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.
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 on multi-tenant model-serving architecture, inference routing, and financial risk analytics using Java, Kubernetes, AWS, and GCP.
I've 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 (3.95 GPA).
Building multi-tenant cloud platforms and developer tooling across AWS, Azure, and GCP
Led cross-functional teams of 10 engineers; 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, improving availability to 99.9% and cutting inference latency by 25%. Designed multi-tier inference routing supporting hundreds of millions of daily search queries.
Engineered a Financial Risk Reporting platform on GCP processing 10M+ daily transactions for fraud detection and chargeback analytics. Led Databricks analytics (30% efficiency gain), DynamoDB migration (30% cost reduction), and data-layer modernization (50% faster feature delivery).
Architected the Azure Right-to-Provision service automating subscription creation and budget management for 5,000+ engineers. Built RBAC with automated cloud billing, led delivery of the Cloud Portal 2.0 developer experience platform, and built a Kafka-based observability system reducing incident detection time.
Led monitoring and alerting across 50+ data centers and 10,000 servers with Icinga, Grafana, and PagerDuty, achieving 99.99% uptime for IBM Cloud. Built a 500 TB/day logging pipeline with Logstash, Kafka, Elasticsearch, and Kibana that informed $3M+ in infrastructure cost reductions.
Overhauled the in-house Azure billing system in Java, delivering a 40% performance improvement and increased pipeline reliability. Implemented Cassandra data modeling and query optimization for a real-time analytics platform, achieving 50% faster data retrieval.
Delivered web-security projects for ANZ Bank with Java and Spring, and built an Android OTP authentication app that reduced unauthorized access by 50%. Trained 5 interns in the Finacle e-Banking Framework and REST API design; all five shipped features to production.
Career trajectory
Each role widened the scope: from shipping secure applications to setting technical direction for systems used across organizations.
Leading multi-tenant model-serving and search infrastructure supporting hundreds of millions of daily Walmart Search queries.
Engineered GCP-based financial risk platforms for fraud and chargeback analytics processing 10M+ daily transactions.
Designed and delivered cloud automation, billing, observability, and API platform capabilities.
Led a team of 10 engineers running monitoring for 50+ data centers and 10,000 servers at 99.99% uptime. Built 500 TB/day logging with Kafka, Elasticsearch, and Kibana, informing $3M+ in cost reductions.
Overhauled the Azure billing system in Java with a 40% performance boost. Implemented Cassandra data modeling achieving 50% faster data retrieval for real-time analytics.
Delivered web-security projects for ANZ Bank with Java and Spring. Built an Android OTP authentication app reducing unauthorized access by 50%, and trained 5 interns who all shipped to production.
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.
University of Illinois Urbana-Champaign · 2022 – 2024 · GPA 3.95
The University of Texas at Dallas · 2014 – 2016 · GPA 3.9
Visvesvaraya Technological University · 2008 – 2012
Next problem
Open to staff–principal engineering roles, interesting infrastructure problems, and conversations about building at scale. If the work sounds interesting, reach out. I read every message.