# Sharad Babar

> Software Engineer | 4+ Years Experience | Java, Spring Boot, Microservices, Distributed Systems | AI & Cloud (AWS, Kubernetes)

Location: New York, New York, United States
Profile: https://flows.cv/sharadbabar

I’m a software engineer with 4+ years of experience building scalable backend systems and full-stack applications across healthcare, financial services, and supply chain platforms. I enjoy designing software that solves real problems and performs reliably at scale.

My core focus is backend engineering. I primarily work with Java and Spring Boot, building microservices, designing APIs, and working with distributed systems that process large volumes of data. I enjoy thinking through system design challenges like how to make services scalable, resilient, and easy for teams to maintain in production.

Recently, I’ve been working on AI-powered knowledge retrieval systems, building platforms that use embeddings, vector databases, and LLM-based workflows to help researchers quickly discover insights from large collections of clinical and regulatory documents. It has been exciting to work at the intersection of backend engineering and AI infrastructure, designing systems that enable intelligent search and contextual information retrieval.

Before that, I worked on fintech payment platforms, developing backend services and event-driven pipelines for wallet transactions, merchant payments, and real-time balance updates. These systems required high reliability, strong security controls, and low latency because they handled large volumes of financial transactions.

Technically, I work most often with Java, Spring Boot, microservices, Kafka, PostgreSQL, Redis, and cloud infrastructure on AWS, along with containerization and orchestration tools such as Docker and Kubernetes. I enjoy building systems that are not only scalable but also well-designed and maintainable.

What I enjoy most about engineering is solving complex problems with simple, thoughtful solutions and collaborating with teams that care about building reliable, high-quality systems.

I’m always interested in connecting with people working on backend platforms, distributed systems, and AI-driven applications.

## Work Experience
### Software Engineer @ Johnson & Johnson
Jan 2025 – Present | New Brunswick, New Jersey, United States
At Johnson & Johnson, I work on building scalable backend services for an AI-driven clinical knowledge retrieval platform designed to help researchers and clinicians quickly access insights from large collections of medical literature and clinical trial data. I develop microservices using Java, Spring Boot, and reactive frameworks, design secure REST and GraphQL APIs, and integrate AI-powered document retrieval workflows using LangChain, Hugging Face models, and vector databases to enable semantic search across millions of documents. My work also involves improving system reliability and observability using tools like Prometheus, Grafana, and OpenTelemetry, while ensuring secure access control, high availability, and performance across distributed cloud-native systems.

### Software Development Engineer @ Barclays
Jan 2022 – Jan 2023 | India
• Programmed backend microservices using Java (Spring Boot) for digital wallet top ups, merchant payments, and transaction history APIs, designing
scalable, fault-tolerant services with sharding, partitioning, and concurrency controls, supporting 98% SLA, sub-250ms API response times.
• Designed and implemented secure RESTful and GraphQL APIs with JWT/OAuth2 authentication and PCI DSS-compliant tokenization for card and
wallet data, incorporating efficient data structures and algorithm optimizations to reduce latency and sensitive data exposure risk by 98%.
• Formed responsive mobile front-end modules using React Native and TypeScript for wallet UI, payment flows, QR scanning, and real-time balance
updates with WebSockets and Redux, applying reactive programming and optimized state, increasing transaction completion rate by 22%.
• Engineered real-time payment pipelines with Apache Kafka, Redis caching for session & balance, and PostgreSQL for transactional consistency,
using queue partitioning, event-driven design, and distributed caching to achieve reliable sub-200ms balance updates during peak operations.
• Deployed cloud-native infrastructure on AWS using EKS (Kubernetes), API Gateway, Lambda serverless functions, and RDS Aurora with multi-AZ
failover, applying system design principles for auto-scaling, high availability, and disaster recovery, achieving 99.99% uptime.
• Established CI/CD pipelines with GitHub Actions, Terraform IaC, automated unit/integration tests (JUnit, Jest), and blue/green releases on
Kubernetes, integrating test-driven design to reduce rollback incidents by 60% and ensure production stability.

### Software Engineer @ Accenture
Jan 2020 – Jan 2022 | India
• Integrated third-party carrier APIs, ERP systems, and payment gateways with backend services to enable real-time shipment tracking, order
fulfillment updates, and transaction validation, improving on-time delivery visibility by 28%.
• Configured backend microservices using Node.js and Express.js for inventory management, order processing, and logistics workflows, reducing
order processing latency by 33% and supporting concurrent warehouse operations.
• Optimized MongoDB data models for warehouses, shipments, and order transactions, implementing indexes, aggregation pipelines, and sharding
strategies, reducing inventory query times by 42%.
• Formulated interactive React.js dashboards for supply chain managers to monitor shipments, track inventory levels, and generate analytical
reports, increasing operational decision-making efficiency by 22%.
• Led migration of legacy order and inventory data to MongoDB Atlas, designing ETL pipelines that ensured zero data loss, improved multi-region
replication, and reduced reporting latency by 30%.
• Orchestrated CI/CD pipelines using Jenkins and GitHub Actions, containerized Node.js services with Docker, and deployed on Kubernetes with
Helm charts, enabling automated and consistent deployments across staging and production.
• Executed automated unit and integration tests using Jest and Supertest, achieving 80%+ backend coverage while enforcing JWT-based role-based
access control for customers, admins, and vendors, reducing production defects by 33%.


## Education
### Master of Science - MS in Computer Science
Binghamton University

### Bachelor of Engineering - BE in Computer Engineering
Savitribai Phule Pune University

### Diploma of Education in Information Technology
MIT World Peace University


## Contact & Social
- LinkedIn: https://linkedin.com/in/sharadbabar10
- Website: https://sharadbabar10.hashnode.dev
- Website: https://sharadbabar.com

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Source: https://flows.cv/sharadbabar
JSON Resume: https://flows.cv/sharadbabar/resume.json
Last updated: 2026-04-05