Navaneeth Rao / Staff Software Engineer
For 13 years I have designed and operated the infrastructure behind search, payments, vehicles, and machine learning. I turn ambiguous platform problems into systems that teams can trust, scale, and understand.
Scale operated
Things run in production, one log₁₀ axis
Engineering practice
The work is rarely about one tool. It is about finding the constraint, choosing the right boundary, and leaving the system easier to run.
I specialize in distributed systems, ML serving infrastructure, and developer platform engineering. My recent focus has been multi-tenant model-serving architecture, inference routing, and financial risk analytics using Java, Kubernetes, AWS, and GCP.
I have led cross-functional teams of up to 10 engineers, established architecture governance adopted across multiple organizations, and driven $3M+ in infrastructure cost reductions and 30% efficiency gains through platform modernization.
My graduate work spans both fields: an MS in Computer Science from UT Dallas and an MBA from the University of Illinois Urbana-Champaign, earned while shipping full time.
Multi-tenant cloud platforms and developer tooling across AWS, Azure, and GCP.
Teams of up to 10 engineers, plus architecture governance and mentorship across orgs.
99.99% uptime across 50+ data centers and 10,000 servers.
Selected systems
A cross-section of platform work where reliability, scale, developer experience, and business impact had to move together.
Migrated Walmart Search clusters from single-tenant to secure multi-tenant Kubernetes model serving. Designed multi-tier inference routing for hundreds of millions of daily search queries across locales.
Built a financial risk reporting platform on GCP for fraud detection and chargeback analytics, then modernized the data layer behind it: Databricks analytics, a DynamoDB migration, and faster feature delivery.
Architected the Azure Right-to-Provision service, automating subscription creation and budget management with RBAC and automated billing. Led Cloud Portal 2.0 and a Kafka-based observability system that cut incident detection time.
Ran monitoring and alerting for IBM Cloud across 50+ data centers and 10,000 servers with Icinga, Grafana, and PagerDuty. Built a 500 TB/day logging pipeline whose findings drove the infrastructure cost programme.
Overhauled the in-house Azure billing system in Java and made the pipeline more reliable. Implemented Cassandra data modeling and query optimization for a real-time analytics platform.
Delivered web-security projects for ANZ Bank in Java and Spring, and built an Android OTP authentication app. Trained five interns on the Finacle e-banking framework and REST API design; all five shipped to production.
Career trajectory
Each role widened the scope: from shipping secure applications, to running infrastructure, to setting technical direction for systems used across organizations.
Technical range
Deep backend and infrastructure experience, with enough range to follow a production concern from API contract to cluster behavior.
Formal foundations
Technical depth matters more when it is paired with a clear understanding of organizational and economic constraints.
Next problem
Open to staff and principal engineering roles, hard infrastructure problems, and conversations about building at scale. If the work sounds interesting, reach out. I read every message.