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RAG-Based Conversational AI Platform
Production-grade RAG pipelines over 20k+ documents with re-ranking, score filtering, and sub-200ms latency using FastAPI and Qdrant.
FastAPIQdrantLangChain+3
Hey, I'm
Manesh ReddyPonnapati
Software Engineer | AI Engineer
Building AI-driven, production-ready systems
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About Me
3+
Years of Experience
Building production-grade systems across AI and backend
9M+
Records Processed Daily
Microservices processing millions of records across telecom regions
~35%
Latency Reduction
API latency reduced via event-driven architecture with RabbitMQ
7+
AI Pipelines
LangGraph-based agent workflows designed and deployed
I am a Software Engineer with 3+ years of experience and a strong focus on AI/ML, building production-grade LLM systems, RAG pipelines, and scalable microservices processing millions of records daily. I have a proven ability to architect end-to-end solutions on AWS and Kubernetes, from vector search backends to real-time observability frameworks. I care about reliability, observability, and system design — building systems that hold up under real-world constraints.
Tempe, Arizona
Production-grade LLM systems, RAG pipelines, and agentic AI workflows with LangChain and LangGraph
Scalable microservices processing millions of records daily on AWS and Kubernetes
End-to-end backend engineering with Python, FastAPI, Flask, and event-driven architectures
Real-time observability and performance optimization with Prometheus, Grafana, and LangSmith
Skills & Technologies
AI/ML, backend engineering, cloud infrastructure, and observability
LangChain
LangGraph
RAG Systems
Qdrant
PyTorch
TensorFlow
Hugging Face
Python
Java
C++
SQL
JavaScript
FastAPI
Flask
REST APIs
Microservices
RabbitMQ
Async Programming
PyTest
AWS
Docker
Kubernetes
Helm
CI/CD
PostgreSQL
MySQL
MongoDB
DynamoDB
Redis
Prometheus
Grafana
LangSmith
Career Journey
Professional journey and key contributions
Current
AI Engineer
XNODE Inc.
•Jan 2025 - Present
📍 Westport, CT
Designing and building LangGraph-based AI agent workflows, GenAI backends, and production-ready RAG pipelines deployed on Kubernetes and AWS.
- Proposed and led design of LangGraph-based AI agent workflows across 7+ pipelines, presenting architecture decisions to cross-functional teams
- Partnered with backend engineers to develop a GenAI backend using Qdrant over 50k+ embeddings for context-aware retrieval
- Built asynchronous RAG pipelines with concurrent request handling, reducing query latency by ~25%
- Integrated LangSmith observability, identifying tool-call failures and reducing production errors by 25%
- Coordinated with DevOps to deploy containerized microservices on Kubernetes (RKE2) clusters on AWS
LangChainLangGraphPythonQdrantKubernetesAWSLangSmithDocker
Current
AI Engineer
XNODE Inc.
•Jan 2025 - Present
📍 Westport, CT
Designing and building LangGraph-based AI agent workflows, GenAI backends, and production-ready RAG pipelines deployed on Kubernetes and AWS.
- Proposed and led design of LangGraph-based AI agent workflows across 7+ pipelines, presenting architecture decisions to cross-functional teams
- Partnered with backend engineers to develop a GenAI backend using Qdrant over 50k+ embeddings for context-aware retrieval
- Built asynchronous RAG pipelines with concurrent request handling, reducing query latency by ~25%
- Integrated LangSmith observability, identifying tool-call failures and reducing production errors by 25%
- Coordinated with DevOps to deploy containerized microservices on Kubernetes (RKE2) clusters on AWS
LangChainLangGraphPythonQdrantKubernetesAWSLangSmithDocker
Software Engineer
Reliance Jio Infocomm Ltd.
•May 2022 - Aug 2024
📍 Hyderabad, India
Architected Python/Flask microservices processing 8-9M+ records/day across 10+ telecom regions for real-time network monitoring.
- Architected Python/Flask microservices processing 8-9M+ records/day across 10+ telecom regions
- Designed a Random Forest model for telecom coverage optimization, improving planning accuracy by ~25%
- Consolidated 10+ APIs into an asynchronous event-driven architecture using RabbitMQ, reducing latency by ~35%
- Optimized PostgreSQL schemas through indexing and partitioning on 8M+ records, reducing response time by ~40%
- Established CI/CD pipelines using GitHub Actions, increasing code coverage by ~30%
- Orchestrated Prometheus and Grafana dashboards for cross-team incident reviews and faster resolution
PythonFlaskPostgreSQLRabbitMQKubernetesDockerPrometheusGrafanaGitHub Actions
Software Engineer
Reliance Jio Infocomm Ltd.
•May 2022 - Aug 2024
📍 Hyderabad, India
Architected Python/Flask microservices processing 8-9M+ records/day across 10+ telecom regions for real-time network monitoring.
- Architected Python/Flask microservices processing 8-9M+ records/day across 10+ telecom regions
- Designed a Random Forest model for telecom coverage optimization, improving planning accuracy by ~25%
- Consolidated 10+ APIs into an asynchronous event-driven architecture using RabbitMQ, reducing latency by ~35%
- Optimized PostgreSQL schemas through indexing and partitioning on 8M+ records, reducing response time by ~40%
- Established CI/CD pipelines using GitHub Actions, increasing code coverage by ~30%
- Orchestrated Prometheus and Grafana dashboards for cross-team incident reviews and faster resolution
PythonFlaskPostgreSQLRabbitMQKubernetesDockerPrometheusGrafanaGitHub Actions
Academic journey & Achievements
Academic journey and achievements
Arizona State University
Master of Science in Information Technology
Tempe, Arizona
4.0/4.0GPA
Perfect 4.0 CGPA
Coursework: Data Structures & Algorithms, Distributed Systems, Advanced Database Systems, Machine Learning
Vellore Institute of Technology
Bachelor of Technology in Information Technology
Vellore, India
3.38/4.0GPA
3.38/4.0 CGPA
Coursework: Operating Systems, Computer Networks, Database Management Systems, Software Engineering
Featured Projects
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Let's Create Something Amazing
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Location
Tempe, Arizona
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