- Performed server-level testing and rack-level testing to validate high-density server systems for production readiness and quality standards.
- Diagnosed hardware failures by analyzing BMC/IPMI logs, system event logs, and diagnostic outputs to isolate root causes.
- Conducted rack-level diagnostics across compute nodes, networking components, NICs, storage devices, power distribution, cabling, and supporting infrastructure.
- Partnered with hardware, firmware, manufacturing, and quality engineers to investigate failures, validate fixes, and improve product reliability.
- Executed hardware validation, system bring-up, and functional testing using Linux CLI, manufacturing test tools, and standard operating procedures.
- Maintained test reports, inspection records, and quality documentation aligned with manufacturing, ISO, and organizational standards.
Dipesh Wosti
Software Engineer
DevOps Engineer
AI Engineer
Hardware Validation • Automation • AWS
About
Building Scalable Systems with AI & Cloud.
Artificial Intelligence master's student and engineer with experience across server validation, DevOps, cloud infrastructure, data pipelines, and automation. Comfortable working from hardware diagnostics and Linux CLI workflows through AWS, Kubernetes, CI/CD, and observability systems.
I like building practical systems that make complex work easier to operate, whether that means validating high-density servers, automating ETL workflows, or using AI tools to create faster ways to query, monitor, and support data-driven systems.
Experience
Where I've worked
- Built and managed scalable data processing pipelines on AWS using Python and cloud-native services for ingestion and transformation.
- Designed and automated ETL workflows with Jenkins CI/CD pipelines, improving deployment efficiency and consistency.
- Developed and optimized SQL queries for extracting, transforming, and analyzing structured data across relational databases.
- Deployed and managed distributed systems on Kubernetes and EKS for scalable data workloads and high-availability services.
- Provisioned reproducible data infrastructure environments with Terraform.
- Built monitoring and observability systems with Grafana, Splunk, and Dynatrace to track pipeline performance and detect anomalies.
- Collaborated with cross-functional teams to support data-driven decisions and reliability improvements.
Projects
Selected work shaped around reliability, delivery, and backend scale.
AI-Powered Data Query System
Built a natural-language database interaction system using LLMs and MCP tools, helping users query data and trigger backend workflows through an AI-assisted interface.
Kubernetes-Based Data Pipeline Deployment
Designed and deployed containerized applications for data workflows on AWS EKS, focusing on scalable infrastructure, cloud networking, and deployment reliability.
AI Email Assistant
Created an n8n workflow that reads incoming emails, generates AI-powered responses with an LLM, and drafts replies automatically for faster communication workflows.
Skills
Tech stack
Languages
Python
Shell Scripting
SQL
HTML/CSS
Systems
Linux CLI
Ubuntu
Windows
macOS
AI / ML
OpenAI
LLMs
MCP
OpenCV
n8n
Cloud / Infra
AWS
Google Cloud
Kubernetes
EKS
Docker
Terraform
Jenkins
Git
Jira
Networking
TCP/IP
DHCP
DNS
VLAN
Routing
Switching
Ethernet
SSH
Hardware
Server Hardware
PCB
PDU
Switches
SSD/HDD
Firmware Validation
BIOS Configuration
Contact
Get in touch
Open to engineering roles, collaborations, and AI-driven opportunities.