Aniket Singh

Software Engineer

Bengaluru, Karnataka, India5 yrs experience

Key Highlights

  • Expert in Elasticsearch and RabbitMQ integration.
  • Proven track record in backend development and system architecture.
  • Strong experience in optimizing search and sync processes.
Stackforce AI infers this person is a Backend Engineer with expertise in SaaS and system architecture.

Contact

Skills

Core Skills

Back-end Web DevelopmentTechnical ArchitectureElasticsearchRabbitmq

Other Skills

API DevelopmentAlgorithmsAmazon Web Services (AWS)Apache KafkaApplication Programming Interfaces (API)Asynchronous ProcessingC#Code RefactoringCode ReviewContinuous Integration and Continuous Delivery (CI/CD)DSAData StructuresDatabasesDeep LearningDesign Patterns

Experience

5 yrs
Total Experience
1 yr
Average Tenure
1 yr 1 mo
Current Experience

Linkedin

Software Engineer

May 2025Present · 1 yr 1 mo · Bangalore Urban, Karnataka, India · Hybrid

  • Building the tools infrastructure for content review and moderation at LinkedIn scale
Low Level ProgrammingProduct DevelopmentCode ReviewPostgreSQLPostgresKafka+55

Leena ai

SDE Il

Jun 2024May 2025 · 11 mos · Gurugram, Haryana, India · Remote

  • Worked in Backend Team for the core product Knowledge Management (KM) service which worked with NLP service to power the AI chatbot product for the company
  • 1) Led the Integration of Elasticsearch for Scalable Search
  • Designed and implemented Elasticsearch-based search to replace MongoDB’s text search, reducing search latency by 80 percent and improving relevance ranking.
  • Developed custom index mappings to efficiently index articles, FAQs, metadata, and user-generated content.
  • Implemented multi-field search, fuzzy matching, field boosting, and aggregations to enhance the search experience.
  • Integrated n-gram analyzers to improve partial word matching, making search results more intuitive and responsive.
  • Optimized indexing and query performance to handle millions of daily active users (DAU) across 500+ enterprise customers.
  • 2) Architected the KM–NLP Sync Process Using RabbitMQ
  • Engineered a batch-based sync mechanism to efficiently update the KM system with the latest NLP articles.
  • Designed an S3-based chunking system, where large article datasets were split into smaller chunks and stored in S3.
  • Processed article chunks asynchronously using the message broker RabbitMQ, replacing the old synchronous approach.
  • Deployed two separate containers for KM:
  • KM API container (for handling API requests).
  • KM worker container (dedicated for sync processing).
  • This architecture allowed parallel processing of article updates, improving performance and reducing sync latency by 90 percent.
  • The sync process ensures that KM articles remain up-to-date with NLP, enabling accurate chatbot responses.
Low Level ProgrammingProduct DevelopmentCode ReviewPostgreSQLPostgresKafka+55

Stealth startup

Backend Engineer(Founding Team)

Sep 2022Jun 2024 · 1 yr 9 mos · Delhi NCR · Remote

Societe generale

Software Engineer

Sep 2021Sep 2022 · 1 yr · Bangalore Urban, Karnataka, India · Hybrid

Cgi

Software Engineer Intern

Jun 2021Sep 2021 · 3 mos · Greater Bengaluru Area · Remote

Education

Birla Institute of Technology and Science, Pilani

Bachelor of Engineering

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