Backend Engineering Lead

Backend Engineering Lead – Java, Python & AI-enabled Systems.

Job Highlights

Lead the design, development, and scaling of backend systems for a high-performance e-commerce platform.

Architect and build scalable, fault-tolerant microservices using Spring Boot.

Drive AI-assisted development practices using tools like GitHub Copilot, Cursor, or similar.

Own end-to-end backend delivery including design, development, testing, deployment, and monitoring.

Ensure high system performance through load testing, performance tuning, and observability practices.

Work closely with product, frontend, and QA teams to deliver robust and scalable features.

Improve unit testing, integration testing, and debugging using AI assistance

Work with and integrate Python-based services for AI, data processing, chatbot and automation use cases.

Total experience: 4 – 6 years in Java development.

Key Responsibilities:

Lead the architecture, design, and development of scalable backend systems for our e-commerce platform

Build and optimize REST APIs used across mobile apps, websites, CMS.

Drive adoption of microservices architecture at both application and database levels.

Conduct code reviews, performance tuning, and troubleshooting of production systems.

Promote and guide the team in effective use of AI tools for development, testing, and debugging

Contribute to CI/CD pipelines and cloud deployments

Integrate and leverage Python-based services where applicable (e.g., AI integrations).

Required Skills & Qualifications

Strong expertise in Java (8+) and Spring Boot

Working knowledge of Python is a must

Knowledge of AI/ML integration in backend systems is a must

Hands-on experience with Microservices Architecture

Deep understanding of REST API design and best practices

Experience with ORM frameworks (JPA/Hibernate)

Strong experience with PostgreSQL and NoSQL databases

Experience in e-commerce domain (consumer end)

Exposure to event-driven architecture (Kafka, RabbitMQ)

Good to Have

Experience in analytics systems using bigquery.

Familiar with cloud platforms (AWS/GCP) and containerization

Exposure to libraries/frameworks (FastAPI, Flask, Pandas, etc.) is a plus

Education: B.Tech / BE / M.Tech / MCA.