Benudhar Behera · Lead Backend Engineer

About

Open to opportunities

$whoami

I build backend systems that scale, perform, and evolve — without breaking.

9+ years of experience building scalable backend systems, distributed architectures, and cloud-native platforms using Java, Spring Boot, Kafka, Python, FastAPI, and AWS.

I specialize in designing resilient, high-throughput systems with a strong focus on scalability, performance, and clean architecture.

Recently exploring GenAI, RAG, LLMs, and MCP — building intelligent applications that connect AI with real-world systems using Python FastAPI for high-performance API development and AI model serving.

System Design Cloud Architecture Tech Mentoring Event-Driven Microservices FastAPI

0

Years

0

APIs

0

Cloud Projects

0

Passion

"I enjoy solving complex engineering problems, simplifying architecture, and turning ideas into production-ready systems using both Java and Python ecosystems."

Experience

◆

Lead Backend Engineer

Ernst & Young (EY) · Bangalore

2024 – Present

Architected and delivered cloud-native backend and GenAI platforms using Java 21, Spring Boot, Kafka, Python, FastAPI, RAG, and vector search.
Built RAG-powered AI solutions with semantic search and vector databases, supporting 70+ requests/min with low-latency responses.
Improved API performance by ~40% through caching, asynchronous processing, JVM tuning, database optimization, and efficient service design.
Implemented secure distributed systems using OAuth2, Keycloak, RBAC, and centralized authentication/authorization.
Designed AI-ready architectures using LLM tool calling, MCP, and agentic workflows for intelligent enterprise automation.

Java 21Spring BootKafkaPythonFastAPIRAGVector DBAWS

◆

Senior Backend Engineer

Wipro Limited · Bangalore

2021 – 2024

Designed and developed event-driven microservices using Java, Spring Boot, and Kafka for a large-scale enterprise platform.
Built Python-based data processing pipelines and analytics APIs using FastAPI, serving real-time insights to stakeholders.
Improved API response time by 30% via query optimization, caching strategies, and database indexing.
Led the migration of legacy monolithic services to cloud-native microservices on AWS ECS and Kubernetes.
Established robust test automation with JUnit 5, Mockito, and Pytest, reducing production defects by 25%.

JavaSpring BootKafkaPythonFastAPIAWSDockerKubernetes

◆

Backend Engineer

ITC InfoTech · Bangalore

2020 – 2021

Built cloud-native services for e-commerce (order management, payment processing, inventory tracking) using Spring Boot and AWS.
Architected event-driven workflows with Kafka for asynchronous processing and decoupled service communication.
Designed idempotent APIs and resilient payment workflows ensuring transactional integrity and fault tolerance.
Improved code maintainability with SOLID principles, clean architecture, and design patterns.

Spring BootKafkaAWSPostgreSQLRedis

◆

Software Engineer

Silicon Tech Lab · Bhubaneswar

2017 – 2020

Developed ERP backend modules with Spring MVC, Hibernate, and PostgreSQL, serving 500+ concurrent users.
Implemented reusable business components and service layers for core ERP functionalities (finance, HR, inventory).
Resolved production issues via root cause analysis, performance tuning, and database query optimization.

Spring MVCHibernatePostgreSQLJava 8

Skills

Backend

JavaSpring BootSpring Cloud WebFluxHibernateJPA PythonFastAPIDjango

Cloud & DevOps

AWS (Lambda, EC2, EKS, S3)DynamoDB CloudWatchIAM DockerKubernetesTerraform

Databases

MongoDBPostgreSQL RedisMySQLDynamoDB

Messaging

KafkaRabbitMQ SNSSQS

AI & GenAI

OpenAIRAGLangChain Vector DBPrompt Engineering MCPFastAPI

Observability

PrometheusGrafana ELKSplunkCloudWatch

Projects

View all repositories →

distributed-job-scheduler

Scalable distributed job scheduling service supporting cron-based execution, task orchestration, retries, fault tolerance, and distributed processing using Spring Boot, Kafka, MongoDB, Docker, and Kubernetes.

Public

Java ⭐ 9🔄 3

smart-document-hub

Smart Document Hub is an enterprise-grade, cloud-native document management system built with Spring Boot and AWS services. It provides intelligent document processing, storage, search, and analytics capabilities with a focus on scalability, security, and performance.

Public

Java ⭐ 7🔄 2

mcp-fin-lab

Production-oriented AI finance platform built with Java 21, Spring Boot, Spring AI, OpenAI, and MCP, combining LLM-powered natural-language interactions, dynamic tool discovery, real-time financial data, and scalable event-driven services.

Public

Java & Python ⭐ 12🔄 4

agentic-finance-ai

Finance AI Service — a Spring Boot–based GenAI backend for a personal finance assistant, combining LLM chat, RAG-grounded document Q&A over uploaded financial documents (pgvector), and agentic routing to decide when retrieval is needed

Public

Java ⭐ 8🔄 2

Certifications

5 certifications & counting

🏛️