital)
Python Backend Developer | Sept 2025 – Nov 2025
- Building RESTful APIs using Django and FastAPI frameworks with secure authentication.
- Implementing CRUD operations, schema optimization, and data validation in PostgreSQL.
- Testing APIs using Postman and ensuring adherence to OpenAPI standards.
- Working across macOS, Linux, and Windows environments for cross-platform development.
- Contributing to backend architecture and integration of new features for enterprise clients.
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Solytics Partners
Backend Developer
Mar 2024 – Feb 2025
- Developed WarpDrive CLI tool (Python-based) that accelerated JupyterHub execution by 80%.
- Engineered a distributed execution engine (Django + Golang) cutting task runtimes from 5 mins to <1 min.
- Created and optimized APIs for distributed workloads and task orchestration.
- Implemented CI/CD pipelines using Jenkins, Groovy, and GitHub Actions.
- Collaborated with data science teams to deploy ML workflows efficiently.
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DevOps Engineer
Mar 2025 – May 2025
- Transitioned internally to explore end-to-end DevOps lifecycle and infrastructure automation.
- Led containerized deployments with Docker, Kubernetes, Helm, and Terraform.
- Implemented h2o.automl integration for production-grade machine learning pipelines.
- Deployed and managed multi-cloud infrastructure (AWS, Azure, and on-premises).
- Automated environment provisioning using Ansible and Terraform, improving deployment speed by 60%.
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🚀 Bridging Backend Engineering & DevOps — delivering reliable, scalable, and automated systems.
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