# Nandeeswar Reddy > Software Engineer | Java · Go · Python | Distributed Systems · Observability · GenAI | Kubernetes · Kafka · OpenTelemetry | Austin, TX Location: San Francisco, California, United States Profile: https://flows.cv/nandeeswar Software engineer with 4+ years of experience building distributed, cloud-native backend systems across observability platforms, API infrastructure, and AI-integrated tooling. My work sits at the intersection of backend engineering, platform reliability, and modern data pipelines. On the technical side, I work primarily with Java, Go, and Python, building services on Spring Boot that handle high-concurrency workloads. I have hands-on experience instrumenting systems with OpenTelemetry, designing Kafka-to-ClickHouse streaming pipelines, and extending anomaly detection capabilities for alerting systems. More recently I have been integrating RAG-based LLM tooling into operational workflows, which cut incident resolution time significantly on one of my core projects. Before moving into observability and platform work, I spent close to three years modernizing large-scale enterprise platforms, consolidating microservice architectures, and improving API performance for systems serving tens of thousands of concurrent users. That background gave me a strong foundation in understanding how systems behave at scale before problems show up in dashboards. What I genuinely enjoy is working on systems where the feedback loop between infrastructure decisions and product outcomes is tight. Observability, platform engineering, and AI infrastructure are the spaces where I feel most engaged right now. Open to backend, platform, observability, and AI infrastructure roles across the US. MS in Computer Software Engineering, University of Houston-Clear Lake (December 2024) ## Work Experience ### Software Engineer @ SolarWinds Jan 2024 – Present | Austin, Texas, United States Worked on the core observability platform team, focused on telemetry ingestion pipelines, alerting infrastructure, and AI-assisted operational tooling. Built a Kafka-to-ClickHouse streaming pipeline for OTel metrics ingestion that reduced query response times by 35%. Extended the AlertStack anomaly detection service with seasonal baseline modeling, improving alert precision by 28% and reducing noise for on-call teams. Designed and shipped a RAG-based AI runbook assistant integrated with the Service Desk, pulling context from historical incident data and runbook documentation through a vector database. This brought incident MTTR down by 40% across the teams that adopted it. Contributed backend API work in Go and Java, with telemetry instrumentation using OTel SDKs across distributed services. All development followed Secure by Design practices aligned with NIST SSDF requirements. ### Senior Software Engineer @ Infosys Jan 2021 – Jan 2023 | Bengaluru, Karnataka, India • Developed a Java-based microservices application for incident record management, ensuring scalability and reliability. • Designed and implemented RESTful APIs using Spring Boot and PostgreSQL for seamless data management. • Built a messaging queue with Kafka for efficient communication between microservices. • Automated deployments and ensured code quality using CI/CD tools like GitLab, Jenkins, and Docker. ### Software Engineer Intern @ Infosys Jan 2020 – Jan 2021 | India Project: Openreach Real-Time Incident Observability Platform • Re-architected a legacy monolithic incident management system into a Java-based microservices architecture with three domain- aligned services covering fault detection, incident lifecycle management, and notification dispatch. • Applied fault isolation and independent deployability principles across service boundaries, reducing maintenance overhead by 40% and eliminating cross-service regression risk during production releases. • Built high-throughput REST APIs in Java (Spring Boot) engineered to process 100K+ daily telemetry events from Openreach's copper and fiber access network, with optimized PostgreSQL query execution and connection pooling. • Tuned database indexing strategies and query plans to sustain 10K+ concurrent users, reducing backend API response time from 420ms to 210ms (50% faster) under peak NOC load. • Developed a real-time operational intelligence dashboard in React providing NOC engineers with live fault visibility across the access network, consolidating event streams from multiple upstream monitoring sources ## Education ### Bachelor's degree in Electrical and Electronics Engineering Sri Venkateswara University ### Master's degree in Computer Software Engineering University of Houston-Clear Lake ## Contact & Social - LinkedIn: https://linkedin.com/in/nandeeswar-reddy - GitHub: https://github.com/nandeeswarbadugu --- Source: https://flows.cv/nandeeswar JSON Resume: https://flows.cv/nandeeswar/resume.json Last updated: 2026-04-11