Job Title: Senior OpenSearch Engineer – eCommerce Search & AI Solutions

Location: Bangalore/Remote

Experience: 5–10 Years

Budget – As per the market

About the Role

We are looking for a highly skilled OpenSearch Engineer to build and optimize next-generation search experiences for our eCommerce platform. The ideal candidate will possess deep expertise in OpenSearch/Elasticsearch, vector search, semantic retrieval, and Amazon Bedrock-based GenAI solutions.

This role will be responsible for designing scalable search architectures that combine traditional keyword search with AI-powered semantic search, recommendation systems, and Retrieval-Augmented Generation (RAG) capabilities to enhance product discovery and customer experience.

Key Responsibilities

Search Platform Engineering

• Design, deploy, and manage enterprise-scale OpenSearch clusters.
• Build high-performance search solutions for product discovery, category browsing, filtering, autocomplete, and recommendations.
• Define and maintain index mappings, analyzers, tokenizers, synonyms, and ranking strategies.
• Optimize query performance, relevance scoring, aggregations, and search latency.
• Implement real-time and near real-time indexing pipelines for products, inventory, pricing, promotions, and customer data.

Vector Search & Semantic Search

• Design and implement vector indexing strategies using OpenSearch vector engine.
• Build semantic search capabilities using embeddings generated from foundation models.
• Configure and optimize:
  • Dense vectors
  • k-NN search
  • Approximate Nearest Neighbor (ANN)
  • Hybrid search (keyword + vector search)
  • Similarity search
• Implement product recommendations, related products, and personalized search experiences using vector embeddings.
• Evaluate search quality using relevance metrics and semantic retrieval benchmarks.

Generative AI & Amazon Bedrock

• Integrate OpenSearch with Amazon Bedrock Foundation Models.
• Develop Retrieval-Augmented Generation (RAG) solutions for conversational commerce and intelligent product discovery.
• Generate embeddings using Bedrock-supported models such as:
  • Amazon Titan Embeddings
  • Cohere Embed Models
  • Anthropic Claude (for AI-assisted search applications)
• Build AI-powered use cases:
  • Natural language product search
  • Conversational shopping assistants
  • Product recommendation systems
  • Catalog enrichment and metadata generation
• Optimize embedding pipelines, chunking strategies, and vector retrieval performance.

Platform Operations

• Monitor cluster health, indexing performance, and search analytics.
• Troubleshoot production issues and ensure high availability.
• Implement backup, disaster recovery, and security best practices.
• Automate deployments using CI/CD pipelines and Infrastructure-as-Code.

Cross-functional Collaboration

• Partner with Product, Data Science, Merchandising, and Engineering teams to improve search relevance and conversion rates.
• Conduct performance tuning and capacity planning exercises.
• Drive best practices for search architecture and AI-powered search solutions.

Required Skills

OpenSearch & Search Engineering

• 5+ years of experience with OpenSearch or Elasticsearch.
• Strong knowledge of:
  • Query DSL
  • Aggregations
  • Index lifecycle management
  • Search relevance tuning
  • Analyzers and tokenizers
  • Sharding and replication
  • OpenSearch Dashboards/Kibana

Vector Search & AI Search

• Hands-on experience with:
  • Vector databases and vector indexing
  • Embedding generation
  • Semantic search
  • Retrieval systems
  • Hybrid search architectures
  • RAG implementations
• Experience implementing:
  • k-NN
  • ANN algorithms
  • Similarity ranking
  • Embedding lifecycle management

Amazon Bedrock & GenAI

• Experience with Amazon Bedrock services and APIs.
• Knowledge of:
  • Foundation Models
  • Prompt Engineering
  • Embedding Models
  • Knowledge Bases
  • Agentic AI workflows
• Experience integrating Bedrock with OpenSearch for semantic retrieval and GenAI applications.

Software Development

• Strong programming skills in:
  • Java
  • Python
  • Node.js
  • Go (preferred)
• Experience building microservices and REST APIs.
• Understanding of distributed systems and scalability concepts.

Cloud & DevOps

• AWS Services:
  • OpenSearch Service
  • Bedrock
  • Lambda
  • ECS/EKS
  • DynamoDB
  • S3
  • API Gateway
• Docker and Kubernetes.
• CI/CD tools and Infrastructure-as-Code (Terraform/CloudFormation).

eCommerce Domain Expertise

• Product Catalog Search
• Merchandising Search
• Faceted Navigation
• Personalized Recommendations
• Semantic Product Discovery
• Conversational Commerce

Search Analytics & Conversion Optimization