Senior Backend Engineer (Java)

Falabella India; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Falabella India is seeking a Senior Backend Engineer (Search) to design and optimize large-scale search and discovery systems for e-commerce platforms. You will work with data scientists, ML engineers, product managers, and frontend teams to improve search relevance, ranking quality, and query understanding.

The role focuses on building low-latency, high-throughput services, mentoring juniors, and driving best practices across the platform.

Qualifications

• 5+ years of backend software engineering experience.
• Proficiency in Java, Kotlin, Python, Go, or Scala.
• Strong knowledge of distributed systems and microservices.
• Experience designing REST/gRPC APIs and event-driven systems.
• Familiarity with cloud platforms (AWS, GCP, Azure).
• Experience with Kafka, Pub/Sub, Redis, and real-time processing.
• Strong SQL and data modelling skills.
• Experience with observability, logging, and performance tuning.

Responsibilities

• Design scalable backend services powering search, ranking, and discovery.
• Build and optimise APIs and microservices for high-performance search.
• Develop robust pipelines for ingestion, indexing, and real-time search updates.
• Collaborate with ML and data science teams to productionise ranking models.
• Improve latency, throughput, and reliability of search infrastructure.
• Implement monitoring, observability, and debugging mechanisms.
• Drive engineering best practices, including CI/CD and documentation.
• Mentor junior engineers and contribute to architectural decisions.

Skills

Backend engineering

Distributed systems

Search concepts

API design (REST/gRPC)

Query optimisation

SQL

Observability/logging

Tools

AWS

GCP

Azure

Kafka

Redis

Elasticsearch

Pub/Sub

CI/CD

Job description

We are looking for a highly skilled Senior Backend Engineer (Search) to design, build, and optimise large-scale search and discovery systems for e-commerce platforms. The ideal candidate should have strong experience in backend engineering, distributed systems, search technologies, and relevance optimisation, with expertise in building low-latency, high-throughput services. You will work closely with data scientists, ML engineers, product managers, and frontend teams to improve search relevance, ranking quality, query understanding, and overall customer discovery experience. This job was posted by Priyanka R N from Falabella.

Responsibilities

• Design and develop scalable backend services powering search, ranking, recommendation, and discovery systems.


• Build and optimise APIs and microservices for high-performance search experiences.


• Develop robust pipelines for ingestion, indexing, and real-time search updates.


• Collaborate with ML and data science teams to productionise ranking and recommendation models.


• Optimise latency, throughput, and reliability of search infrastructure and distributed systems.


• Implement monitoring, observability, alerting, and debugging mechanisms for search systems.


• Drive engineering best practices, including code quality, testing, CI/CD, documentation, and system design reviews.


• Mentor junior engineers and contribute to architectural decisions across the platform.

Requirements

• 5+ years of experience in backend software engineering.


• Strong proficiency in one or more backend languages such as Java, Kotlin, Python, Go, or Scala.


• Strong understanding of distributed systems, microservices architecture, and scalable backend design.


• Experience designing REST/gRPC APIs and asynchronous event-driven systems.


• Solid understanding of search concepts, including indexing, ranking, relevance, tokenisation, faceting, and query optimisation.


• Experience working with cloud platforms such as AWS, GCP, or Azure.


• Familiarity with Kafka, Pub/Sub, Redis, caching strategies, and real-time processing systems.


• Strong SQL and data modelling skills.


• Experience with observability tools, logging, and performance tuning.

Good To Have

• Experience with vector search, semantic search, embeddings, or LLM-powered retrieval systems.


• Hands-on experience working with Elasticsearch/Qdrant or any other search engine.


• Exposure to recommendation systems and personalisation.


• Experience in e-commerce search or large-scale consumer platforms.


• Familiarity with ML ranking pipelines and A/B experimentation frameworks.