Headline

aSDE @ Swiggy · VIT ’26 | Golang · Python · AWS | Building LLM-powered systems & backend infra at scale

About

I'm a final-year CS student at VIT-AP with a minor in AI/ML, and I tend to build things when something catches my curiosity — sometimes it's a lift allocation system after watching elevators behave inefficiently at a company event, sometimes it's a full deployment platform. It usually starts with "that's an interesting problem" and ends with a GitHub repo. For the last six months, I've been an SDE intern at Swiggy on the Data & Platform team. Built an automated deployment pipeline that abstracts all infra decisions away from the developer (think Vercel but on Swiggy's internal stack), a Slack-powered visibility platform that kept engineering teams on top of open blockers and stalled threads, and Swiggy's AI context and benchmark layer — pulling from MCP sources and benchmarking LLMs against real Swiggy problems, not synthetic ones. Technically I'm most at home in Golang and Python, working across platform engineering, cloud infra (AWS, Terraform, Kubernetes), and applied AI — LLM integrations, agentic systems, and MCP. I hold Oracle Cloud certifications in GenAI and Data Science. Now joining Toing full-time as an aSDE. Still building. Still curious.

Location

Bengaluru

AI stack

codex

cursor

opencode

Work experience

Associate Software Engineer at Swiggy, Jun 2026 - Present · 3 mos, Hybrid, Working on the Vendor/Restaurant side of Swiggy and Toing.

Backend Engineering Intern at Swiggy, Dec 2025 - Jun 2026 · 7 mos, Remote, Engineered a new automated deployment method with the principal architect using Terraform and AWS Controllers for Kubernetes (ACK). Engineers point to a repo and the entire infra stack — resources, config, provisioning — is handled automatically. Zero manual intervention at deploy time. Built an internal project visibility platform that aggregated all ongoing engineering projects and parsed Slack channels to detect open blockers, unresolved threads, and stalled pointers — automatically nudging the right owners via Slack. Gave program managers and engineering leads real-time visibility across active work without any manual status updates. Implemented Swiggy's AI context and benchmark layer using MCP sources (Glean, Grafana, GitHub CLI, Prometheus) to establish verified sources of truth for internal AI systems, and built custom benchmarks grounded in real Swiggy engineering challenges. Onboarded multiple engineering teams to the layer. Stack: Golang, Python, Terraform, ACK, AWS (EKS, CodeBuild, EC2, S3, SQS), Docker, Slack API, Prometheus, Grafana, Glean, GitHub CLI, MCP, LLM/GenAI tooling

Education

Bachelor of Technology - BTech, Computer Science Engineering with minor in AI and ML, VIT-AP University

Public links

github: https://github.com/Swaraj-sync