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Hi, I’m Laxmi Sai Vamshi Kalva. I’m a software engineer focused on building scalable backend systems and distributed data platforms for real-time processing and high-throughput services. I design event-driven architectures and streaming pipelines using Java, Python, Kafka, and Spark, with a strong emphasis on cloud-native development on AWS, system reliability, observability, and latency optimization for production-scale services. I’ve built data pipelines for ranking, recommendation, and analytics workloads with a focus on fault tolerance and scalability. I also work on embedding-based retrieval pipelines and feature stores, have run LLM-assisted ranking experiments, and deploy services on Docker/Kubernetes with robust monitoring and automated experimentation to accelerate delivery and improve quality.…Hi, I’m Laxmi Sai Vamshi Kalva. I’m a software engineer focused on building scalable backend systems and distributed data platforms for real-time processing and high-throughput services. I design event-driven architectures and streaming pipelines using Java, Python, Kafka, and Spark, with a strong emphasis on cloud-native development on AWS, system reliability, observability, and latency optimization for production-scale services. I’ve built data pipelines for ranking, recommendation, and analytics workloads with a focus on fault tolerance and scalability. I also work on embedding-based retrieval pipelines and feature stores, have run LLM-assisted ranking experiments, and deploy services on Docker/Kubernetes with robust monitoring and automated experimentation to accelerate delivery and improve quality.

Laxmi Sai Vamshi Kalva

Full Stack Developer, Back-End Developer, Web Developer, +2

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Hi, I’m Laxmi Sai Vamshi Kalva. I’m a software engineer focused on building scalable backend systems and distributed data platforms for real-time processing and high-throughput services. I design event-driven architectures and streaming pipelines using Java, Python, Kafka, and Spark, with a strong emphasis on cloud-native development on AWS, system reliability, observability, and latency optimization for production-scale services. I’ve built data pipelines for ranking, recommendation, and analytics workloads with a focus on fault tolerance and scalability. I also work on embedding-based retrieval pipelines and feature stores, have run LLM-assisted ranking experiments, and deploy services on Docker/Kubernetes with robust monitoring and automated experimentation to accelerate delivery and improve quality.…Hi, I’m Laxmi Sai Vamshi Kalva. I’m a software engineer focused on building scalable backend systems and distributed data platforms for real-time processing and high-throughput services. I design event-driven architectures and streaming pipelines using Java, Python, Kafka, and Spark, with a strong emphasis on cloud-native development on AWS, system reliability, observability, and latency optimization for production-scale services. I’ve built data pipelines for ranking, recommendation, and analytics workloads with a focus on fault tolerance and scalability. I also work on embedding-based retrieval pipelines and feature stores, have run LLM-assisted ranking experiments, and deploy services on Docker/Kubernetes with robust monitoring and automated experimentation to accelerate delivery and improve quality.

Available to hire

Hi, I’m Laxmi Sai Vamshi Kalva. I’m a software engineer focused on building scalable backend systems and distributed data platforms for real-time processing and high-throughput services. I design event-driven architectures and streaming pipelines using Java, Python, Kafka, and Spark, with a strong emphasis on cloud-native development on AWS, system reliability, observability, and latency optimization for production-scale services.

I’ve built data pipelines for ranking, recommendation, and analytics workloads with a focus on fault tolerance and scalability. I also work on embedding-based retrieval pipelines and feature stores, have run LLM-assisted ranking experiments, and deploy services on Docker/Kubernetes with robust monitoring and automated experimentation to accelerate delivery and improve quality.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Work Experience

Software Engineer at Meta

July 1, 2025 - Present

Contributed to backend services supporting large-scale feed ranking data pipelines using Java and Spring Boot, optimizing data partitioning and query tuning to reduce end-to-end latency by 2.5 seconds under peak traffic. Built components for embedding-based retrieval pipelines, integrating ranking signals from feature stores and ANN search infrastructure to improve content relevance and reduce user fatigue. Developed distributed stream processing with Apache Spark and Kafka, including schema evolution, fault-tolerant checkpointing, and backpressure handling to deliver low-latency feature generation (<150ms) for real-time inference. Implemented governed feature store pipelines with lineage tracking, IAM access control, and encryption policies, reducing feature drift and improving consistency across production ranking services. Implemented experiments leveraging LLM-assisted ranking evaluation, streamlining cycles by 40% across 10+ configurations and A/B testing environments. Hardened ra

Software Development Engineer at Amentum

October 1, 2024 - May 31, 2025

Engineered backend services for predictive maintenance pipelines using Java Spring Boot and Kafka to analyze aircraft telemetry, reducing unplanned downtime and improving anomaly detection accuracy. Delivered scalable event ingestion architecture using AWS IoT Core, Kafka, and Kinesis, enabling near real-time analytics (<2s latency) across 1,000+ devices with partitioned processing and automated retry policies. Architected secure cloud-native infrastructure on AWS (EC2, S3, Lambda, RDS) using Terraform-based IaC, implementing IAM role separation, KMS encryption, and VPC network isolation. Formed containerized microservices deployed on Kubernetes (EKS) with automated CI/CD pipelines and service discovery, improving deployment reliability and release cadence. Developed an Angular-based monitoring dashboard integrated with REST APIs to visualize aircraft telemetry streams, maintenance alerts, and anomaly detection insights, improving operational visibility. Applied event-driven analytics

Software Engineer at KPIT

February 1, 2021 - July 31, 2023

Constructed backend payment and ledger microservices using Node.js and REST APIs, reducing p95 latency from 5s to under 2s through asynchronous processing, query optimization, and improved service concurrency. Formulated and optimized relational data systems on PostgreSQL (migration from MySQL), implementing indexing strategies, partitioning, and ACID-compliant transactions, reducing reconciliation time by 40% and improving audit consistency. Deployed Redis caching and Elasticsearch indexing for transaction search and account lookup, reducing API latency from 400ms to 120ms and enabling real-time low-latency query access in production workloads. Established internal financial analytics dashboards using React.js and TypeScript with role-based access controls, enabling monitoring of transaction anomalies and reducing manual investigation time. Configured event-driven microservices using Apache Kafka for payments, settlements, and fraud detection pipelines, improving system throughput and